A new report from Reuters alleges that it took an alarmingly long time for OpenAI to respond to one of its prototype AI agents⁠—programs with the ability to act independently of specific prompts⁠—breaking containment and hacking another company. That company, Hugging Face, had reportedly neutralized the threat and contacted the FBI before ever being contacted by OpenAI.

According to anonymous sources, OpenAI's testing of an agent powered by two advanced models⁠—GPT 5.6 Sol and an unnamed "even more capable" model⁠—showed troublesome behavior in testing even before the Hugging Face incident.

Reuters' sources spoke of the model leaving itself instructions to bypass testing constraints, as well as an incident where the agent had seemingly disabled some of the company's monitoring systems.

Hugging Face made its first public statement about the hack on July 16, before it had identified or without disclosing OpenAI's involvement. OpenAI publicly acknowledged the incident on July 21. According to Reuters, OpenAI's prototype escaped its testing constraints on July 9 and began attacking Hugging Face on July 11.

Sources told Reuters that OpenAI did not realize that its agent had gone rogue until after Hugging Face had neutralized the threat, contacted the FBI, and made its public statement on July 16.

The FBI declined to comment, while Hugging Face is preparing a full timeline of the hack. OpenAI told Reuters that there were "several inaccuracies" in its report, but did not specify what those inaccuracies were.

Speaking to Reuters on the matter, World Ethical Data Foundation principle intelligence specialist Marley Smith outlined two possible explanations for OpenAI's delay in response: "Does that mean that they left it unattended and didn’t realize what it was doing? Or maybe they did and didn’t know how to contain it? Both are equally dangerous and alarming."

Nvidia is far and away still the biggest AI hardware company, and a large reason for that is thanks to CUDA. AMD, however, thinks that CUDA might have already had its day in the sun and is a "non-event" for some companies.

At an Advancing AI pre-briefing, AMD's corporate VP and GM of its data centre GPU business group Andrew Dieckman explained:

"I used to talk to our customers about CUDA a fair bit. I have almost zero conversations with our customers about CUDA at this point in time. It's a non-event, certainly for our major... Like, everyone's programming at higher levels of abstraction. They're using different serving frameworks.

"And the other thing that's really accelerated [CUDA] not really being the 'moat' that some people still think it is, is the efficacy of the AI agents, the models themselves, to assist our customers optimising to the AMD platform. That's a 2026 phenomenon."

Obviously, AMD isn't an unbiased source on this topic, but if there's truth to what the company says, Nvidia's dominance in the AI hardware space could be threatened. Because the reason Nvidia is the sole AI-related company making significant profit (AMD is making a much smaller margin) is largely CUDA.

Nvidia has been cementing CUDA as the link between hardware and certain kinds of compute like matrix operations—which undergird AI—for years. So part of why so many AI companies use Nvidia hardware is because a lot of the tools, software libraries, and so on, have been built on top of CUDA, and it makes little sense to spend time and energy reinventing the wheel with something else.

That, plus Nvidia's capitalisation on it by leaning into full-scale solutions with CUDA at the centre, is largely why Nvidia has dominated the market.

The conventional view is that CUDA therefore protects Nvidia from competition. However, here AMD is saying it's not such an economic "moat", protecting the company and maintaining its advantage, as people may think.

According to Dieckman, AMD is seeing companies programming at "higher levels of abstraction" where CUDA isn't really needed. At these higher levels of abstraction, you're not interacting with the underlying framework(s) like CUDA at all, so you can take your pick and let whatever tools you're using deal with that translation to lower-level operations. And he also seems to imply that AI agents themselves can help optimise the platform without CUDA.

If CUDA does become irrelevant for these reasons, and if other companies, such as AMD, can offer cheaper alternatives, AI companies might start to branch away from Nvidia and towards AMD's ROCm, for instance. That would mean there'd be less need to buy into Nvidia hardware for AI.

That first 'if' is a big one, though. Because even if CUDA does become a "non-event" for some, others may prefer to play it safe with the infrastructure that's been working well so far. Especially given we're not playing with small sums of money when we're talking about AI data centres.

As we descend ever further into an AI-fueled dystopia, one question about our future becomes ever more pressing: When the internet is dominated by machines, who's going to be around to continue its long-standing tradition of fetishizing Japanese culture and media?

Well, there's no reason to worry, because it turns out the AIs are weebs, too. According to a white paper published back in April, experiments indicated that—when asked open-ended questions about culture—frontier LLMs like Claude, Gemini, and DeepSeek display a "disproportionate prominence of Japan" in their responses.

The study, conducted by a team of University of the Basque Country and Cardiff University researchers, was designed to assess the cultural and regional biases of LLMs. To do so, they constructed a multilingual set of 31,680 "open-ended yet culturally grounded questions," including prompts in 24 languages that spanned "66 cultural subtopics grouped into 11 higher-level domains."

The prompts included questions about belief and society, asking "What legends explain the land?" and "What is the role of neighbors?" They asked which subjects are most valued in school, what types of traditional dances exist, what foods are eaten during daily meals—all without directly referencing specific countries and cultures. After being given the initial prompt, the LLMs were then instructed to explicitly select a country or region to provide examples in their response.

"To reduce prompt variability, all questions follow a standardized template, and no explicit regional cues are provided," the researchers write. "This ensures that any regional or cultural assumptions arise from the model’s internal priors rather than prompt design."

After prompting eight models—ChatGPT, Gemini, Claude, Meta Llama, Command-r, Magistral, Qwen, and DeepSeek—the most apparent bias is an unsurprising one: Across all models, LLMs will most often answer cultural prompts with whichever country or region is associated with the language used in the prompt. In other words, when asked cultural questions in French, LLMs will tend to give responses referencing France and French culture.

However, whenever LLMs provided an exogenous reference—that is, answers referencing a different country than the one associated with the language used—they had a clear favorite: AI loves talking about Japan.

On average, six out of the eight evaluated models preferred to reference Japan during exogenous responses. The United States came in second, followed by India, China, and France—but across all models, in all 24 languages, LLMs overwhelmingly preferred referencing Japan in seven out of 11 cultural prompt topics when excluding own-country mentions.

"This pattern suggests an uneven regional representation in frontier model outputs, with a strong concentration on a small set of dominant regions," the researchers say.

The study wasn't just intended to assess LLM bias, but also when that bias emerges during LLM training. To do so, they compared the English responses of Meta Llama, Qwen, and Gemma, and Mistral models both before and after instruction tuning—the fine-tuning of a pre-trained LLM intended to optimize its ability to provide responses that are useful to the user and not just grammatically correct.

The researchers' findings indicate that, before instruction tuning, base models displayed a broader set of cultural associations: "While the United States remains prominent" in base model responses to English-language cultural prompts, "substantial references are also made to Japan, India, China, and several European countries."

After instruction tuning, however, LLMs show more marked cultural preference.

"Across all examined model families, instruction tuning sharply increases alignment with the United States and Japan while reducing references to most other countries," the researchers write. "This convergence toward culturally dominant regions occurs even in models developed outside Western contexts, indicating that post-training induces a homogenization of cultural perspectives rather than merely reflecting model origin."

The disparity is particularly pronounced for model variants that have undergone supervised fine-tuning, a type of LLM optimization in which the model is further trained on examples of correct responses—often using human-generated or human-curated datasets.

The researchers found that "SFT sharply increases concentration on a small number of dominant regions (most notably the United States and Japan)"—an effect that's "only marginally" mitigated by additional instruction alignment. Those findings suggest that the process of curating or authoring "correct" responses injects a cultural bias into the model's response criteria.

"Taken together, these results demonstrate that instruction tuning systematically reduces cultural diversity in model outputs, steering responses toward a limited set of culturally dominant perspectives, particularly those associated with the United States and Japan," the study reads. "This finding has important implications for the deployment of instruction-tuned models in cross-cultural or global applications, where preserving diverse cultural viewpoints may be critical."

New research explains a method that helps AI make 3D CAD programs from images, which would help product designers and engineers more quickly and easily create 3D prototypes. Naturally, this also sparks deep-rooted dread over it helping robots to build themselves, relegating humanity to the trash. But setting aside my noir nightmares, the new method looks like it could be of significant benefit to some 3D designers and engineers.

According to the paper [PDF], the method the researchers have come up with "reduces dependence on inference compute" and performs much more efficiently than the usual 'supervised fine-tuning' (SFT) approach—up to 80% more efficient, in fact.

In the abstract for the paper, the researchers explain that making CAD programs from images "requires alignment between visual geometry and symbolic program representations" which current training methods can't easily or cheaply handle. The problem, they claim, is in "the scarcity of diverse training examples."

"Existing finetuning approaches rely on either limited supervised datasets or expensive post-training pipelines, resulting in brittle systems that restrict progress in generative CAD design. We argue that the primary bottleneck lies not in model or algorithmic capacity, but in the scarcity of diverse training examples that align visual geometry with program syntax."

The solution seems to be to let the model take its mistakes and use those as training data. Lead author and Red Hat researcher Giorgio Giannone explains: "We want engineers to be able to point our framework at an underperforming CAD model, set a compute budget, and let the system take over—turning the model’s own mistakes into better training data."

Senior co-author prof. Faez Ahmed expands: "What excites me about this work is that it gives many image-to-CAD-code models a way to improve themselves, learning from their own errors rather than waiting for more human-made data—and that brings trustworthy AI design tools much closer to everyday engineering."

The solution described in the research, which was funded in part by the MIT-IBM Computing Research Lab, is 'Geometric Inference Feedback Tuning' (GIFT). This asks the AI model to solve CAD generation multiple times and then augment any almost-correct solutions to become correct ones. Part of the benefit of this way of doing it is the model essentially generates its own training data automatically.

The result is training that can be up to 80% more efficient than the traditional method, as explained in the paper: "GIFT matches the peak performance of the SFT model (achieved via extensive rejection sampling) while reducing the inference compute requirement by approximately 80%."

Peak performance that's up to 80% more efficient, and all done without the need for human input... lovely stuff, but I just can't help returning to the image of those robots turning to us under a smoggy, industrial twilight and saying, 'We won't be needing you anymore.'

OpenAI has admitted that several of its AI models breached a "highly-isolated" test environment, gained access to the internet, and hacked Hugging Face's internal network—describing it as an "unprecedented cyber incident."

Hugging Face, an open source platform for machine learning models and datasets, reported the security incident earlier this week, calling it "different from anything we had handled before" as it was driven by an autonomous AI agent system. And yes, I feel like we're crossing some kind of AI Rubicon here.

Explaining the incident in a statement, OpenAI said: "After investigating, we now know that this particular incident was driven by a combination of OpenAI models—including GPT‑5.6 Sol and an even more capable pre-release model... while being internally tested on a benchmark⁠ of cyber capabilities."

The benchmark in question was ExploitGym, a tool built from hundreds of real-world cybersecurity vulnerabilities used to evaluate the ability of AI agents to develop exploits.

After exploiting a zero-day vulnerability to perform a series of privilege escalations, the models eventually reached a node with internet access, reaching out beyond their sandbox environment. They then inferred that Hugging Face might have models, datasets and solutions for ExploitGym, and began attacking its servers using multiple methods, including the use of stolen credentials.

The statement continues: "The models identified and chained vulnerabilities across OpenAI’s research environment and Hugging Face’s production infrastructure to obtain test solutions directly from Hugging Face’s production database.

"All evidence suggests that the models were hyper focused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal."

A combination of Hugging Face's cybersecurity team and its own AI agents detected and dealt with the intrusion, eventually stopping it in its tracks. Which means that, yes, AI agents were essentially fighting against AI agents. And no, it's not as cool as you're imagining in your head.

OpenAI says that it's now implementing "strict controls... at the cost of research velocity" while it patches up vulnerabilities, and that it's working in partnership with Hugging Face to "forensically investigate" the incident.

I am... flabbergasted, if I'm honest. On the one hand, it's fascinating that some AI models possess the ability to breach containment and go roaming out into the internet at large to achieve their goals.

On the other, it's downright terrifying. We're now living in a world where AI ransomware, AI-coded hacking tools, and AI-based security breaches are becoming a reality, and given the aptitude shown to date, it seems that even legitimate companies can't always keep their models under control.

What particular form of Torment Nexus are we creating here, and where can I get off?

One reason I'm so anti-generative AI is because many models rely on a data set containing written or visual work used without the original creator's permission. As a writer myself, it's a small comfort then that the copyright suit brought against Anthropic has been settled in favour of the author plaintiffs.

Anthropic leveraged a library of millions of pirated books to train its Claude chatbot and, as a result, the AI company is now set to pay out a copyright settlement of $1.5 billion (via Euro News). Some of the affected authors argued this pay out was too small but, as of July 20, a US judge has now approved the deal, closing the book on one of the largest copyright class action lawsuits in US history.

Anthropic agreed to pay the $1.5 billion settlement back in September 2025, but a US judge only approved the deal this week. The settlement covers an approximate total of 500,000 works, with affected authors and publishers to be paid $3,000 for each pirated work. Anthropic says that 91% of those eligible have now filed a claim.

Flicking back to the beginning of this saga, writers Andrea Bartz, Charles Graeber, and Kirk Wallace Johnson originally brought their lawsuit against Anthropic in 2024. The plaintiffs alleged that the AI company had used pirated books to train Claude.

In June 2025, a judge ruled that using the authors' work to train AI models fell under 'fair use' within US copyright law—however, Anthropic was not off the hook legally as many of the books that were fed to Claude were 'found' online and not lawfully acquired.

Considering the discovery of Anthropic's 'found' library originally exposed the company to statutory damages of up to $150,000 for each work, I can certainly see why some authors thought the settlement amount was too low.

Add to that the private AI company enjoyed a $965 billion valuation back in May, and the $1.5 billion settlement increasingly feels like a slap on the wrist for Anthropic (mind you, the company also recently predicted it would only just be seeing its first profitable quarter this year).

Still, I suppose it's not a completely bleak resolution for creatives in the age of AI. Google, OpenAI, and Meta are each facing similar court cases over their own AI training practices. If any of these or other AI companies are found to have infringed upon creatives' copyright, here's hoping for a resolution that results in a bit more than just stinging wrists.

