Meta reportedly hires four more researchers from OpenAI


Looks like Meta isn’t done poaching talent from OpenAI.

Earlier this week, TechCrunch reported that Meta had hired influential OpenAI researcher Trapit Bansal, and according to The Wall Street Journal, it also hired three other researchers from the company.

Now The Information is reporting four more Meta hires from OpenAI: Researchers Shengjia Zhao, Jiahui Yu, Shuchao Bi, and Hongyu Ren.

This hiring spree comes after the April launch of Meta’s Llama 4 AI models, which reportedly did not perform as well as CEO Mark Zuckerberg had hoped. (The company was also criticized over the version of Llama that it used for a popular benchmark.)

There’s been some back-and-forth between the two companies, with OpenAI CEO Sam Altman suggesting that Meta was offering “$100 million signing bonuses” while adding that “so far, none of our best people” have left. Meta CTO Andrew Bosworth then told employees that while senior leaders may have been offered that kind of money, “the actual terms of the offer” were more complex than a simple one-time signing bonus.

The cracks in the OpenAI-Microsoft relationship are reportedly widening


OpenAI and Microsoft may be reaching an inflection point in their relationship, according to a report from The Wall Street Journal.

The report, citing anonymous sources, says OpenAI executives have considered publicly accusing Microsoft of anticompetitive behavior throughout their partnership. OpenAI executives also mulled whether to seek a federal regulatory review of their contract with Microsoft.

OpenAI is trying to loosen Microsoft’s grip on its intellectual property and computing resources, but the startup also needs the tech giant’s approval to complete its for-profit conversion.

The two companies are in a standoff over OpenAI’s $3 billion acquisition of the AI coding startup, Windsurf. OpenAI doesn’t want Microsoft to get Windsurf’s intellectual property — which could enhance the cloud provider’s own AI coding tool, GitHub Copilot — according to the report.

While Microsoft was once a major accelerant to OpenAI’s growth, the companies’ relationship has grown tense. In recent months, OpenAI has reportedly tried to reduce its reliance on Microsoft for cloud services.

OpenAI teams up with Cisco, Oracle to build UAE data center


As rumored, OpenAI is expanding its ambitious Stargate data center project to the Middle East.

On Thursday, the company announced Stargate UAE, which will bring a 1GW data center cluster to Abu Dhabi. OpenAI expects 200MW will go live in 2026, developed with partners including G42, Oracle, Nvidia, Cisco, and SoftBank.

In a blog post, OpenAI claims that Stargate UAE has the potential to provide AI infrastructure and compute capacity within a 2,000-mile radius.

“This is […] the first partnership under OpenAI for Countries⁠, our new global initiative to help interested governments build sovereign AI capability in coordination with the U.S. government,” writes OpenAI. “Under the partnership, the UAE will become the first country in the world to enable ChatGPT nationwide — giving people across the country the ability to access OpenAI’s technology.”

The unveiling of Stargate UAE comes the same week as billionaire Elon Musk said his AI company, xAI, would build the world’s first “gigawatt” AI training cluster.

OpenAI’s Big Bet That Jony Ive Can Make AI Hardware Work


OpenAI has fully acquired Io, a joint venture it cocreated last year with Jony Ive, the famed British designer behind the sleek industrial aesthetic that defined the iPhone and more than two decades of Apple products.

In a nearly 10-minute video posted to X Wednesday, Ive and OpenAI CEO Sam Altman said the Apple pioneer’s “creative collective” will “merge with OpenAI to work more intimately with the research, engineering, and product teams in San Francisco.” OpenAI says it’s paying $5 billion dollars in equity to acquire io.

The promotional video included musings on technology from both Ive and Altman, set against the golden-hour backdrop of the streets of San Francisco, but the two never share exactly what it is they’re building. “We look forward to sharing our work next year,” a text statement at the end of the video reads. Given the pair’s emphasis on building a hardware device for the AI era, and Ive’s pedigree at Apple, it’s likely a consumer-facing product.

Io launched last spring as part of a joint project between Ive’s design firm LoveFrom and OpenAI. In the fourth quarter of last year, Io and OpenAI entered into an official agreement for OpenAI to receive a 23 percent stake in io. Now, OpenAI is buying the entity outright.