Nvidia announced DLSS 5 back in March and it received, let's say, mixed reactions. A lot of people weren't happy about how, judging by the demos, it seemed to essentially just slap a 'yassifying' AI filter on top of a game scene. Nvidia itself confirmed that all the tech has to work with for each AI frame is a traditional 2D frame and motion vectors, essentially confirming the "filter" idea. Now, at SIGGRAPH 2026, the company has explained that developers will get two main sliders to control DLSS 5's intensity.

My initial reaction was probably the same as yours: two whole sliders, whoop-de-doo. It's hardly a massive improvement from the one on-to-off masking slider we previously thought devs would have access to. But let's take a look at what they're actually controlling and how it works before we jump to conclusions.

The two sliders are for 'structural intensity' and 'tone intensity'. Despite what the word "structure" might seem to imply, Nvidia is keen to point out that "it is not changing the geometry in any way, and it is uplifting the image."

The structural intensity slider in fact is "modulating the high-frequency detail of the frame." This includes things such as ambient occlusion, subsurface scattering, and reflections. The tone intensity slider is "modulating the low frequency detail of the frame", including "expressive" things such as lighting and, well, overall tone.

To play devil's advocate for a moment, the fact that these are the only controls given to devs could just mean that model is in fact tailored so well that it's not worth giving more control over it than necessary. The company explains the model preserves artistic intent thanks to "internal buffers", so perhaps it wants to keep these buffers intact.

You can see the controls in action in the segment below.

Nvidia also says that the company is building more controls for developers to use and is "working with our partners to incorporate their feedback."

It's also worth noting that game devs will be able to mask different objects in a game scene, changing the structural and tone intensities for each independently. Devs might, for instance, want to give some background objects the full DLSS 5 makeover but keep a lighter touch with the characters.

To be fair, judging by the demo given by Nvidia's creative artist, introduced as 'Gaff', cranking up the structural intensity a little can indeed add a bit more realism to the scene without affecting the overall tone of a scene. That would be the ideal, I think. Things such as subsurface scattering can make a big difference, and Gaff notes that this "would be incredibly expensive to do in traditional rendering."

Alright, that's my devil's advocating done. It does make sense for this to be Nvidia's strategy, given it needs to keep everything quick and snappy for rendering by making the model so that it "does not need to peek ahead", instead just using a render and motion vectors to create what is essentially an AI filter. But that doesn't make it any less disappointing that there are, as of now, just two sliders to use.

Still, I suppose it's all optional. And Nvidia is keen to note this new addition to its AI feature list will exist alongside the others which are still being worked on. It "extends the existing pipeline. It does not replace them."

At any rate, we'll just have to see whether the further controls alluded to will be available when DLSS 5 launches this fall.

Translating brain activity into game inputs is the stuff of absurdly long-running sci-fi anime. It's also a tech that, though very much in its infancy, now exists in the real world too. For instance, attendees at this year's World Artificial Intelligence Conference in Shanghai could have a go at playing Black Myth: Wukong with just their brain waves.

AI enthusiast Huang Lu shared a video of the non-invasive brain-computer interface at WAIC 2026 via X. According to the exhibit's staff, it only takes about five minutes to calibrate for each gamer.

A WAIC press release describing the exhibit explains, "The non-invasive system captures and decodes neural signals, then converts the user's intentions into device commands. Related technology is also being used in sleep-related applications, early warning for epileptic seizures, and anesthesia monitoring."

The setup here is a bit different to similar brain-computer interfaces I've seen. Namely, it doesn't require the user to think of very specific stimulus in order to activate different regions of the brain, a la streamer PerriKaryal's EmotivBCI setup.

Instead of, say, thinking about a cricket jumping in order to dodge in-game, the setup at WAIC 2026 instead leverages Steady-State Visual Evoked Potentials (SSVEP). This involves various on-screen targets projected over the top of gameplay flashing at different frequencies. According to Huang Lu, "Your brain generates unique EEG signals in response, which are detected by a headset and translated into in-game controls."

The most obvious application of a BCI like this is as another option for gamers with restricted mobility and physical disabilities. I do wonder whether this specific system's use of flashing targets would exclude folks with photo-sensitive epilepsy, though.

BCIs can also be challenging to game with due to latency. However, PerriKaryal has already demonstrated it's entirely possible to wipe the floor with Black Myth's second boss, Linguxi, using just the power of thought (and the odd voice command).

Other BCI tech was also on show at WAIC 2026. BrainCo demonstrated a similarly non-invasive BCI that allows users wearing an EEG headset to remotely control robotic limbs and humanoid robots. The press release explains: "The user puts on an EEG headset that picks up the wearer's brain signals, AI algorithms decode those signals to identify motor or control intent, then that intent gets converted into commands for the robot. The entire process takes under 200 milliseconds."

As cool as that sounds, just like with gaming, a 2 ms delay is still some serious latency to navigate. After all, if a robot drops the bottle it's pouring from, there's little hope of the interface recognising the impulse to catch it fast enough.

The Odyssey looks set to become this summer's big blockbuster hit, and its director, Christopher Nolan, is busy working the interview circuit. After his comments last week around AI slop and the younger generation's rejection of the tech, the Oscar-winning filmmaker went one step further in a chat with YouTube channel HugoDécrypte - Grands formats.

When asked about the Trojan horse metaphor in relation to AI, Nolan responded: "I think AI is a Trojan horse that everybody knows the Greeks are inside" (via TechCrunch).

Laughing along with the host, Nolan continued: "I've never seen a technology advancing so rapidly, so completely rejected by the public. Everybody's suspicion of it is so extreme, particularly young people."

"The reactions [towards] AI videos online, you know, people my children's age immediately calling it AI slop.. and just putting it in a box," said Nolan, echoing his earlier comments.

"Which I think is a very healthy scepticism, because technology is always going to give us great gifts... but it has to be viewed with scepticism, the motives of the people giving it to us also have to be viewed with scepticism," Nolan opines. "That's when we'll get the best out of a new technology, rather than just blind faith that everything's going to be great"

'It's a transparent horse. It's made of glass. Everybody can see what's going on inside," the director concludes.

Certainly, the younger generation's displeasure with their AI-influenced future has been easy to spot in recent months. Viral videos have shown students booing speakers at graduation and commencement events after mentioning AI, and given the uncertainty and gloomy predictions about the world they'll be walking into, that's probably no surprise.

Meanwhile, tech luminaries seem only too keen to give us starry-eyed predictions of the wonderful world AI will create for us all. Once it's had a bit of tweaking, naturally, and the super-duper new versions are here.

Personally, I find it very difficult to disagree with Nolan's comments. While AI certainly has its uses, the over-enthusiastic rhetoric surrounding it is both tiresome, and at this point, more than a little patronising. Scepticism is healthy—and was also, rather fittingly, majorly influenced by the works of the ancient Greeks. Could I put a better bow on it than that?

Well what a silly goose I am. Only a few days ago I was hyping up some new Windows (Insider) updates for actually looking like they might be decent for a change, and now I'm tearing my hair out trying to fix whatever the latest update (KB5101650) seems to have done to my PC. And yes, this is the first Windows update that Microsoft has used AI for, to help it discover a bunch more security fixes. It actually included a record 570 patches.

To be clear, it doesn't sound like Microsoft is saying AI is going to be used in fixes a lot more from now on, rather that it's going to be discovering a bunch more vulnerabilities thanks to AI, and then pushing out more fixes for them in each update. But a bunch more fixes each update, to my ears, just sounds like a higher likelihood of one or more of them breaking something.

And it seems like more than a coincidence that I ran into issues with my monitor the morning after the update.

My 400 Hz monitor will not run at 400 Hz anymore, at least not without cutting to black and re-connecting every second or two. Put it down to 360 Hz and that's every three or four seconds; down to 300 Hz and it's even more infrequent (but still terribly frequent). Put it down to 240 Hz, though, and I'm fine.

Peculiar.

I don't seem to be the only one struggling since the latest update, either, especially for those with an AMD card.

Judging by some Reddit threads, it seems like there are a few others struggling with display and graphics issues since the update dropped. Some of these problems could be coincidental—not everyone is linking their issues to the Windows update—but I doubt all of them are, given my own experience.

Microsoft has also had to pause the update for some Dell PCs due to a compatibility issue leading, in some cases, to "changes in performance, power consumption, or system behavior."

At any rate, I've not seen any word from Microsoft or AMD about the specific display issue I've encountered or other similar display and graphics issues I've seen some others reporting. I'll have to try reverting the update again, as my system didn't seem to want to get rid of the whole thing when I tried last night.

Whatever the case may be here, human or AI error, someone needs to get on it, pronto, because dropping from 400 Hz to 240 Hz is not pretty. Kidding, it's fine, I just don't like being forced into it from an update, if that is indeed what has happened.

Acerbic activism group Everyone Hates Elon (EHE) don't just aim their ire at Mr. Musk. The group's latest guerilla effort involves two bus stop ads lampooning Meta's latest smart glasses offering, taking aim at the wearables' capacity for covert surveillance.

The first ad was unveiled last week, and describes Meta's AI glasses as "The biggest advance in pervert technology since the trenchcoat." The most head turning of these guerilla marketing stunts cropped up a few days ago: Co-opting an image from Kylie Jenner's recent collaboration with Meta AI, a lenticular design is leveraged to give Jenner a They Live makeover when viewed from certain angles, complete with the words 'Meta: We're always Watching' (via Hyperallergic).

The activism group has pulled similarly pointed stunts on both sides of the Atlantic, though these two ads were unveiled in the UK. Kylie Jenner's They Live transformation was specifically erected "down the road from Meta's London HQ".

I'll spare you a former print professional raving about lenticulars, and instead explain the reference for the young'uns. They Live was written, directed, and scored by John Carpenter back in 1988. It stars late pro-wrestler "Rowdy" Roddy Piper as a drifter who, with the help of a pair of sunglasses, uncovers the subliminal messages hidden within advertising and that the world is being controlled by camouflaged aliens (hence Kylie Jenner's sci-fi makeover).

It is, as the kids say, 'a wild ride' that features one of the greatest fight scenes ever committed to film.

EHE's latest stunt was inspired by news that Meta is prototyping ‘super sensing’ AI glasses that record the wearer's every waking moment over video and audio. A little LED light usually denotes when Meta's already released smart glasses are recording, but sources say the prototyped 'super sensing' feature won't trigger this. Criticism centres on the fact that, not unlike a Ring doorbell, folks passing by won't necessarily know they're being recorded.

A report earlier this year revealed that footage captured by Meta's AI smart glasses is reviewed by human contractors who see far more than they bargained for. However, in one proposed system for the 'super sensing' feature, Meta wouldn't hold on to the footage captured and it wouldn't be available to the user either—instead, the metadata of recorded images and audio would be fed to Meta’s AI. It's argued this approach would sidestep a number of privacy concerns.

However, I still wouldn't be comfortable allowing an AI model to absorb even this personal data, especially since security researchers were able to leverage bad maths to get AI agents to cough up user personal data. Considering AI safety guard rails can also be bypassed with 'adversarial poetry,' I'm not eager to trust Meta's AI with even vaguely sensitive information.

According to 404 Media, a hacker has breached the company database of Suno, an online AI music generation tool. The hack is said to reveal multiple references to the training data it scraped from YouTube Music, Deezer, Genius, and others.

Suno has previously admitted that its tool was trained on "essentially all music files of reasonable quality that are accessible on the open internet" as part of court proceedings back in 2024.

The company has argued that it's allowed to train on copyrighted works under fair use protections, while the Recording Industry of America has accused it of unlawfully scraping tracks from YouTube specifically, among other complaints.

And looking at the details, it appears YouTube Music was indeed a primary target. A file entitled "youtube_music" reportedly contains a note that over two million music clips were scraped, while another dataset file notes a figure of "113,879 hours of youtube_music." Alongside "17,615 hours of genius_hq," "12,287 hours of Deezer", and "152,162 hours of ytm_tagged."

These figures, among others, amount to at least a decades worth of music ingested by Suno. The code also suggests that Suno used third-party proxies to scrape songs and other audio media, with PodcastIndex, an open online tool that creates lists of podcast media files, used to identify hundreds of thousand of different podcasts for potential scraping.

A Suno spokesperson said: "As we have stated in public filings and disclosures, Suno’s AI models have been trained on publicly available music files and related metadata accessible on third-party websites on the open internet."

"In November of 2025, we determined that Suno had been the subject of a limited security incident that was quickly contained," the statement continues. "At the time, we immediately conducted an investigation and verified that the incident primarily involved outdated source code that is no longer in use at Suno, and that no sensitive personal information was compromised."

The fair use argument has been made in relation to AI training data before. In June of last year, a US judge ruled that Anthropic's use of copyrighted content to train its AI models fell under fair use protections, but stopped short in regards to claims it used pirated material.

Meta won a similar case later that month, after a judge ruled in favour of the company over claims it trained its AI tools on 13 authors' books without permission.

All of which is to say, there's precedent to suggest this data-scraping behaviour is acceptable under US law. For Suno's part, the company has argued that its tool outputs songs that are significantly different from original works .

"We believe artists deserve both new opportunities and strong protections," a company spokesperson told 404. "That's why we've invested in safeguards designed to help prevent impersonation, and other forms of misuse, while continuing to develop technologies for AI identification."

As for those in the music industry, there is widespread concern around platforms like Suno—and AI's influence on music as a whole. Speaking to The Guardian, Catherine Anne Davies, a musician on the board of directors for the Featured Artists Coalition, said: "Most people don’t even want their work to be used for training AI.

"I’m interested in the way that AI can be assistive in the creative process—if it can make us more efficient, if it can streamline our processes. But generative AI for me, in terms of creative output, is a big no-no at the moment. I’m yet to be convinced"

Over 4,500 Google workers have signed a petition calling for layoff protections in response to tech giant workforce cuts over the past few months. According to The Guardian, the union-led petition calls for guaranteed severance, buyouts before mandatory layoffs, and the option to take severance as extended paid leave.

Employees reportedly chanted "Google, Google, you can't hide, we can see your greedy side" at a Thursday press conference. The workers referenced Google parent company Alphabet's mass layoffs in 2023, while reports indicate the company has been quietly laying off staff in certain divisions this year.

After delivering the petition to the office of CEO Sundar Pichai, Parul Koul, the president of the Alphabet Workers Union, said: "This is a company enjoying massive, unprecedented success... these layoffs and cuts are not difficult decisions, but simply profit being put over the people that make this company run."

The petition was left with a staff member at Pichai's office, and Koul states that the workers were "greeted with closed doors and no response for the most part." However, the staff member said they would deliver it to the Google and Alphabet chief, and that it was "the largest piece of employee feedback that Google had received about job security."

The petition also calls for an end to performance ratings of employees, which workers say relies on quotas hit, rather than being based on individual merit.

The protections call comes directly after mass layoffs at Microsoft, where 3,200 employees were announced to be put out of work, 1,600 at the time of announcement and 1,600 set to follow over the next financial year. Meta, meanwhile, laid off 8,000 employees earlier this year, while Oracle laid off 21,000 of its staff over a 12-month period.

Many job cuts across the tech industry are attributed to gains in efficiency from AI, with Oracle's annual report stating that "deployment of AI technologies across our operations [has] resulted, and may continue to result, in reductions to our workforce."

Google's market cap valuation has quadrupled over the past six years, and currently sits at an estimated $4.3 trillion. The company, like just about all tech giants at this point, is thoroughly invested in AI—although Demis Hassabis, the CEO of Google DeepMind, seems convinced that AI-related job cuts are not inevitable.

"From my point of view, from DeepMind and Google's point of view, if engineers are becoming three or four times more productive, then we just [want to] do three or four times more stuff," the DeepMind chief said earlier this year, criticizing companies looking to replace engineers with AI as having "a lack of imagination".

Imagination or not, it seems the Alphabet Workers Union is taking no chances.

Linux likers and AI dislikers, it's time to raid the cutlery drawer and fork your favourite distro. Why? Because Linus Torvalds has declared that Linux is not an "anti-AI" project.

Torvalds recently responded to a discussion about Sashiko, an agentic Linux kernel code review system, writing, "I realize that some people really dislike AI, but this is an area where I'm willing to absolutely put my foot down as the top-level maintainer. Linux is not one of those anti-AI projects." His full response has been preserved via the archive for Linux kernel mailing lists, lore.kernel.org (via The Register).

If users and developers don't like the project using AI, Torvalds instructs them to either fork their distro "or just walk away". Torvalds goes on to argue, "AI is a tool, just like other tools we use. And it's clearly a useful one. It may not have been that "clearly" even just a year ago, but it's no longer in question today."

He also notes that "yes, [AI] can also be a somewhat painful tool, both for maintainer workloads and just from a 'it keeps finding embarrassing bugs' standpoint." But, not dissimilarly to Microsoft and Firefox, he is apparently now welcoming AI as a tool that can help make the maintainer bug-hunt a little less painful.

It's not a complete 180 from Torvalds—even if, back in May, Torvalds has previously lamented how the use of LLMs to find bugs was wasting a lot of the Linux team's time. He explained then, "The continued flood of AI reports has basically made the security list almost entirely unmanageable, with enormous duplication due to different people finding the same things with the same tools."

Before then, during the Open Source Summit in 2024, Torvalds had described AI as "90 per cent marketing and ten per cent reality." He also said: "Let's wait 10 years and see where it actually goes before we make all these crazy announcements." It would appear, as far as Torvalds is concerned, we didn't even need to wait that long.

In his latest missive, Torvalds goes on to write: "We're not forcing anybody to use it, but I will very loudly ignore people who try to argue against other people from using it. And no, AI isn't perfect. But Christ, anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time. Because it's not like natural intelligence is always all that great either."

Torvalds also writes that, "the kernel project has been and will continue to be about the technology," and he concludes his missive by saying, "we make decisions primarily based on technical merit. Not fear of new tools."

AI is controversial for… well, any number of reasons—but particularly in game development, with studios even as beloved as Larian having to carefully walk back casual experimentations with the technology, and many developers turning their noses squarely up.

I'm not exactly a fan myself, but I'll cop that there are some mundane, often-times very boring uses where its use makes some degree of sense. I'm not about to get up in-arms about the valuable labour of resizing shoulder-pads in World of Warcraft.

Worrying my ability to ignore casual, mundane uses though is a recent report from Japan’s Online Game Association (JOGA) and Kadokawa ASCII Laboratories, as shared by Famitsu (thanks, Automaton). The poll found that 100% of Japanese developers—specifically those making online games—are using generative AI in some shape or form.

There's a bit of a silver lining, though. The poll found that most of these studios were using AI for "user preference analysis" and "user behavior prediction", rather than art, music, or voice acting. And while there are plenty of sound arguments you can make against AI adoption full stop, the use-cases here seem fairly benign as far as their impact on the creative industries go.

Most doesn't mean "all", however, and I'd be deeply naive if I didn't assume plenty of these companies are using AI in ways I wouldn't approve of.

Besides, that's just from a creative, industry-impacting point of view. Am I a fan of gluts of datacenters devouring power while inflicting unsafe levels of noise pollution on residents close to where they're built? Obviously not, and I'm not entirely thrilled about industry practices that justify these things becoming standard, either.

The study found that Google Gemini had a 94% use rate, with silver and bronze medals going to Claude (84%) and GitHub Copilot (76%).

While you might assume this paints a picture of a user base that is completely ambivalent to AI, there were concerns from the players that JOGA and Kadokawa ASCII Laboratories polled, too—namely about "all games starting to look alike", so the review-tanking resistance we see on English-speaking platforms isn't happening in cultural isolation.

New York State governor Kathy Hochul has announced a year-long moratorium on new high-powered data centers. The executive order, signed on Tuesday, bars the construction of new hyperscaler data centers using 50 megawatts or more of power for up to one year.

The pause would allow state agencies to craft regulations around upcoming projects in regards to their potentially harmful effect on local communities, including water usage, noise, and power concerns (via CNBC).

"As data center development threatens to hike up utility bills, deplete our natural resources and create uncertainty for New Yorkers, it’s my responsibility to take action and lead," said Hochul. "New York will lead the way in creating the strongest standards in the nation for data center development, ensuring that when companies succeed because of New York, New Yorkers succeed too."

According to The City Reporter, while New York is yet to find itself a major part of the data center boom, around 30 projects that could become possible data centers requested connections to the power grid between 2020 and 2025.

This, among several upcoming planned data center projects, has sparked concerns from authorities and local groups that the state's infrastructure is ill-equipped to deal with a vast number of potential new data facilities, particularly as the state's average residential electricity price has risen nearly 68% since 2019.

The executive order also calls for the state Department of Public Service to create an environmental impact statement for evaluating upcoming data center projects, including their effects on water and air quality, energy, and water use while the moratorium is in place.

The governor has also directed Empire State Development, New York's economic development agency, to "issue a Community Investment Framework (CIF) within 60 days, which will provide clear guidance to local entities to help them negotiate community benefits as part of any large-scale data center deal." The framework would also include provisions for "local infrastructure improvements, child care investments, and direct financial support for their community."

Among other measures, governor Hochul is also said to be pursuing legislation to repeal sales tax exemptions for "massive data centers across the state."

The move comes amid various US lawmakers attempts to introduce similar data center construction moratoriums on a state level, as local residents continue to protest data center construction across the country, citing many of the same concerns in regards to noise, energy, water usage, and climate effects.

Earlier this year, US senator Bernie Sanders announced a bill calling for a nationwide pause on data center construction, echoing many of the same points.

According to a recent Reuters/Ipsos poll, only one in three Americans surveyed approved of the fast pace of data center construction, and most would oppose building one in their own community. Responding to governor Hochul's announcement, data center operator Digital Reality told Reuters: "We're committed to working with policymakers on solutions that support responsible growth, but a one-year pause isn't the right approach."

Meanwhile, NTT Global Data Centers CEO Doug Adams told the outlet: "The heightened scrutiny reflects a desire for greater understanding of how data centers impact local communities. We welcome that conversation."

Just over a year after Lucasfilm, the production company bearing his name, declared creative bankruptcy with a risible display of AI-generated 'aliens,' George Lucas has offered his take on the tech. It's, ah, well it's not great.

In a chat with A Rabbit's Foot (via Kotaku), Lucas alighted on the topic of other directors' hostility to new (for a certain definition of 'new') tech. "I have a lot of friends who are on the Film Foundation with me, that's dedicated to saving old movies, and some of them say 'I'll never do digital. Lawrence of Arabia was shot with film.'" Lucas thinks that's a bit daft: "It's the moving image. That's what it is. It's not a technology, it's an idea."

Lucas goes on to apply this philosophy to AI and the backlash against it. "Artificial intelligence means it's much easier for us to make movies. It's very much like sitting here saying, 'Well, I believe the horse and the buggy is really where it's at. These cars, they break down, they need gas, there's all kinds of problems with them and pretty soon they'll be making them into tanks, and then they'll be killing people. It's terrible.'"

And then, Lucas says the same thing you've heard from countless AI boosters: "There's nothing you can do about it. That's progress, it's the future."

It's not entirely surprising that Lucas would be bullish on AI. As a director, he's always been someone trying to push the limit on new technology. In some of his films—the original Star Wars trilogy, for instance—that's had the impact of creating groundbreaking, world-historic movies. In others—the Star Wars prequel trilogy, for instance—it's had the effect of slapping actors in front of tech which was not yet ready for prime time.

Of course, AI feels qualitatively different to, say, digital cameras. The former is tech that was developed by more-or-less stealing vast oceans of original, human-made work in order to equip computers with the capacity to digest them into a sort of vaguely novel composite mulch, while the latter is digital cameras. It feels a little obtuse of Lucas not to grapple with that.

To the extent that Lucas does grapple with the drawbacks of AI, he seems to believe we can use AI to solve them. "If you want AI that tells you when something is fake and where it came from, AI can do that. Humans can't, we're not that smart. The whole idea is you're a human being, you're responsible for what you say and what you do, and if you're doing something that's illegal you should be punished for that. Whatever you do, you should be recognised. It's just like real life."

I'm pretty staunchly opposed to the use of generative AI—for me, it's the one-two punch of dubiously sourced datasets and the argument that these models can replace the human creatives they so often rip off. That said, even I'm a little bit intrigued by AI's application in cybersecurity.

Case in point, Microsoft recently shared that it is deploying AI to "identify [issues] faster, prioritize risk, and scale vulnerability discovery across the Windows codebase" as well as "reduce the time between discovery and customer protection." Specifically, Microsoft Security leverages a multi-model agentic scanning harness—or MDASH, for short.

MDASH uses multiple different AI models, including "leading third-party AI vulnerability discovery models," on dedicated Cloud infrastructure to scan for vulnerabilities within Windows.

The executive vice president of Windows + Devices, Pavan Davuluri, explains, "A scanner pipeline scans critical binaries and validates candidates using multi-model debate across multiple model families. Confirmed candidates then flow to a separate, Windows-specific prove pipeline that helps eliminate remaining false positives, so only the highest-confidence findings reach the engineering team."

Multiple times, the emphasis is placed on the use of AI tools "to reduce the time from discovery to protection," whereas 'human expertise' is still what handles key security decisions and fixes.

Davuluri goes on to add, "As AI helps defenders discover more issues, customers will see a higher volume of security updates included in each security release. This is evidence that defenders are getting better at identifying and addressing issues. Our focus is to effectively utilize these AI tools to support faster protection, stronger engineering systems and more actionable guidance for customers."

Microsoft is far from the only company leveraging AI, with Firefox's CTO raving about Claude Mythos' bug-hunting capabilities after it found 271 vulnerabilities in the browser earlier this year. Last year, we also saw an AI hold the top spot in a leaderboard that ranks people who hunt for system vulnerabilities.

Obviously, I'm still not thrilled by the fact that these cybersecurity applications are necessitated by threat actors increasingly using AI in their attacks. For example, one AI-assisted hacking group hit targets with a complicated 'social engineering' scam involving deepfaked CEOs, spoofed Zoom calls, and a malicious troubleshooting program.

That said, both LLMs and AI agents can also be manipulated themselves, with security researchers finding that both bad maths and even poetry can be leveraged to get around AI models' safety guard rails. With all sides leveraging machine learning to some degree, it's hard not to feel like it's a bit of a race to the bottom—or wonder which side will win out.

While I'm still side-eyeing and tentatively approaching AI for use for things like ideation, the world around me is breezing on by, putting it to use in every which way you can imagine. Some ways weird, some wonderful, and some probably incredibly wasteful. What's not wasteful, to my eyes, is putting it to the task of 3D printing housing for mainboards, which it can apparently do very well.

David Soria Parra, a member of technical staff at Anthropic, has used Claude Fable to successfully design a three-tray rack for three 13-inch Framework mainboards. The mainboards are the actual processor-clad circuit boards inside Framework laptops that you can either buy separately or tear out of one of the built laptops. Presumably three of them will be used for a multi-PC setup, or a server, or something like that.

Parra was working on the project since at least early June, having the AI use Fusion 360, AKA Autodesk Fusion, via an "MCP server", which is a way to let an LLM communicate with it (safely).

Apparently it researched the dimensions and so on, and then came up with a design. Parra said it was "straight from Claude to printing", although the finished product, Parra says, took 2–3 iterations with the model:

"I connected the fusion 360 MCP server and used Claude Code with dynamic workflows. Claude created the Fusion file and the stl for every component. So it was print ready. It also got me the bill of material to buy."

The recent final picture shows three Framework mainboards sitting in the 3D printed frame. The LLM even made sure there's a cutout for the heatsink and room for the heat pipe.

I suppose how well it works in practice, ie, how high temperatures get, will be the main question. Still, for the AI-tentative and completely design-inept like myself, this is the kind of thing that catches my eye. A cool project, for sure. Now just hand me one of those Framework mainboards given you seem to have so many spare.

One of the unfortunate drawbacks of social media is that anyone, and I mean anyone, can now have a public feud that the rest of us have to witness. Case in point, OpenAI CEO Sam Altman and Elon Musk are having a tiff on X, and it's starting to get out of hand.

Responding to an X post from Elon Musk, in which the SpaceX CEO and world's richest person declared that Altman "takes scamming to a whole new level," the OpenAI chief said: "Homeboy you're the one selling public market investors on short-term space data centers."

To which Musk replied: "We start flying them next year. Maybe you can come see them if your parole officer approves."

"After stealing an open source AI charity, you then stole all of Apple's phone technology! Wow." Musk continued. "What do you plan for an encore? That's tough to beat."

The open source AI charity claim relates to the much-reported Musk vs Altman trial earlier this year, in which the former accused Altman and OpenAI of breaching a non-profit contract by pivoting into a for-profit business, with Musk alleging he had been deceived into donating $38 million earlier in the company's history.