The merger is a slightly complicated one. The Io team was made up of 55 people prior to this announcement. Now it will expand to include both io and OpenAI employees—hardware and software engineers, physicists, scientists, and “experts in product development and manufacturing,” according to a blog post on OpenAI’s website. Ive and Lovefrom will manage the creative design process. But Ive himself will remain independent, OpenAI says, and his firm LoveFrom will continue to operate as a separate entity. The io team will instead report into Peter Welinder, OpenAI’s vice president of product, who has worked at OpenAI for eight and a half years.

Io’s founding team has major design chops. Beyond Ive, the founders include Evans Hankey and Tang Tan, who both worked at Apple. Those who’ve worked closely with them say they’re known to hire people whom they believe have exceptional taste.

By bringing on Ive, OpenAI is officially embarking on what is likely one of the more ambitious AI hardware project to date. A number of other major tech companies, including Meta and Google, have tried developing AI-powered devices such as smartglasses in recent years, but mainstream adoption of the technology has been slow and some devices have been plagued by glitches.

Humane, another high-profile AI hardware startup founded by former Apple employees, debuted a wearable device in late 2023. Reviewers later found the device, a pin, was susceptible to overheating and a number of other issues. Less than two years later, Humane’s devices were pulled from the market and its operating system software and patents were sold to printer giant HP.

The joint effort between Altman and Ive was spurred by advancements in AI and also compute power. In its blog post, OpenAI wrote that “computers are now seeing, thinking and understanding.”

Altman reportedly has hardware ambitions beyond the generative AI software his company develops and sells, and Ive has seemingly been eager to make new imprints in the design world since he left Apple in 2019. “I have a growing sense that everything I have learned over the past 30 years has led me to this moment,” Ive said in the video. “While I am both anxious and excited about the responsibility of the substantial work ahead, I am so grateful for the opportunity to be a part of such an important collaboration.”

OpenAI’s planned data center in Abu Dhabi would be bigger than Monaco


OpenAI is poised to help develop a staggering 5-gigawatt data center campus in Abu Dhabi, positioning the company as a primary anchor tenant in what could become one of the world’s largest AI infrastructure projects, according to a new Bloomberg report.

The facility would reportedly span an astonishing 10 square miles and consume power equivalent to five nuclear reactors, dwarfing any existing AI infrastructure announced by OpenAI or its competitors. (OpenAI has not yet returned TechCrunch’s request for comment, but to put that into perspective, that’s bigger than Monaco.)

The UAE project, developed in partnership with G42 — an Abu Dhabi-based tech conglomerate — is part of OpenAI’s ambitious Stargate project, a joint venture announced in January that could see OpenAI, SoftBank, and Oracle build massive data centers around the globe stocked with powerful computer chips to support AI development.

While OpenAI’s first Stargate campus in the U.S. — already under development in Abilene, Texas — is expected to reach 1.2 gigawatts, this Middle Eastern counterpart would more than quadruple that capacity.

The project is emerging amid broader AI ties between the U.S. and UAE that have been years in the making, and have made some lawmakers nervous.

OpenAI’s relationship with the UAE dates back to a 2023 partnership with G42 aimed at driving AI adoption in the Middle East. During a talk earlier that same year in Abu Dhabi, OpenAI CEO Sam Altman praised the UAE, saying it “has been talking about AI since before it was cool.”

As with much of the AI world, these relationships are… complicated. Founded in 2018, G42 is chaired by Sheikh Tahnoon bin Zayed Al Nahyan, the UAE’s national security advisor and younger brother of the country’s ruler. Its embrace by OpenAI raised concerns in late 2023 among U.S. officials, who feared that G42 could enable China’s government to gain access to advanced U.S. technology.

These concerns focused on G42’s “active relationships” with blacklisted entities, including Huawei and Beijing Genomics Institute, as well as ties to individuals connected to China’s intelligence efforts.

Following pressure from U.S. lawmakers, G42’s CEO told Bloomberg in early 2024 that the company was shifting its strategy, saying: “All of our China investments that were previously made are already divested. Because of that, of course, we have no need anymore for any physical China presence.”

Soon after, Microsoft — a major shareholder in OpenAI with its own broader interests in the region — announced a $1.5 billion investment in G42, and its president, Brad Smith, joined G42’s board of directors.

The Middle East Has Entered the AI Group Chat


Donald Trump’s jaunt to the Middle East featured an entourage of billionaire tech bros, a fighter-jet escort, and business deals designed to reshape the global landscape of artificial intelligence.