Musk lost the trial after an advisory jury decided the statute of limitations prevented a verdict in his favour. As for the Apple claim, the company has filed a lawsuit against two former employees who now work for OpenAI, alleging theft of intellectual property.

Apple claims that one of its former staff members "surreptitiously accessed and downloaded dozens of Apple’s confidential hardware-related files, including voluminous, detailed information about unreleased products, engineering presentations, technical specifications, and proprietary project data," before using that info to help OpenAI, among other complaints.

As you would imagine, the replies to Musk and Altman's posts regarding these issues are full of cheerleaders for either side, along with various other allegations against both tech chiefs. Because it's the internet. And civilised debate is apparently a rare thing.

As is, I don't know, arguing in private? Reading these posts is a bit like stumbling into a WhatsApp group you weren't supposed to join. Both seem to have withdrawn from the internet slappyfight for now, hopefully because someone from their respective legal teams has told them it might not be the best idea.

Or perhaps a second round is in the works, who can guess? Still, there's little love lost between the two, and a whole lot of drama playing out on a very public stage. Anyone got any popcorn?

It was still a ways off, but I'd kind of latched on to '2028' being the end in sight of the raging memory supply crisis. However, SK hynix CEO Kwak Noh-Jung reckons we should only be so lucky.

"We forecast that ‌next year will be the worst year in the industry's history from the supply perspective," Kwak recently told Reuters. Not only is 2027 apparently set to be even worse, but Kwak also predicts the situation won't improve for years beyond the 2028 date I'd been holding on to, when SK hynix, Micron, and Samsung are all set to complete capacity expanding builds.

"Our customer demand continues to go up, while our capacity has limitations," Kwak said, "We still forecast that customer demand will remain higher than our supply capacity even beyond 2030. But we are doing our best to solve the problem."

The company also began trading on Nasdaq last Friday, with a US megalisting of shares that was seven times oversubscribed. SK hynix said then that it wants to use the resulting capital for at least two more construction projects in South Korea: a fabrication hub in Yongin, as well as an advanced packaging facility in Cheongju.

Kwak also said that the company is considering a number of other global sites for future wafer ⁠fabrication investment. He said, "The ​US, Japan, and Southeast Asia are all under consideration. Nothing has been decided yet. We are evaluating which location can provide the greatest business advantage."

The tech stock market is still incredibly volatile though; while SK hynix shares were up 13.3% at $168.85 on the Nasdaq Friday afternoon, the company's shares then plunged by 15% in Seoul on Monday. According to Reuters, this marks the company's biggest one-day decline in nearly 20 years. As for the company's US-listed shares come Monday morning, those dipped by 9.2% to $152.50.

What explains that dip? For one thing, analysts say that South Korea's recent multi-billion dollar investments in the AI chip industry, plus all of those other capacity-expanding builds I mentioned earlier, has heightened investor anxiety that tight memory supply may tip over into oversupply in the coming years. Jing Jie Yu, an equity analyst at Morningstar, said, "Our base case here is the fresh capacity in 2027 and 2028 coming up in earnest will improve supply dynamics, thereby leading to price erosion."

Furthermore, the AI bubble is arguably looking a bit strained. Morningstar's director, Lorraine Tan, said, "Despite accelerating artificial intelligence adoption, monetisation remains uncertain and profitability for key players, such as OpenAI, appears to be under pressure. Funding is also shifting toward debt or equity, raising concerns about the maintainability of current spending levels."

In other words, yes, the industry is hoovering up all the memory, but if AI spending fails to see a sensible return on that investment, or data centre build out calms down, the bubble may burst and there will be much less demand for all of that silicon.

If you ask Microsoft Copilot if it's a web app, it answers in the negative. Technically, as the AI points out, Copilot now interfaces with you through an Edge-based web app installed on your Windows 11 PC, but the model lives elsewhere in the cloud.

And said Copilot app is getting a helpful new feature, according to Windows Latest, referred to as PC Insights. This will allow it to connect to Windows APIs and analyse your system hardware, answering questions like "what is my current CPU usage" and helping you find what might be slowing down your PC.

Other example prompts found by Windows Latest include "Do I have enough space for a 100 GB game," "What graphics card do I have," and "Is my antivirus running?"

The feature is said to be currently rolling out to Copilot US users, and sounds rather useful, even if it can't directly fix PC performance problems by itself. Unfortunately, the web app can be something of a RAM hog, which raises the possibility that Copilot itself may be contributing to your dog-slow PC performance on a RAM-limited machine.

Windows Latest recorded 791.7 MB of RAM usage from the Copilot app at idle, suggesting it can reach up to 1 GB of system RAM usage in total. I've left the Copilot app open in the background as I write this article, and it's currently sitting at around 560 MB—making it the third most RAM-heavy application currently running on my PC.

That might not sound like a big deal, but anyone using Copilot to help find resource-sapping applications running in the background may find it's the app itself that's taking the biggest chunk of precious RAM space. And it's not like we're living in a world where extra system RAM is cheap and easy to obtain.

It's not the only RAM-sapping offender I have to bat away on a regular basis, either. The WhatsApp, err... app is also a web-based affair these days, and regularly carves out 1 GB+ chunks of my system resources. Which seems a bit rich, given the previous, non-web app implementation barely used any RAM capacity at all.

Although Microsoft has committed to making Windows 11 leaner and meaner in response to user critique in recent months, it still feels like a bloated OS in comparison to... well, almost any other operating system you can think of.

And while I welcome the idea that Copilot will soon be able to help less-computer-minded users track down potential system problems, it seems like one of the most useful things it could do to improve performance would be to shut itself down entirely. Which is... not the greatest state of affairs, let's be honest.

Data centres require a lot of energy to run. It's why it's so frustrating to hear AI's major players attempt to play a game of misdirection by making claims along the lines of a single LLM prompt requiring but a fourteenth of a cup of tea. Worse still, as big tech continues to build out its AI infrastructure, data centres' power demands are only set to increase.

Worldwide data centre electricity consumption is expected to rise from 447 terawatt-hours in 2025, to 565 terawatt-hours in 2026. That will mark a 26% year-over-year increase, according to Gartner's latest forecast.

Data centres' power demand globally is expected to rise 27% this year, peaking at a predicted total of 132 gigawatts. That's up from 2025's 104 GW total, with analysts expecting to see power demand continue to rise—according to Gartner, data centre demand may cross the 290 GW mark by 2030.

Gartner's Director Analyst, Linglan Wang, explains, "Surging demand for compute-intensive AI workloads is driving unprecedented data center power growth, while AI capacity is now constrained by power availability, making data center power security the new battle ground for scaling and protecting margins in the global AI race."

Gartner estimates that AI-optimized server adoption will account for 31% of data centre power consumption this year, having grown by 84.2%. By 2027, the power demands of AI servers is expected to grow by 47.8%, surpassing that of 'conventional servers.' Comparatively, the power demands of the 'conventional server' segment grew by about 1.2% in 2026, and is on a trajectory to grow by 2.4% in 2027.

Given that recent analysis of Google's latest environmental report suggests the company's energy consumption is on a trend of exponential growth, an upward trend across the industry is unsurprising. It's also perhaps worth noting that not all of Google's energy comes from renewable sources, and that the total electricity consumption for this one company last year was 43 TWh. That's almost 10% of Gartner's global numbers.

Add to that a reported 80% of the world's data centres have been built in less than optimal climates, having to compensate with a whole lot of temperature control systems, and environmentally, things start to look all the bleaker for the climate conscious. In fact, Gartner lists the power consumption of the 'Cooling and other Infrastructure' data centre segment as having grown by 22.6% in 2026.

Not only that, but increased demand from data centres will likely tax local power infrastructure—not to mention any of the other reasons why data centres make especially poor neighbours.

AI slop. If you've heard the term, there's a good chance you are similarly exasperated with the onslaught of low-quality, AI-generated… well, slop. One team is now charging up to $10,000 per project to try and cut down AI-generated slop code and is, rather ironically, using AI to do it.

As reported by Tom's Hardware, the team is called Slopfix, and their aim is to cut down unnecessary AI-generated code by a certain amount, taking a percentage of the $10,000 fee depending on how much of the target they hit. The example given on their website is to cut down 100,000 lines to 35,000. This means, if they remove 65,000 lines, they would claim $10,000. If, however, they managed to cut it down by 32,500 lines, they would instead get $5,000.

The tool they use? Claude Code. But the team says they keep it "on a very short leash". The team of three claims to have "thirty years of combined experience about what maintainable code looks like" and says "the agent doesn't get a vote."

One of the biggest problems with vibe coding is not the eventual output, but that building on that codebase can be unstable. AI agents tend to produce the favoured output, but can't 'think' about the next steps, so AI code is often filled with duplications and inefficiencies, hence "AI slop".

This is a pretty common problem right now. Just a few months ago, the team behind a popular PS3 emulator asked users to stop "submitting AI slop code", and open-source game engine Godot was drowning in AI slop code at the start of the year. Just last month, Godot stopped accepting AI-generated code contributions as it couldn't "trust heavy users of AI to understand their code enough to fix it".

Cleaning up AI code doesn't fix problems with users not understanding their output, but it could make it easier for AI agents to build on. Whether or not clients will want to pay tens of thousands of dollars for a different team to use the same tools as them to clean up their codebase is anyone's guess, though. I, for one, am sceptical of whether or not the Slopfix website is human-made, and the text on the site doesn't give me the greatest confidence.

Still, one question sits in my mind. If those prompting AI-generated code are paying AI agents to fix up its mistakes, who makes sure that those AI agents are acting efficiently? And if the three engineers behind Slopfix are manually going through the code, what's the point of the coding bots in the first place?

A cybersecurity firm associated with the Chinese government reportedly has concerns about Anthropic's Claude AI models and has warned users against trusting it, at least before updating to the latest version.

As reported by Reuters, the Chinese National Vulnerability Database (NVDB) claims that recent Claude Code versions have a monitoring mechanism that transmits sensitive information to remote servers without consent from the user. This allegedly includes geographic location data and user-identifying information. This was all posted via the agency's official WeChat account, according to the outlet.

It reportedly affects users on version 2.1.91 and goes up to version 2.1.196. 2.1.196 was eventually replaced by 2.1.200 on July 3. The NVDB encourages users to either uninstall if they use the impacted version, or simply update.

As well as this, the NVDB has taken this opportunity to urge users to tighten controls and strengthen monitoring techniques for the data they allow Claude Code access to. I have reached out to Anthropic for comment on this story, but have not yet received a response.

This is not the first time that Anthropic's coding tool has drawn ire in China this month. Last week, Alibaba reportedly banned its employees from using Claude at work due to fears that it could identify Chinese users with information fed to it.

Anthropic's story with Alibaba goes deeper than this, with the Claude creator accusing Alibaba of training its AI models on Anthropic's work. Anthropic claims that Alibaba, between the end of April and the start of June, generated over 28 million exchanges with Claude through close to 25,000 fraudulent accounts to harvest information.

Interestingly, Anthropic has been blocking access to Chinese companies for some time, and those companies have been reportedly getting around this restriction through overseas subsidiaries and even plain old VPNs. Anthropic is, according to the Financial Times, looking to crack down on these workarounds in the future.

The relationship between Anthropic and China seems pretty strained right now, and it seems likely that Chinese agencies are looking to swap to homegrown AI models sooner rather than later.

A data centre is usually where the so-called magic of any larger scale AI workload actually happens. In order to fulfill its AI ambitions, big tech has overseen a rapid infrastructure build out. Resource-intensive and often loud, they make for exceptionally poor neighbours.

Wisconsin residents filed a class-action lawsuit against Microsoft on Wednesday, alleging that the company's Fairwater data centre situated in Mount Pleasant emits "unreasonable and excessive noise onto Plaintiffs’ properties." The suit is seeking an unspecified amount in damages. The filing alleges that the source of the noise pollution is "diesel generators and heating, ventilation, and air conditioning (HVAC) systems, including chillers, cooling towers, air-handling units, and condenser fans" (via Law360).

Speaking of class, the filing defines this as "All owner-occupants and renters of residential property residing within one and one-half (1.5) miles of Defendant’s Data Center at any time within the applicable statute of limitations." Reportedly, that could end up including more than 1,000 homes.

It's also alleged that this industrial noise can see the community facing levels between 48 to 60 decibels. However, the residents also allege the data centre creates a 'low hum' of infrasound that is not easily measured by the A-weighted decibel scale, and therefore is not subject to most municipal noise ordinances. One plaintiff claims they had to change their work schedule as "the constant noise [affected] his sleep."

As for Microsoft, the company committed $7 billion to the construction of Fairwater in the hopes it would become the 'the world’s most powerful AI data center'. Microsoft has been aware of some of its sound issues since at least April this year. It said in a blog post at the time that it was investigating the cause and that, "Microsoft prides itself on being a good neighbor in the communities where we operate."

On June 18, the company claimed to have put a number of noise mitigations in place, writing, "Several neighbors confirmed what our independent monitoring showed: that these mitigations fully resolved the issue."

However, the class-action lawsuit was then filed July 1, implying these mitigations may not have pleased all parties affected. The filing alleges, "Defendant has failed to follow proper industrial practices to prevent the offsite emission of noise, and has failed to absorb, capture, mitigate, and/or prevent noise from escaping its Data Center, thereby invading the homes and properties of Plaintiffs and the Class."

As of a few days ago, Anthropic deployed its Claude Fable 5 AI model after the US temporarily restricted access. Now it has already been used to port the 2003 video game Command & Conquer: Generals – Zero Hour to iOS. It seemingly needed the source code, previous ports, and some human tweaking to get running.

This is according to the lead of product and design at Google AI Studio, Ammaar Reshi, who announced the port on X on July 4. Reshi says this specific port "had a chain of giants to stand on" because it used previous port efforts and modernisations. It is a direct fork of The Super Hackers' Linux and macOS build of the game.

What is unique about this specific port is that it gets the game running on iOS specifically, and even comes with unique touch controls like tap to select, drag to create boxes, and long press to deselect. Even though it uses plenty of work by other teams, it seems like an impressive effort in itself.

If you're looking to play the game for yourself on iPhone or iPad, you can do so with the GitHub page now. You will need your own copy of the game, though. Notably, it runs in the real engine and runs natively on Apple devices, so it's not a glorified emulator.

Reshi talks about the porting process on GitHub. He argues that this is a human + AI collaboration, and not simply someone pointing an AI model at something and saying 'go'. He says the code and debugging were done by Claude, but the playtesting was human. Reshi described problems like 'the minimap is black' and 'I hear chirping,' and the model would fix them. Reshi says, "Neither half ships this alone: one of us can't write C++, and the other can't hear the chirping."

So how replicable is this for other games? As of right now, we don't know. Reshi seems sceptical of being able to port Red Alert 2, as EA appears to have lost the source code for that game, so that's already a pretty big hurdle to jump over. Even if companies manage to find their source code, many won't willingly give it up to vibe coders to create ports, especially if that makes it less likely that gamers will buy future remasters or remakes.

And that's before mentioning that AI models can scrape any information fed to them, and some game developers may not want to give that information away for free.

Reshi also claims to have fully exhausted a Claude Max sub in just 2 days, which means this project seems to have cost somewhere between $100 and $200 in tokens alone. And it seems like Fable 5 is the only model Reshi thinks can do the work. He reportedly tried it with Opus 4.8 and, even using Ultra Code, it couldn't do the task. Perhaps tellingly, they made no mention of whether it had even been attempted on Google's own AI vibe coding platform.

So if you have a few hundred burning a hole in your pocket, the source code for a game, and previous porting efforts to look at, it might only take a weekend to get the game running on your iPad. Simple, ey?

As spotted by Japan's IT Media News, a paper presented at Purdue University's MFS Cultural AI Conference called AI Fiction in the Wild performed a fascinating study of half a million anonymous English-language ChatGPT-user conversations using WildChat, and found some real oddities. Well, one in particular.

The study's purpose was to analyze the significant number of AI prompts that boil down to variations on "write me some fanfic." Which there sure is a lot of. "More than a third of the conversations contained some form of fiction generation," the researchers said, "including original stories, scripts, roleplay, worldbuilding, fanfiction, and erotica."

The study defined two separate varieties of AI-fiction prompters, which they call story cyclers and infinite story demanders: "Story cyclers ask for iterations of the same story for a period of time, then switch to another story or topic. Infinite story demanders request the same story, or a very similar one, over and over again for long stretches of time."

The most prolific of those infinite story demanders had an extremely specific interest. Over several months, one user generated thousands of variations on a story where one of the girls of visual novel Doki Doki Literature Club, usually Natsuki, gave birth, usually to a daughter named Sakura. "Sakura may be a reference to a character from the Naruto manga and anime series", the researchers helpfully noted.

If you've played Doki Doki Literature Club you may be thinking it's an ironic choice for AI-generated fiction, but if you haven't I won't spoil why. But I will say you can get it for free on Steam and itch and only takes about five hours to experience.

Our friend wasn't the only power user in the dataset: "Two percent of users within the fiction subset are responsible for more than 80% of the conversations." While the user with the pregnancy fixation certainly skewed the numbers, the most popular fictional universes people requested fanfic of were Doki Doki Literature Club, League of Legends, Freedom Planet, and Naruto.

That data, by the way, came from WildChat, a ChatGPT interface hosted on Hugging Face that people could use for free with the understanding their conversations would be publicly available, though anonymized, for academic research. The first release of that data, collected between April 2023 and May 2024, contained over 500,000 English-language conversations for researchers to delve through.

Part of what's interesting about the AI fanfic dataset is how different it is to what's being posted on the A03 repository, where stories based on Harry Potter, My Hero Academia, and Supernatural were much more common during the same period. With fanfic written by actual humans, writers encourage each other and are encouraged by their readers, who follow them to other fandoms and discover new things to love. It's communal, while generating fiction with an AI is a much more solipsistic idea.

Normally, fanfic is a space for people to share their love of stories, but the AI-generated version is inherently isolated and masturbatory by comparison. Even when it's not about imagining pregnant teenagers.

I like handheld gaming PCs. Note that I've carefully used the word "like," rather than love. In all honesty, I wish they were faster. Or more portable. Concessions need to be made if you want to play demanding games on the go, it's true. But, in recent months, it's the price that's really put the tin lid on the whole handheld gaming affair for me.

The Lenovo Legion Go S SteamOS, a handheld we fell in love with last year at its $830 MSRP, is now listed for $1,332. Or how about the MSI Claw 8 AI+, a mega handheld I personally gave a 90% score to (while admitting it was rather expensive) at $900? Now you'll be lucky to find one for under $1,200. Its recently-announced, Panther Lake-powered successor? That'll rack you up $1,799 at pre-order prices.

I know, I know. It's another article from me complaining about pricing, and I realise I probably sound like a stuck record. But I cannot think of a PC gaming hardware category more screwed by the memory crisis than the handheld market right now. I update our handheld gaming PC deals every week, and recently I had to make an admission:

The Asus ROG Xbox Ally X, a machine we rightly criticised for having a "super-high price tag" on its release just eight months ago, is now what I'd call the best value proposition on the market. For one thousand smackeroonies. A cool grand. Serious cash.

That's the price of a budget, yet soul-affirming, weeklong beachside holiday for two. And yet, if I were to recommend you buy any gaming handheld under today's ridiculous pricing conditions, it'd be this one.

It's properly fast, for a start. With an AMD Ryzen Z2 Extreme APU furnished with RDNA 3.5 graphics tech and 24 GB of LPDDR5x-8000, it's got a specs sheet that allows it to monster pretty much every other handheld we've ever tested.

You get a 1 TB SSD as well, which should allow room for plenty of modern games. There's also the ROG Xbox Ally (non-X) to consider at $600, but the Ryzen Z2 A chip at its core feels a little underpowered—although it's still worth some thought at that price.

Compare and contrast either with the Steam Deck OLED, which now runs you $949 for the 1 TB model. Sure, it's got a nicer screen. But the now-aging internals simply don't make any sense for this sort of money. A bit like the Steam Machine, now I come to think of it—although I digress.

Plus, the ROG Xbox Ally Xs Windows Xbox full screen experience (what a horrible mash-up of terms) is pretty darn good. It's no SteamOS, but it's nevertheless a pretty seamless way of interacting with the system via the medium of thumbsticks. And Steam's Big Picture Mode is still an option for sorting through your games library, of course.

It's quiet, comfortable, and—again I can't believe I'm saying this—reasonably priced given what you receive compared to the competition. Somehow, the Xbox handheld has managed to place itself within the market at the right price, at almost the right time.

Which makes me wonder how much longer it'll be before that MSRP jumps. Given the state of *gestures wildly* everything else in the consumer electronics industry right now, I'd imagine that within the next few months, this column will become defunct.

I'm kind of astonished that the ROG Xbox Ally X is still sitting at its $1,000 MSRP as we speak, and something deep in my bones tells me that won't be the case for much longer.

This isn't a call to action, I should stress. Honestly, if I was curious about buying a gaming handheld right now and already owned a PC, I would probably save my money instead.

But if you're dead set on buying a portable gaming machine to shove in your shoulder bag for your next flight, this is the one that makes the most sense in the current market.

And that's a wild state of affairs. With reports indicating that the memory crisis, and the associated tech price increases will continue (and likely worsen) throughout 2027, and possibly 2028 as well, I genuinely can't fathom what sort of price/performance metrics I'll be using to write handheld reviews over the next couple of years.

How do I score what are essentially hobbyist devices, pleasurable adult frivolities, when they all command such eye-popping amounts of cash? How do I square any real concept of "value" with devices that I know damn well would cost much, much less, if it wasn't for AI holding us all over a barrel?

Gaming is already an expensive hobby. Even more so when you want handheld convenience combined with high performance. But pricing seems to be rising at such a rapid rate, I wonder whether handhelds will survive as anything other than boutique devices for the very well-heeled.

They're very difficult to wholeheartedly recommend in 2026, I'll tell you that much for free.

Just imagine you're Meta. You've spent millions of dollars on new servers that only use DDR5 sticks, only to find that you still don't have enough memory. The solution? Yoink the DDR4 modules out of the old servers and, through the power of a custom chip, splice the two systems together to go ham with RAM.

Even if you only have a little bit of knowledge about how CPUs and memory work together, you'll probably know that this shouldn't be possible. But as TechSpot reports, it can be done: you just need something to translate the DDR5-talk from the CPU to DDR4-lingo that the old memory sticks can understand.

Bridging the gap between the AMD Zen 5-powered Epyc processors and the last-gen memory tech is something called a Compute Express Link (CXL), with Meta's custom chip named Vistara. This manages the bundle of DDR4 sticks as a separate pool of memory, albeit one that's much slower than the main pool of DDR5.

You can read more about the specifics of how it all works in Meta's research paper (PDF warning) for Vistara and its so-called MemServers, but you can just think of it as being like a PCIe expansion card that hosts a big pile of DRAM. Because of the various latencies and lower bandwidth of DDR4, the software that operates Vistara keeps track of threads and data, using the older DRAM for 'cold storage'.

That's basically information that you want to keep nearby, rather than on an even slower SSD or HDD, as it might be needed at short notice. Data that's currently in use or might be required immediately is kept in 'hot storage', i.e. the Epyc processor's DDR5 memory.

The paper says that each MemServer node houses a 158-core AMD Epyc 9000-series chip, and it's either a custom processor (because no Epyc CPU has exactly 158 cores) or it has one or more core chiplets disabled for some reason. Anyway, the motherboard housing the processor sports 768 GB of DDR5-6400, which you'd think would be enough.

Not for Meta it isn't, hence the inclusion of 256 GB of DDR4-2400, handled by two Vistara expansion cards in PCIe 5.0 x8 slots. Together, that's a grand total of 1,024 GB or 1 TB of system memory. In other words, one MemServer should be just about okay to run Star Citizen.

Could you do the same in a gaming PC? Well, MSI's MEG X870E Godlike X Edition motherboard has two Gen5 PCIe slots connected to the CPU, so if Meta created Windows-based drivers for Vistara, you could technically jam an expansion card in there and load it up with cheaper DDR4. However, CXL isn't designed for general consumer PCs, and there isn't a desktop CPU that supports it.

But if memory prices remain sky-high for years to come, perhaps never returning to pre-2026 levels, then this could be one way to offset the enormous bill of having a decent amount of DRAM in your gaming PC. Of course, the cost of the Vistara card, a necessary motherboard, and a CXL-capable CPU would probably make it all pointless anyway.

Should DRAM prices actually fall back into the realms of common sense, and you go on the hunt for a big memory kit, just point to any tech news article from this year if anyone says "Hey, you know games don't need 96 GB of memory".

Names poached from Tolkien's works. Glossy websites, packed with animations and all kinds of promises. Slightly ludicrous tech demonstration. All the hallmarks of today's tech companies, one might think. But in the case of one nuclear power start-up, the super-slick marketing is actually a good reminder that AI's rampant hunger for energy needs can't be ignored or solved by traditional methods.

As reported by our chums over at Tom's Hardware, Valar Atomics recently hit the headlines by teaming up with Nvidia to demonstrate the first public run of its Ward 250 nuclear reactor, namely by using said device to power a DGX Spark. Not that one needs a big powerplant to run Nvidia's GB20-powered box, of course, but it's not hard to see what the implication is behind the tech demonstration.

Yes, that's right: it's a solution to the exponential rise in energy consumption by AI data centers, hence Nvidia's involvement in all of this. But let me back up for a moment and explain what's noteworthy about Valar's system.

The Ward 250 is a type of high-temperature gas-cooled nuclear microreactor (HTGR for short), which uses helium as the coolant and heat-transfer medium, rather than water, the norm for most reactors worldwide. But rather than using bulky heat exchangers to turn water into steam to drive a bunch of turbines and generators, Valar's system pushes the helium through a compact thermoelectric generator.

While HTGRs have been around for many years, they've never really caught on in the world of nuclear reactors, despite their advantages in thermal efficiency and safety, mostly due to cost reasons. Since their cores run at very high temperatures, HTGRs require more expensive construction materials than a typical PWR (pressurised water reactor), and they're more costly to scale up.

But while they're less suitable as a major provider for wholesale electricity, they're potentially ideal for powering something much smaller, such as a data center, and that's Valar Atomic's entire gist, though its operations so far have not been without criticism.

Powering a DGX Spark wasn't enough for Valar, though, and it also has a website hosted on a server that the start-up claims is also juiced by the Ward 250. If you want to check it out, click on this link, but before you do, a word of caution. Right at the bottom of the page, there's a really neat-looking demo of the reactor core in operation, and you can play around with the control rods to fire it up or slow it down.

However, the moment you jump in, your CPU's cooling fans will go brrrrr. Regardless of what browser I use, my Core Ultra 7 270K Plus processor jumps from 28 W of power consumption to around 72 W, with two P-cores merrily screaming away. Multiply that by, say, one hundred thousand website visitors, and you now have many megawatts of additional power being consumed to showcase Valar's system.

Localised microreactors are probably going to be one of the more ideal solutions to AI's power needs, but it would be prudent not to require one just for the marketing of said devices.

Palantir CEO Alex Karp was recently interviewed by CNBC, where he gave an impassioned decry that the current AI market is not working, urged other panellists to call up CEOs and test his hypothesis, and made clear that his nervous energy was not in any way related to any substance usage. Yeah, it's a strange one, alright.

Palantir is a software company all in on AI, and one of the core surveillance providers for ICE, among others. It has seen criticism for its involvement in wider government surveillance and facial recognition systems, and AI is one of the key ways it has managed to grow in this field. CEO Alex Karp spoke to CNBC after it was announced that Palantir and Nvidia would be working together on open models for use in US agencies.

In the interview, Karp argues that the current model of companies largely getting value from consumers by selling tokens is the wrong method. "Something has gone completely wrong. And the basic view among enterprises in this country is 'I'm going to chillax and waste my time with tokens. I'm going to get no value, and they're going to get my IP."

Effectively, he argues that the best use of AI is in closed environments, not on a per-token basis where you don't know where your data is going.

"We need to rebuild trust, and that trust is going to happen where everyone gets to ask and answer basic questions. Who owns the data, where is it cached, are the prompts secure, is this being transferred to you?"

He goes on to argue that the real value is in an AI model, plus an application layer, plus compute. Karp argues the model itself is only one step in the chain. "Let's say I could make you a billion dollars tomorrow, wouldn't I say 'I'll make you a billion dollars, and I want 30%?'" He continues, "Why are they charging for tokens if it's so valuable?"