On the final stop of the tour in Abu Dhabi, the US president announced that unnamed US companies would partner with the United Arab Emirates to create the largest AI datacenter cluster outside of America.

Trump said that the US companies will help G42, an Emirati company, build five gigawatts of AI computing capacity in the UAE.

Sheikh Tahnoon bin Zayed Al Nahyan, who leads the UAE’s Artificial Intelligence and Advanced Technology Council and is in charge of a $1.5 trillion fortune aimed at building AI capabilities, said the move will strengthen the UAE’s position “as a hub for cutting-edge research and sustainable development, delivering transformative benefits for humanity.”

A few days earlier, as Trump arrived in Riyadh, Saudi Arabia announced Humain, an AI investment firm owned by the kingdom’s Public Investment Fund. The Saudi firm launched with blockbuster deals already inked with Nvidia, AMD, Qualcomm, and AWS—US tech giants capable of building the infrastructure needed to train and power cutting-edge AI models.

Trump said in a speech in Riyadh that US and Saudi companies would do deals worth hundreds of billions of dollars, with a focus on infrastructure, tech, and defense.

The deals forged in the Middle East this week are meant to strengthen the global importance of American silicon and AI, but they will also help nations like Saudi Arabia play a more significant role in the global race to develop and distribute cutting-edge technology.

“It will help the Saudis and the UAE become bigger players in providing AI infrastructure,” says Paul Triolo, a partner at DGA-Albright Stonebridge Group, a geopolitical consulting group. “It’s a big deal to get access to these GPUs.”

Saudi Arabia’s deal with Nvidia, which dominates the market for AI training hardware, will amount to 500 megawatts of capacity and involve “several hundred thousand of Nvidia’s most advanced GPUs over the next five years,” the company said in a statement.

According to one estimate, this could translate to around 250,000 of Nvidia’s most advanced chips, which are four times better at training and 30 times better at inference (running models that have already been trained) than the next-best offering. This capacity could lead Saudi Arabia to create frontier AI models.

AWS and Humain said they would jointly invest $5 billion in infrastructure in Saudi Arabia. AWS said in March that it will build an AI infrastructure zone in the country, investing more than $5.3 billion. Humain and AMD said they would spend $10 billion on AI infrastructure in Saudi Arabia and the US over the next five years.

Saudi Arabia, the UAE, and other nations in the region have vast quantities of oil money, access to plenty of power, and a strong desire to shift toward more high-tech economies by building out cutting-edge tech infrastructure. The countries also, however, have significant business ties to China, which sells technology to the region, placing them at the nexus of a growing geopolitical rivalry over the future of AI.

Diffusion Rule

A few days before Trump’s visit to the Middle East, his administration reversed a major Biden-era ruling that would have limited the sale of cutting-edge chips globally. The directive created tiers of nations with different access to cutting edge chips, and sought to limit how many chips Saudi Arabia and the UAE could buy. Critics of the rule suggested it might push some countries to buy Chinese technology instead.

In a statement announcing the change, the US Bureau of Industry and Security said the Biden rule “would have stifled American innovation and saddled companies with burdensome new regulatory requirements” and “undermined U.S. diplomatic relations with dozens of countries by downgrading them to second-tier status.”

Studio Ghibli hasn’t commented on OpenAI’s onslaught of AI copies, but the fan subreddit has


When OpenAI debuted its image-generation feature in ChatGPT last week, social media exploded when users realized that they could make AI-generated images that looked like something out of an animated film from Studio Ghibli. Fans hoped that Studio Ghibli mastermind Hayao Miyazaki would take a stand, but the 84-year-old animator has remained silent. In the Ghibli fan subreddit, however, fans are enforcing a long-standing ban against AI art.

“I just noticed about a dozen different ‘BAN AI NOW’ posts here seemingly spurred on by an influx of AI Ghibli art on other sites,” a moderator posted to the Ghibli subreddit last week. “We don’t allow AI art. We haven’t allowed it basically since it became a thing.”

These fans don’t see the AI-generated copies as an homage to the iconic artist. Rather, these generative AI models are trained on copyrighted images from artists like Miyazaki, who never gave OpenAI or any of its competitors permission to use their work as such.