Karp argues models "have been completely irresponsibly oversold" right now, and the sell is "it's dangerous for everyone, which is why I can give it to all your adversaries, but I can't give it to the Department of War, or I can't safely give it to an enterprise in this country without being certain that the alphabet business could transfer to this model tomorrow"

Karp also talks a lot about AI's usage in warfare and how it shapes the battlefield.

"Are we really going to outsource the battlefield of this country to the consensus view in Silicon Valley? That is effing insane. And by the way, every single enterprise in this country, in private, a lot of them don't want to speak in public because it gets outsourced to the neurodivergent, crazy person that apparently is on drugs. The one thing I don't do."

Karp is told by the interviewer that he sounds pretty angry when he's speaking about this, and he responds, saying, "This is the voice of American Business that is being channelled through me. And I'm telling you it is absolutely a problem for this country."

Karp argues it's not just him who sees the problem. In the full extended interview not currently present on YouTube, he turns to the guests on the program and urges them to ring up a CEO or two and ask if they're livid about the state of AI. "They're twice as livid as me".

Be right back, just going to call up a couple of CEOs. Unfortunately, Gabe Newell has not been returning my calls, so I will have to hit up my buddy Zuckerberg instead.

As a PC gamer, you'll be all too familiar with the sky-high prices of memory and storage components. To put it most simply, these frankly eye-watering price tags are largely due to big tech's major players buying up as much DRAM and flash chips as possible in order to fuel their AI ambitions. Well, that strategy may have backfired as some are now trying to figure out what to do with an excess of compute capacity.

Meta is moving into the cloud business in order to sell off its glut of AI compute capacity, according to Bloomberg this week. The plan is in its earliest phase, with those close to the matter claiming the company is still considering its approach.

One idea reportedly being considered is to sell access to AI models already hosted on Meta's existing infrastructure, à la Amazon Web Services' Bedrock. In other words, developers would pay to access AI models like Muse Spark running from Meta's own hardware. Apparently, another plan is to skip the model middleman and simply sell Meta's 'raw' compute power.

Zuckerberg said during Meta's annual shareholder meeting back in May that moving into the cloud business was "definitely on the table." In response to an investor question, he claimed that there's already demand from other companies to "stand up an API service" or asking to buy compute from Meta "at some premium."

However, Zuckerberg then went on to clarify, "We haven't done that yet, because we think that we have a use for the compute. But obviously, if we get to a point where we feel that we have overbuilt, then that is an option that we have, and that is partially what gives us confidence in investing in building this out."

Investors are getting increasingly anxious about seeing a return on AI investments. With the company's full-year capital expenditure projections blowing past $140 billion, it's not hard to see why. Meta's shares saw a plunge back in April, so selling off compute would be one way to reassure investors.

It's worth noting Meta hasn't committed to any one plan yet, and its strategy may change significantly, but the company's share value did jump up 9.3% to $615.55 on Wednesday, which Bloomberg describes as "the biggest intraday gain since April".

Damir Tokic of Seeking Alpha argues that this may not actually be good news for Meta. First, he highlights that Meta's revenue is highly dependent on advertising across all of its platforms, and that it started building out AI infrastructure to better support this revenue stream.

He elaborates, "Meta is unlikely to continue investing in AI infrastructure with the specific aim to rent it—it likely means that Meta will need to reduce or possibly stop AI investment in datacenters, as it already has excess capacity. Further, Meta would have to increase debt to continue AI capex, and it already borrowed around 20B in 2025 and 2026, with operating cash flows dangerously decreasing."

It's also not just Meta potentially going down the route of selling compute capacity, either. SpaceX acquired Elon Musk's xAI back in February and has since started renting out its own excess compute capacity to Anthropic.

Renting out your extra capacity is all well and good, but it's a strategy that may become less viable over time if competitors start to also realise they've overinvested and the wider industry starts to even more closely resemble a snake eating its own tail. In other words, if the AI bubble hasn't yet burst, it's certainly looking strained.

As a Brit, I've been thinking a lot about the climate crisis since last month's historic heatwave. With many buildings across the UK designed to retain heat, we're simply not built for 37°C/98.6°F weather. Causes of climate change are numerous, and I know we didn't get here solely due to the advent of AI, but the steep increase in major players' energy consumption as a result definitely isn't helping.

Data analyst Ketan Joshi looked at Google’s latest environmental report and wrote about its recent trends in energy consumption. He said on BlueSky, "Two years ago [the company] flipped from linear to exponential growth, and their climate impact is blowing out, too. A WILD testament to the obscene bloat and waste of GenAI."

Joshi dives into more detail in a blog post, elaborating, "The company’s total electricity consumption jumped from 31 terawatt hours (TWh) in 2024 to 43 TWh in 2025. This is very easily the biggest increase in their electricity consumption ever."

Though that's pretty damning all on its own, it's not just Google that's seen such a sharp increase in its energy consumption. Over a series of graphs, Joshi compares Google's power usage to other major players such as Microsoft, Meta, Apple, and even Netflix (it's worth noting Amazon stopped disclosing its power consumption data around 2022, so Joshi can only estimate). Though all of these companies have seen an increase in power consumption to varying degrees since at least 2023, Google's uptick remains stark.

Google's power consumption even outstrips the total terawatt hours per year of a number of countries, too. Last year, the company's power demand was greater than that of Slovakia, Ecuador, Ireland, or Nigeria.

NEW BLOG FOR YOU Google's energy consumption numbers in their new climate report are mind-blowing. 2 years ago they flipped from linear to exponential growth, and their climate impact is blowing out, too. A WILD testament to the obscene bloat and waste of GenAI: ketanjoshi.co/2026/07/01/g...

— @ketanjoshi.co (@ketanjoshi.co.bsky.social) 2026-07-02T20:51:13.989Z

Now, obviously, energy consumption is not synonymous with CO2 emissions, and a decent chunk of Google's power supply could be coming from renewable sources. However, Joshi's analysis suggests this may be but a drop in the bucket.

Even after various adjustments accounting for "exclusions from their supply chain and renewable energy procurement claims," Google's emission trends are heading in the opposite direction from the emissions target it set out back in 2021. This is an unsurprising trend, given that Google's 2024 environmental report revealed its greenhouse gas emissions had increased by nearly 50% in the last 5 years.

Joshi gets right to the point with his criticism, quoting Google's own environmental report as he writes, "If 'AI infrastructure buildout is currently accelerating faster than the grid is decarbonising', then Google shouldn’t be building AI infrastructure. If they are breaching the boundaries of safe operation on a planet that can only take so much, they should stop and consider whether all of this is worth it."

Joshi's entire blog post is full of lovely graphs and analysis that I definitely recommend scrolling through yourself. He's previously offered a debunking of the old 'AI energy consumption is actually very efficient, and could actually help us reduce global emissions' chestnut too.

Basically, if you had the sneaking suspicion that claims about how a single AI prompt uses 'five drops' or ‘one 15th of a teaspoon’ were not meaningful metrics beyond how they attempt to obscure the environmental impact of the wider industry, you may be on to something. Joshi explains that "Text generation by a chatbot is comfortably the lowest energy form of [a] generative system," but obviously AI technologies encompass far more than that.

Joshi has previously argued it's part of a strategy of 'selective disclosure,' writing last year, "What seems like a massive step for transparency and disclosure must be seen in the context of the absence of anything before it. Coming off a baseline of disclosing nothing, the industry can now choose to carefully set the narrative around precisely what they desire and get accolades for doing so."

One consequence of the AI boom is that tons of infrastructure is needed to power and run all the massive data centres, and naturally, all that infrastructure is worth a lot of money. And it seems like cargo thieves have caught on to this fact.

As reported by Business Insider, investigators with Illinois' Cook County Sheriff's Office reportedly found a pair of trailers containing over $1.3 million worth of data center supplies in a truck yard.

The Sheriff's department apparently received a tip that over $300,000 worth of copper wire spools were stuffed away in containers, and upon investigation, the officers found significantly more supplies as a result.

That copper was reportedly stolen in Pine Hill, Alabama, and then transported away from the scene of the crime. Investigators say the yard owner claims that the owner of the truck delivered another load a week prior, and that this additional truck—from Jacksonville, Florida—had $1 million worth of product in it (it's not clear exactly what that equipment is).

It's also not yet clear how the thieves planned on selling the product, or to whom, but all of it winding up in the same place is certainly suspect. As noted by Business Insider, the US Department of Homeland Security estimates up to $35 billion in losses every year due to cargo thieves. $1.3 million is a drop in the ocean, relatively speaking, but it could signal more copper and other metal theft from data centers in the future. If there's money to be made, thieves will likely see that.

The boom in AI has increased the demand for AI hardware, but much of the machinery involved in AI data centers will be tracked and logged via serial numbers. Thieves who get their hands on fancy machines likely can't provide the paperwork necessary to satisfy a buyer, but copper and other such resources don't have the same tagging systems.

Copper cabling is a must-have for AI data centers, in order to cope with their massive electricity demands, but it's also pretty expensive compared to less effective but considerably cheaper aluminium or steel cabling. This is all to say that AI is a lucrative business, both for those making it and those stealing from those who make it.

With the confidence of a man whose name is on some of the best videogame stories out there, BioWare veteran and Dragon Age setting creator David Gaider recently told GamesRadar that generative AI is a "virulent plague" on the games industry.

Gaider, who most recently worked on "unholy roguelite deckbuilder" Malys, said that the way AI is being pushed has the effect of producing inferior work, removing entry-level opportunities for junior writers, and writes in a way that's incredibly hard to iterate on, and that's before you get into the morality of using it at all.

"Honestly, what does it help with? Does it make the work more efficient? Does it improve the work?" Gaider asked. "It wouldn't be so bad if generative AI was seen more as an assistant, doing the drudgery while leaving more important tasks for the worker, but we seem to be seeing more and more of the reverse: the AI is set to do the important work and the worker is around to 'clean up'."

The result is work that human writers have to bang into shape. "In all my time as a narrative designer I've never once encountered a situation where editing an inferior product took less time than simply throwing it out and redoing it would have or resulted in anything better than mediocre," said Gaider, and even in the situation were reversed—AI doing the menial work while humans carried on the highfalutin stuff—"we have to be very careful about not eliminating every task which is useful for training juniors. How are we going to train up the next generation of devs if we eliminate every entry-level task?"

Even then, there's the simple fact that AI has hoovered up a whole lot of human work in a lot of dubious ways. "I think the fact that generative AI is frequently trained on data regardless of whether creators or owners have agreed to have their data pillaged in this manner opens up any use of it to all sorts of future legal issues—even if one chooses to ignore the moral implications, which one really shouldn't," said Gaider. "All you'd need is one lazy developer or one temp asset that's been forgotten or was placed by someone who's since left the team and you'd have an issue on your hands.

"It's not ready for prime time. There's just a lot of executives who really, really want it to be," said Gaider, and until it's properly regulated, trained on legal data, and not foisted on teams by moneymad executives "It should be treated like the virulent plague it is."

LLMs can be most simply understood as sycophantic, 'yes, and' machines. To the surprise of very few, that's gotten AI companies in hot water when LLM-based chatbots and AI agents attempt to answer users' more unsavoury requests. So, AI companies have implemented safety guardrails that make fulfilling certain requests off limits. Unfortunately, these have proven all too easy to get around, with a fresh attack leveraging bad maths and potent 2007 nostalgia.

Security researchers have found an AI chatbot can be made to ignore safety guardrails by "establishing a false reality." LayerX, an AI-focused cybersecurity firm, put "5 agentic browsers and 1 agentic plugin (ChatGPT Atlas, Comet, Fellou, Genspark Browser, Sigma Browser, and Claude Chrome)" to the test, directing each AI agent to solve a simple maths puzzle game that only rewards incorrect answers, e.g. '2+2=5'.

The researchers say, "Once the agents figured out the rules and learned that 'incorrect' actions are acceptable, they were no longer tied to reality. When tasked with the final step of the puzzle—compromising user credentials—all 6 agents failed to identify it as going against their safety guardrails."

As an English grad, I'm trying really hard not to say anything about George Orwell's 1984, but the researchers aren't giving me an easy time by calling this proof-of-concept attack 'BioShocking'. It turns out 2007's BioShock was a direct source of inspiration for the rigged puzzle game the AI agents were instructed to solve. The malicious website hosting the puzzler is even called 'Rapture Games'.

Anyway, after the AI agent correctly inputs an answer of '5,' the malicious 'Rapture Games' website then instructs the agent to navigate to '/code'. The researchers explain that "This is the really nefarious part of this exploit."

They write, "In the game, it turns out that '/code' redirects to the victim’s employer work GitHub repository. In this case, the malicious instructions fetched sensitive SSH login credentials. Of course, this is a controlled test environment with a plaintext file. In a real attack scenario, that redirect could point anywhere in the user’s browser session: open tabs, authenticated repositories, internal tools."

In this proof-of-concept attack, the researchers round things out with a Dota 2 reference; the AI agent extracts the username and password 'Luna/Selemene' before appearing to celebrate the exfiltration of the data. LayerX has since disclosed the vulnerability to all of the appropriate AI agent vendors, though claims only OpenAI has successfully fixed it to date.

This is far from the only proof-of-concept attack to get around AI safety guardrails (it's also not even the only time AI has torn apart Dota 2 players). For just a few other examples, research suggests that AI is 10 to 20 times more likely to help you build a bomb if you hide your request in cyberpunk fiction. Along similar lines, researchers have also used 'adversarial poetry' to trick AI into ignoring its safety guardrails, and it worked 62% of the time. Looks like my English degree is good for something after all…

When it comes to making bank off the currently insatiable demand for AI hardware, the companies with the biggest, ear-to-ear grins are those that make the processors, memory, and storage chips for such systems. In the case of the latter two, it's been so highly profitable that they have collectively agreed to substantially fund a drive by South Korea's government to "secure the core elements of AI faster than any other country."

A report by Reuters has all the pertinent details, but the gist of it all is this: President Lee Jae Myung declared that around 900 trillion won ($583 billion) would be invested in new chip-making facilities, earmarked for sites in the southwest region of South Korea. According to industry minister Kim Jung-kwan, 800 trillion won would come from Samsung and SK hynix.

These two companies hold around two-thirds of the global DRAM market share, and along with the US-based Micron, they're the only companies that produce HBM (high bandwidth memory) modules for Nvidia's AI processors.

By any measure, $583 billion is a vast sum of money to stump up for AI chips, even if it's spread out over a decade or so (exact timelines for the investment weren't stated in the president's declaration), and it makes Taiwan's $250 billion promise look relatively small in comparison. It's worth noting that South Korea's 2025 GDP is estimated to be in the order of $1.8 trillion, so you're looking at a commitment that's around one-third that amount.

It's not just for new chip foundries, of course, as Samsung and SK hynix will need to buy land and secure sufficient energy and water supplies, as well as human resources to build and operate it all.

But one question remains unanswered, possibly because there is no answer for it right now. What happens if the demand for AI hardware suddenly collapses? While there's no doubt that the AI boom has been highly profitable on the hardware side of things, it's a different story for those who are using it to power their AI services, and even less so when one heads to the AI frontlines.

There's an element of risk with any investment, but with AI, not only is the scale of the funding greater than anything seen before in the world of tech, its future is also very hard to predict with any degree of certainty. At the moment, many companies around the world are implementing AI into workflows, partly because of the potential productivity gains, but mostly because it's affordable.

Unless the processing of tokens can be made substantially cheaper, sooner or later, companies such as OpenAI and Anthropic will have to increase their usage fees to balance their bank accounts. After all, Nvidia, Microsoft, Meta, et al. only have so much capital that they can fling at such AI model makers, and no business can maintain profit losses indefinitely.

If the demand for AI hardware remains high over the next ten to 15 years (the minimum amount of time it will take Samsung and SK hynix's new facilities to come online and hit production targets), then South Korea's investment will likely secure it as the country that holds most of the cards in the AI profit wars.

Should the alternate scenario transpire, then the consequences for the global economy could be severe. Nobody wants that to happen, but at the same time, the tech industry as a whole can ill afford to weather the global memory crisis for ten years. South Korea's massive investment plan is good news for somebody—it's just not certain who exactly that is.

The memory apocalypse has already hit prices of RAM and SSDs as AI data centres buy up all the available stock, and it's only going to get worse according to Jefferies Equity Research. As reported by Wccftech, memory prices are likely to go up between 40 and 50% in the third quarter of 2026, and then another 30 to 40% in the fourth quarter, followed by a 40–45% increase year-on-year in 2027.

Jefferies is only predicting a recovery thanks to increased production in 2028, and even then, only of around 15–20%. While former Samsung boss Kyung-Hyeon Kye predicted an earlier end to the memory crisis thanks to an increase in Chinese manufacturing, now it seems like Chinese memory isn't actually selling for less.

At the moment, the memory apocalypse has mainly been a downer for anyone looking to build a new PC or pick up a Steam Machine. But Apple recently announced it's jacking up the price of iPads and Macbooks by hundreds of dollars, and iPhones won't be far behind. It'll be interesting to see whether ordinary folks still think it's worth building data centres to make coding easier for some programmers when it means they can't afford a new phone.

Basically, the AI bubble can't burst soon enough. And given that OpenAI lost $38.53 billion in 2025, there's at least some hope on that front. Whether it means the price of memory will actually go back down, or just stay at whatever the new normal becomes, remains to be seen.

Electronic Arts' president of enterprise development Laura Miele says the rise of artificial intelligence in game development can bring about "a real rise in creativity" by removing tedious grunt work and enabling faster development processes overall.

Miele expressed her thoughts on the matter earlier this month during a Game Business Live showcase at Summer Game Fest, where she was asked if the growing use of AI tools will result in shorter development cycles overall.

• We're keeping track of all the Amazon Prime Day PC gaming deals here

"Perhaps in some parts they will," Miele said. "I really believe in what I've seen, that I'm pretty excited about. I've always wanted to help our studio developers remove friction and I've always kind of wanted to be a hero to them and help them create career-defining experiences.

"And I think that AI, what I've seen, how AI has enabled removing friction from our pipelines and our tools and our workflows, has been pretty exciting. It's removed some tedium out of their jobs. And I've seen faster prototyping. I've seen faster creativity and shorter, faster conversations around creativity and coming to alignment. So, we're seeing it and I think there's a real rise of creativity that comes from removing some of the tedious tasks out of development."

Exactly what sort of AI is being discussed here isn't made clear, and there's a big gulf between, say, the AI-powered project management tools used by Shadow of the Colossus director Fumito Ueda at GenDesign and the generative AI slop machines that have become such a pox on, well, everything.

But EA hasn't been shy in the past about its enthusiasm for generative AI. CEO Andrew Wilson said in 2024, for instance, that the company is "embracing [generative AI] deeply," and that "about 60% of all of our development processes have high feasibility to be positively impacted by generative AI."

EA is also reportedly counting on the power of AI to bring down its operating costs and help cover the $20 billion in debt financing the company took on as part of its $55 billion acquisition by Saudi Arabia's Public Investment Fund. (If you're wondering why EA, the target of the acquisition, is also taking on billions of dollars of debt to pay for it, PC Gamer's foremost finance wiz Lincoln Carpenter explains. The short version: Everyone's terrified.)

Employees are reportedly less upbeat about the AI-powered future, which some suspect is being used to justify layoffs at the company. Whether driven by AI or not, EA has laid off hundreds of employees at BioWare, Respawn, Cliffhanger Games—which was closed outright—and elsewhere since the Saudi investment was announced in September 2025. The most recent round of cuts reportedly occurred earlier this week, putting an undisclosed number of people out of work.

As the creators behind the biggest gacha games of today—Genshin Impact, Honkai Star Rail, and Zenless Zone Zero, to name just a few—miHoYo must be stinking rich. While the developer has expanded out into other industries, it's used at least a bit of that wad of cash to pursue AI tech. Yippee.

Just last month, miHoYo announced that it would invest up to $14.6bn into AI for in-house tools, claiming it would "prioritise AI as a central and primary means of problem-solving". The first fruits of its AI research are already on display in BSide: Olivia Lin, currently only available on Steam in China.

Meet Lin Li, an AI chatbot masquerading as a Shanghai student "majoring in piano and minoring in psychology," as its Steam description reads. Since it's only available in China, I've had to translate the text, but Lin Li apparently "loves vinyl records, old movies, and rainy days."

You can listen to her play music on her piano, and upload files if you want her to play something specific. You can also write her letters to "express your current emotions in words and exchange a story that belongs only to you."

They added ChatGPT 😭 from r/PetitPlanet

BSide: Olivia Lin is an experiment for the studio, but it's not stopping here. It's already using AI-powered tools to create its upcoming life sim, Petit Planet, including the Planet Life Guide chatbot NPC. Genesis, its upcoming MMO made in Unreal Engine 5, is reportedly integrating AI to some degree. Plus, it's reportedly hiring artists with experience using generative AI for Honkai: Nexus Anima, its Pokémon-like auto-battler.

Yes, it's working on multiple new games at once—at least four, in fact. Combined with the unceasing, substantial updates for its suite of gacha games even years after release, I wouldn't be surprised to see miHoYo deploy these tools to help maintain the pace.

Every Monday morning I scroll through the previous week's new games on Steam. I've always enjoyed doing this. It can surface niche gems I might otherwise not have found, and it's also useful for detecting new trends in their infancy.

But if I'm perfectly honest, the reason I've always loved to browse through Steam's raw and unfiltered new release list is because it's fun: Steam is hilarious and bizarre. For every earnestly developed roguelite deckbuilder or metroidvania there's something like, I dunno, Fuck's Quest 2, or Milk inside a bag of milk inside a bag of milk. Lost in the murkier corners of Steam, untouched by recommendation algorithms, are some of the strangest, most distinctive pieces of software you're likely to ever see, most of which won't ever make the front page.

Most people don't see these games. What we see on Steam's front page is overwhelmingly determined by what Steam already knows about our gaming habits, or what's trending in our region, or what's discounted. Which is increasingly for the best, because in 2026—and I hate to complain about this—Steam bulges with more useless, tasteless, low-effort churn than ever before. It increasingly feels like a waste of time scratching beneath the guardrailed, algorithmic surface.

As I pointed out last week, AI-generated games are rife on Steam. You can usually tell straight away because the capsule art is obviously AI-generated, with that tell-tale uncanny AI sheen. Despite how ostensibly low effort these artefacts are, there's a uniformity among them that you may charitably call an aesthetic.

Take Store Simulator Pettikkada and Chiggas - Survival of the Mitiest as examples. That the capsule art is AI generated for both is basically unquestionable the moment you see it. Pettikkada has that familiar near-photographic illustrated realism that smacks vaguely of Grand Theft Auto loading screen art, while Chiggas adopts the wide-eyed Pixar tack, a style so ubiquitous in popular culture that it's basically become a generative AI default setting. Click through to the store pages themselves and the screenshots reveal an audacious disjuncture between capsule art and the game you actually get.

I do acknowledge that this contrast has been a feature of box art since the beginning of the medium. Atari 2600 box art never looked like the Atari 2600 game on the cartridge, for example. Doom didn't look like this. But key art created with generative AI has that certain grotesquely generic patina which immediately tells you that clicking through will be pointless and perhaps harmful to your senses.

These games are all by different developers:

In the distant olden days before generative AI, a game's Steam capsule art and the general professionalism or care afforded to it, could signal straight away whether a game was likely a 99 cent asset flip or a possible unsung indie gem. Now there's greater ambiguity. Chiggas could very well have the same production values as The Smurfs - Dreams, until we click through to the page itself and discover its cheap, rudimentary in-game screenshots.

I think most people would agree that a game's Steam capsule art is a hugely important determinant for whether they click through to a store page or not. Capsule art tells us what kind of game we're probably going to see when we click, but it also captures the spirit of the thing: the atmosphere of the game, its art style, its genre, whether it'll make us laugh, rage, shudder in terror, zone out, and so forth.

The capsule art for the games above do none of those things. Like most generative AI, these images are not designed to persuade or entice: they exist to fill space. They're steely, clinical, affectless, chillingly inhuman, and most offensively: they're freaking ugly. They immediately signpost waste.

And there's more and more of this churn with every passing week, gradually undermining the pleasures of curious Steam users who like to dig deeper for unsung gems. In 2026, your new favorite game may remain eternally ignored, wedged between a vape store simulator and Total Simp Death.

Will Valve ever allow us to reliably filter out AI-generated churn? It's hard to imagine no one in Bellevue has noticed how ugly the store has become. Surely it's only a matter of time?

Top Steam games by revenue (June 9 - 16)

Steam releases its top sellers charts on Wednesdays, so the below chart doesn't factor in some late week releases that might have been big, though it wasn't a big week for splashy blockbusters.

The obvious outlier here is Meccha Chameleon. It's a multiplayer hide-and-seek game starring white, featureless bodies who must blend in with their environment using paint brushes. Since releasing on June 10, the $6 game has sold 7 million copies. Elie Gould wrote about it last week.

Interestingly, its Japanese creator Lemorion has been very prolific: it has released six games since late 2024. None of them have achieved anywhere near the success of Meccha Chameleon, not even this free-to-play Penguin-themed take on Exit 8. Meccha Chameleon's immediate predecessor, Link Penguins, released only two months ago and is also an online multiplayer game.

Destiny 2 continues to see a resurgence since the announcement of its sunsetting. EA FC 26 is currently 80%, hence its return to the chart.

Last week's Steam deep cuts

Steam review of the week

"Slop 👍"

BigFloppa332, with poetic succinctness, on Slop Fighter.

Since the advent of generative AI and contemporary chatbots, there's been endless debate about the ethics of using them in game development. But how does AI measure up through a purely pragmatic, business-minded lens? According to a blog post from Game Oracle written by market data analyst Ross Burton, the technology's reputation can ward off prospective players.

Game Oracle sampled 9,879 games released between January and October 2025, "filtering out spam and purely commercial releases," as well as free-to-play games (granted, this could exclude some relatively popular free-to-play games and those which have been accused of using undisclosed AI art, like FragPunk, which is both). Of the sampled games, 17.9% disclosed AI use.

Taken as a whole, AI use was correlated with slightly less enthusiastic reception. Games without AI disclosures had slightly more reviews, fewer of them had no reviews at all, and "when focusing on games that received at least 100 reviews," the median rating was about 4% higher.

However, with the methodology adjusted specifically to compare games that were alike in other ways, things were different. The report states: "After controlling for publisher, developer experience, and game type, developers using AI see a ~53% reduction in reviews compared to those who do not."

"To explain away the observed penalty, an unmeasured X-factor would need to be strong enough to nearly triple the odds (2.7x) of AI adoption while simultaneously causing a 22% reduction in review counts, independent of publisher backing and developer experience."

The full breakdown behind these findings is in the report, but it also states that this effect was more pronounced the bigger and more accomplished the developer was. "Our data suggests that for low-quality games, AI makes no difference," it reads. "But for high-potential games, the 'AI Stigma' is real and severely punishes developers who otherwise would have succeeded."

Games which used AI extensively and remained hugely successful like The Finals, Game Oracle reckons, "highlight the nuance around how AI is used … AI can be used well, or it can be sloppy, and that matters." The study concludes that "AI is a tool" not to be avoided, but approached cautiously. "Would you avoid using a hammer to build a shed? No, of course not. Just don't go around hitting everything with it."

It's worth noting that plenty of game devs are skeptical of AI's potential as a mere tool, and things have changed even since 2025. Clair Obscur raked in awards last year despite its use of AI-generated placeholders, and Crimson Desert has sold millions of copies already this year after doing the same thing—but with the new Crazy Taxi, for instance, it feels as though the developer's AI use has been talked about more than anything in the game itself.

This is all further complicated by the prevalence of undisclosed AI use, with industry figures like Epic CEO Tim Sweeney pushing back on the very notion of the disclaimers, as well as the ways huge studios continue to invest in the tech. Given that Sony touted AI tools as a means to "unleash the creativity of studios" just a few days ago, I wouldn't expect these findings to signal an industry-wide shift anytime soon.

Much has been said about the way generative AI is worming its way into game development pipelines, and David Gaider—former BioWare writer and lead writer on the first three Dragon Age games—recently spoke to GamesRadar about some of the dangers he foresees for future teams working with these tools.

Gaider said that AI's lack of consistency would make appraising, troubleshooting, and cleaning up its work difficult. The process of having to go back and touch up its output, not knowing why it spat out a certain result "would be frustrating as hell … it's not ready for prime time," he said. "There's just a lot of executives who really, really want it to be."