This issue is one that’s impacted other creators and writers, too. The New York Times and other publishers have sued OpenAI, alleging that the company used its copyrighted materials to train its models without payment or consent. Similar complaints have been filed against Meta and Midjourney.

The Ghibli situation struck a particularly strong nerve among fans since the studio’s mastermind, Hayao Miyazaki, has been vocal about his hatred for AI-generated artwork.

“I can’t watch this stuff and find it interesting,” Miyazaki said in documentary footage from 2016 in which he was shown AI-generated 3D animation. “Whoever creates this stuff has no idea what pain is whatsoever. I am utterly disgusted.”

People have also generated portraits in the style of Pixar movies or Dr. Seuss illustrations. Even the White House’s X account posted a Ghibli-style image, crudely mocking a woman for crying while being handcuffed by ICE.

As more “Ghiblified” images spread across the internet, fans of the legendary 84-year-old animator resurfaced his commentary to discourage others from imitating his work, but the damage had already been done. Of course, not all of these are Ghibli-style images, but the popularity of these images has stretched the AI company’s capacity.

OpenAI’s Brad Lightcap, who oversees day-to-day operations at the company, said that over 130 million users have generated more than 700 million images with this new ChatGPT feature.

“The range of visual creativity has been extremely inspiring,” Lightcap wrote.

Researchers suggest OpenAI trained AI models on paywalled O’Reilly books


OpenAI has been accused by many parties of training its AI on copyrighted content sans permission. Now a new paper by an AI watchdog organization makes the serious accusation that the company increasingly relied on nonpublic books it didn’t license to train more sophisticated AI models.

AI models are essentially complex prediction engines. Trained on a lot of data — books, movies, TV shows, and so on — they learn patterns and novel ways to extrapolate from a simple prompt. When a model “writes” an essay on a Greek tragedy or “draws” Ghibli-style images, it’s simply pulling from its vast knowledge to approximate. It isn’t arriving at anything new.

While a number of AI labs, including OpenAI, have begun embracing AI-generated data to train AI as they exhaust real-world sources (mainly the public web), few have eschewed real-world data entirely. That’s likely because training on purely synthetic data comes with risks, like worsening a model’s performance.

The new paper, out of the AI Disclosures Project, a nonprofit co-founded in 2024 by media mogul Tim O’Reilly and economist Ilan Strauss, draws the conclusion that OpenAI likely trained its GPT-4o model on paywalled books from O’Reilly Media. (O’Reilly is the CEO of O’Reilly Media.)

In ChatGPT, GPT-4o is the default model. O’Reilly doesn’t have a licensing agreement with OpenAI, the paper says.

“GPT-4o, OpenAI’s more recent and capable model, demonstrates strong recognition of paywalled O’Reilly book content … compared to OpenAI’s earlier model GPT-3.5 Turbo,” wrote the co-authors of the paper. “In contrast, GPT-3.5 Turbo shows greater relative recognition of publicly accessible O’Reilly book samples.”

The paper used a method called DE-COP, first introduced in an academic paper in 2024, designed to detect copyrighted content in language models’ training data. Also known as a “membership inference attack,” the method tests whether a model can reliably distinguish human-authored texts from paraphrased, AI-generated versions of the same text. If it can, it suggests that the model might have prior knowledge of the text from its training data.

The co-authors of the paper — O’Reilly, Strauss, and AI researcher Sruly Rosenblat — say that they probed GPT-4o, GPT-3.5 Turbo, and other OpenAI models’ knowledge of O’Reilly Media books published before and after their training cutoff dates. They used 13,962 paragraph excerpts from 34 O’Reilly books to estimate the probability that a particular excerpt had been included in a model’s training dataset.

According to the results of the paper, GPT-4o “recognized” far more paywalled O’Reilly book content than OpenAI’s older models, including GPT-3.5 Turbo. That’s even after accounting for potential confounding factors, the authors said, like improvements in newer models’ ability to figure out whether text was human-authored.

“GPT-4o [likely] recognizes, and so has prior knowledge of, many non-public O’Reilly books published prior to its training cutoff date,” wrote the co-authors.

It isn’t a smoking gun, the co-authors are careful to note. They acknowledge that their experimental method isn’t foolproof and that OpenAI might’ve collected the paywalled book excerpts from users copying and pasting it into ChatGPT.