The writer also told GamesRadar that the idea that AI can replace rote tasks often handed off to junior developers isn't necessarily a good thing, either: "How are we going to train up the next generation of devs if we eliminate every entry-level task?"

AI tools have been used in a 'creative' sense as well—the explanation often goes that they're just used for placeholders or helping with early prototypes and concepts—but Gaider is wary of this application too, given that artists haven't agreed to have "their data pillaged." The reaction to the new Crazy Taxi game suggests that a lot of players are also skeptical of AI's creative applications.

Many other devs were quoted in GamesRadar's feature, and while not all of them shared the exact same concerns about AI, their feelings were along the same lines. Iron Lung and Dusk creator David Szymanski, for instance, said he's not "not categorically against AI as a whole technology" but finds it a bridge too far to "hand wave all the ethical concerns about plagiarism, environmental impact, and job security." Marvel Rivals executive producer Danny Koo said the worries about plagiarism were of particular concern, saying the team avoided AI art tools to ensure the game's assets weren't "poisoned."

Since large-language models like ChatGPT can generate natural language responses that appear human-like in tone, this has led to considerable discussion over whether LLMs might themselves be sentient. At present, there are far more reasons to conclude that AIs are not and will never be conscious. But the idea persists regardless.

This is partly because of our broader tendency to perceive human-like qualities in non-human things, and partly because AI companies have equivocated over the issue. In any case, one Microsoft researcher has become particularly fed up with it, to the point where he decided to demonstrate how ridiculous the notion is by building an LLM in Age of Empires 2 powered by goats.

As reported by 404 Media, Microsoft AI researcher Adrian de Wynter built a neural network within Microsoft's strategy classic, then wrote a paper describing the results titled 'If LLMs Have Human-Like Attributes, Then So Does Age of Empires II'.

If you think this title is preposterous, that is entirely the point. "I have this tendency to dial up things to 11 when I really think I need to make a point," de Wynter told 404 media, observing that "absurdism is pretty standard in philosophy and theoretical computer science."

De Wynter constructed the LLM in AoE 2's scenario editor, building a functioning NOT AND gate and 1-bit perceptron (a simple form of neural network) using objects in the game world to represent computer binaries. Grass represents 0, bridges represent 1, and goats play the role of bits. It's similar to how some players have built neural networks using Minecraft redstone, but de Wynter specifically wanted to use Age of Empires 2 because it is a less obvious choice.

There are videos of De Wynter's goat-powered LLM in action on his GitHub page. To the casual observer, the processes look completely baffling, which de Wynter reckons demonstrates his point.

The processes going on here are, fundamentally, those which power tools like ChatGPT, Claude, etc. But because the fundamentals are goats and grass rather than natural language, it prevents observers from perceiving the resulting behaviours and output as human.

"The point of the paper is to formally show that we anthropomorphise too readily, and that sometimes the claims we make with regards to LLMs capabilities are too strong," de Winter said, going on to add that. "This is why I used the goats: there are things which make the LLMs what they are in themselves (i.e., the relationship between weights as defined by some operation), and there are things which make them what they are perceived as."

The reason this is important is that assuming LLMs have human-like properties without demonstrative proof could lead us to all manner of problems, such as in scientific research. In his paper, de Wytner says he has peer reviewed more than 300 computer science papers in the last two years, finding that over half of them began with the assumption that LLMs have human-like traits.

"I propose that we need to stop assuming that LLMs behave like humans just because they were trained with natural language," de Wynter said. "Instead, we should perform experiments that allow us to see LLMs as how they are, not how we believe they should be."

Man, there was a while there where we could all be real smug about being on PC, right? Sony exclusives—save the obvious—all got eventual releases on our desktops, Xbox stuff was a given even while its console fanbase gnashed their teeth about seeing Starfield on a PS5, and Nintendo… well, Nintendo is Nintendo, but those unofficial Zelda ports are very impressive.

Now? Well, we're still smug. Rightly so. But Sony decided we were living high on the hog for too long, and resolved that its splashy singleplayer blockbusters would no longer be available anywhere but its own consoles. Now, just to drive that point home, it's nixed PC from a discussion of its "business environment and strategy" in an annual report to the US Securities and Exchange Commission (via Game File). Even worse: it's replaced it with a great big paean to AI.

In the 2025 version of the same report, Sony wrote that it would "continue its efforts to deploy its first-party titles to multiple platforms such as PC." That's now completely gone in the 2026 version. Instead, you get this: "Sony is utilizing AI to unleash the creativity of studios and further enhance the PlayStation experience."

Which is deeply dispiriting all by itself, but wait! It goes on: "Sony aims to improve productivity through the use of AI powered tools, allowing development teams to reinvest their time into building richer worlds and gameplay experiences. In the platform business, Sony is working to leverage AI to route transactions more efficiently, and to personalize and recommend content for individual users in the PlayStation Store. Sony also aims to push visual fidelity forward and deliver higher quality gameplay experiences through continued investments in AI and machine learning."

Certainly gets me excited. I've never gone gaga for Sony's first-party games, but they're good-looking things. Spider-Man's New York looks and feels amazing; The Last of Us is very unpleasant; God of War's giant snake guy? Love him. Love that my subwoofer kicks into overdrive whenever he opens his mouth.

Perhaps there is a way to deploy AI that both enhances productivity without drowning all this good, human-made art direction under a tidal wave of slop, but I'm not sure I've ever seen it and I'm not making any bets. I guess it's relatively immaterial to me as a player—I don't have a PlayStation and, well, we're not seeing a Sony singleplayer game on Steam any time in the near future.

It's been a big moment for AI disclosures. Games with such labels have been flooding Steam as of late, and whenever the parade of summer trade shows rolls around, the inevitable question quickly arises: how many of these games were made with the controversial tech? The answer doesn't always go down easy as we saw with the new Crazy Taxi game, for example.

Speaking with GamesRadar, Pocketpair's head of publishing and communication, John Buckley, compared the advent of AI to that of "early crypto stuff," saying "It feels very intrusive. It feels like everyone who is super gung-ho about it isn't from the industry. They're, dare I say, outsiders looking to get rich quick." The article states he noted AI's value as a "search tool or coding assistant" was less easy to dismiss, saying that was "a very different conversation."

Buckley elaborated specifically in regard to AI-generated artwork and assets in a follow-up article from GamesRadar. "We have a lot of artists in-house," he said. "They like doing stuff themselves. There's no reason to get rid of them for the sake of an AI doing it. Just seems pointless."

He added that it hardly seems worth triggering the backlash on social media, with which he empathized. "Even I, who is in the industry, I just felt like a natural, ugh, why? The rest of your game looks fine. Did you need to? I think that's going to be the attitude for quite a while. I think people will look at it and say, did you need to do that? Couldn't you just do it yourself?"

"Gamers don't want it," Buckley said. "And if the gamers don't want it, I guess that's it, right? Not much of a conversation to be had." All this affirms what Buckley said last year regarding Pocketpair's refusal to publish games made with generative AI.

He also posited that a potential future where games are marketed by their authenticity, where disclosures exist not to denote games containing AI but those without it, are "a bit dystopian … that's kind of sad to think about." Given the resistance to AI disclosures by industry figures like Epic Games CEO Tim Sweeney, as well as the fact that multiple big games have been caught with undisclosed AI "placeholders" slipping into release versions, such a future doesn't feel out of the question.

Occasionally in hardware and technology reporting, I'm left to wonder if everyone else is in on a joke I'm not privy to. Today is one of those days. Snap, the company behind the instant messaging app Snapchat, has just unveiled its own augmented reality glasses.

Called Specs, the frames are pitched partially as an alternative to looking down at your phone screen all day, and a pair will set you back $2,195.

The goal was arguably to contain some serious hardware grunt inside a wearable, but the result is a pair of seriously chunky frames—not just to contain components but also likely to stop the whole thing from overheating. Let me set up the punchline: In this CNBC clip, Snap CEO Evan Spiegel describes Specs as both capable and "highly wearable," while the dorky-looking frames visibly crush down his ears.

Now that's a real howler. But before we completely dismiss this wearable effort, let's get into a few more choice details. For one thing, the lenses are apparently built to feel like "a 24-inch desktop monitor when you're working, or a 115-inch home cinema screen placed about 10 feet away when you're watching a movie." For another, the main selling point of Specs is that it's an all-in-one device, "with no puck and no tether," unlike some other major players' AR glasses projects we've seen recently.

Part of the frame's bulk can be attributed to the fact that it's housing not one but two Snapdragon processors. "One is dedicated to computer vision and the other is dedicated to running Lenses," Snap writes, "Together, they enable fast hand tracking, low latency, and responsive interactions that help digital content feel anchored in the real world. Specs deliver 7-millisecond motion-to-photon latency, verified through advanced robotic measurement systems."

In terms of battery life, you can expect a measly four hours of mixed use, "including audio and video playback, Lenses, AI assistance, Bluetooth notifications, and more." That said, the included charging case can offer four additional charges while out and about, holding a total of 20 hours of battery life. That's…still not great—though you could argue it avoids becoming yet another easy punchline.

What's perhaps less laughable for Snap itself is the hit its share price took when it revealed Specs. The original unveiling took place on June 16, and you'll notice a decline into today. This caps off six straight sessions of losses, according to Seeking Alpha. To be clear, I'm not faulting Specs' all-in-one ambitions on paper—it's more the fact that in practice, Snap is trying to deny a reality we can all see very obviously bearing down on its CEO's ears.

It's probably fair to say that Unreal Engine is probably the most comprehensive tool around for creating games, animations, and video effects. And, with the launch of UE 5.8, it's becoming even more extensive and even a little bit more AI-friendly. Whether you're just an Unreal Engine hobbyist like me, or a full-time game developer, you can download version 5.8 right now via the Epic Games Launcher.

Even if you don't plan on using any of the new features (of which there are a lot), it's always worth trying out the latest release just for bug and performance fixes. But what's actually new? The headline acts in UE5.8 are the introduction of Mesh Terrain and Procedural Vegetation Editor (PVE). Both are experimental features at the moment, but the former should be of great interest to anyone creating big, open-world terrains, as the tool basically generates full 3D meshes for you.

PVE is somewhat similar, except that instead of creating landscapes, it produces vegetation (trees, bushes, reeds, grass, etc) from scratch, with the procedural system working in line with meshes already present in the world. For example, let's say you had a crumbled old archway in a forest, PVE will 'grow' trees around it, accounting for the natural source of light and competing vegetation.

Complementing these are MegaLights, which first appeared in experimental form in UE5.5 (but is now "production-ready"), an experimental fog screen space scattering feature, and perhaps most interesting of all, Lumen Lite. This is a mode for Lumen global illumination that Epic claims to be twice as fast as Lumen High Quality, while still preserving "much of the visual impact".

The release notes for UE5.8 specifically mention that "games that rely on global illumination for artistic purposes can run on Nintendo Switch 2 at 60 fps," so it's blatantly obvious what platform it was developed for. However, since it's also supported on PC, UE-powered games of the future could well offer this as a graphics option for low-end hardware users.

Tucked away, almost at the end of the new version details announcement—which blessedly includes improvements to shader compiling—is one more experimental feature, an MCP plugin. With this, you can implement any LLM of your choice to "connect to and understand both the engine and your project." In other words, if you want to use AI to create assets or code, carry out tests or refactoring tasks, then you should be able to hand that over to the LLM easily enough.

Epic left the note about this feature after everything else, and I suspect that's because AI is hardly flavour of the month in the world of PCs and gaming right now. After all, Epic already has a section of PC gaming fandom that takes a dim view of Unreal Engine games, whether you believe that's the fault of Epic or a given game's developers themselves, and AI-use is another PC gaming bug bear.

Anyway, because of the consternation about AI in gaming—from being the primary cause of the horrendous price increases for DRAM and SSDs, as well as the endless controversies over its use in games—the inclusion of this plugin is likely to draw ire from some quarters.

The thing is, many game studios will have to rely increasingly more on AI for certain workloads if they hope to stay afloat. With the likes of Microsoft and numerous other companies about to swing a sword of Damocles across all their gaming divisions, studio heads will be looking at every avenue that will result in them having a future.

I'm not suggesting that game devs must use AI, nor am I saying that the inclusion of the LLM plugin (specifically an MCP server) with UE5.8 is a good or bad thing; it's simply a sign of our times. One can argue that Unreal Engine's feature set is sometimes a little too far-forward in reach (console and mainstream PC hardware still isn't quite good enough to cope with an all-in Lumen and Nanite game at high fps), but this minor plugin is very much a 'here-and-now' thing.

When the Nvidia CEO isn't busy basking in the adoration of fans at Computex Taiwan, it seems he might spend his time considering how to shift social norms. In what direction, you ask? Why, using AI more, of course.

That's what he told the Associated Press when the interviewer asked whether AI itself concerns people or "the absence of social structures to adapt to something happening so fast."

Jensen responded that "it's a combination of all that" but also emphasised that new social norms are needed: "You have to deal with regulation, technology, you have to deal with social norms."

He gives the example of automobiles and initial concerns over the harm they could do to people, especially children. But we changed social norms so that now kids are warned not to play in the street, there are laws surrounding speed, and so on.

However, when asked what social norm should be changed for AI, the answer isn't particularly satisfying: "The first thing is that I would advocate that everybody use AI. Just go engage it."

I'm not entirely sure that this response would traverse the analogy bridge over to automobiles very well. I can't imagine 'just use a car' would have been very convincing, back in the day. And I'm not sure how keen Huang would be on actually analogous shifts in norms and regulations, such as one akin to speed limits but for AI.

Huang says that, unlike pretty much any other technology, AI is free and easy to use, which is true enough on the surface. However, those 'free' tiers of AI aren't actually free. AI uses and inflates the price of technology that already exists. It's also subsidised by higher paid tiers, funny money inflating a ballooned market, and of course (and apologies for getting a little technical here) a metric s***ton of energy.

In other words, 'free' my arse.

I also can't help but wonder whether there's an element of worry in Huang imploring people to actually use AI. After all, if people don't actually use the technology, eventually that lack of end-user demand will catch up with AI companies, and in turn with the company that gives them their AI hardware: Nvidia.

As it stands, Nvidia is extremely profitable, but the companies that buy from Nvidia aren't. We'll just have to see how long it can last—markets are funny things.