Muddying the waters further, the co-authors didn’t evaluate OpenAI’s most recent collection of models, which includes GPT-4.5 and “reasoning” models such as o3-mini and o1. It’s possible that these models weren’t trained on paywalled O’Reilly book data or were trained on a lesser amount than GPT-4o.

That being said, it’s no secret that OpenAI, which has advocated for looser restrictions around developing models using copyrighted data, has been seeking higher-quality training data for some time. The company has gone so far as to hire journalists to help fine-tune its models’ outputs. That’s a trend across the broader industry: AI companies recruiting experts in domains like science and physics to effectively have these experts feed their knowledge into AI systems.

It should be noted that OpenAI pays for at least some of its training data. The company has licensing deals in place with news publishers, social networks, stock media libraries, and others. OpenAI also offers opt-out mechanisms — albeit imperfect ones — that allow copyright owners to flag content they’d prefer the company not use for training purposes.

Still, as OpenAI battles several suits over its training data practices and treatment of copyright law in U.S. courts, the O’Reilly paper isn’t the most flattering look.

OpenAI didn’t respond to a request for comment.

Microsoft reportedly ramps up AI efforts to compete with OpenAI


Microsoft is accelerating its push to compete with OpenAI, its longtime collaborator, by developing its own powerful AI models and exploring alternatives to power products like Microsoft’s Copilot bot.

Microsoft has developed its own AI “reasoning” models comparable to models like OpenAI’s o1 and o3-mini, the The Information reports. OpenAI is said to have refused Microsoft’s requests for technical details about how o1 works — stoking tensions between the firms.

Microsoft has also developed a family of models called MAI that are competitive with OpenAI’s own, Bloomberg reports, and is reportedly considering offering them through an API later this year. Parallel to those efforts, Microsoft is said to be testing alternative AI models from xAI, Meta, Anthropic, and DeepSeek as possible replacements for OpenAI technology in Copilot.

Microsoft, which has invested around $14 billion in OpenAI to date, has looked to hedge its bets in a number of ways, including hiring DeepMind and Inflection co-founder Mustafa Suleyman to lead the tech giant’s AI efforts.

Did xAI lie about Grok 3’s benchmarks?


Debates over AI benchmarks — and how they’re reported by AI labs — are spilling out into public view.

This week, an OpenAI employee accused Elon Musk’s AI company, xAI, of publishing misleading benchmark results for its latest AI model, Grok 3. One of the co-founders of xAI, Igor Babushkin, insisted that the company was in the right.

The truth lies somewhere in between.

In a post on xAI’s blog, the company published a graph showing Grok 3’s performance on AIME 2025, a collection of challenging math questions from a recent invitational mathematics exam. Some experts have questioned AIME’s validity as an AI benchmark. Nevertheless, AIME 2025 and older versions of the test are commonly used to probe a model’s math ability.

xAI’s graph showed two variants of Grok 3, Grok 3 Reasoning Beta and Grok 3 mini Reasoning, beating OpenAI’s best-performing available model, o3-mini-high, on AIME 2025. But OpenAI employees on X were quick to point out that xAI’s graph didn’t include o3-mini-high’s AIME 2025 score at “cons@64.”

What is cons@64, you might ask? Well, it’s short for “consensus@64,” and it basically gives a model 64 tries to answer each problem in a benchmark and takes the answers generated most frequently as the final answers. As you can imagine, cons@64 tends to boost models’ benchmark scores quite a bit, and omitting it from a graph might make it appear as though one model surpasses another when in reality, that’s isn’t the case.

Grok 3 Reasoning Beta and Grok 3 mini Reasoning’s scores for AIME 2025 at “@1” — meaning the first score the models got on the benchmark — fall below o3-mini-high’s score. Grok 3 Reasoning Beta also trails ever-so-slightly behind OpenAI’s o1 model set to “medium” computing. Yet xAI is advertising Grok 3 as the “world’s smartest AI.”

Babushkin argued on X that OpenAI has published similarly misleading benchmark charts in the past — albeit charts comparing the performance of its own models. A more neutral party in the debate put together a more “accurate” graph showing nearly every model’s performance at cons@64:

But as AI researcher Nathan Lambert pointed out in a post, perhaps the most important metric remains a mystery: the computational (and monetary) cost it took for each model to achieve its best score. That just goes to show how little most AI benchmarks communicate about models’ limitations — and their strengths.