OpenAI has finally shared details about its plans to shake up its core business by shifting to a for-profit corporate structure.
On Thursday, OpenAI posted on its blog, confirming that in 2025, the existing for-profit arm will be transformed into a Delaware-based public benefit corporation (PBC). As a PBC, OpenAI would be required to balance its shareholders’ and stakeholders’ interests with the public benefit. To achieve that, OpenAI would offer “ordinary shares of stock” while using some profits to further its mission—”ensuring artificial general intelligence (AGI) benefits all of humanity”—to serve a social good.
To compensate for losing control over the for-profit, the nonprofit would have some shares in the PBC, but it’s currently unclear how many will be allotted. Independent financial advisors will help OpenAI reach a “fair valuation,” the blog said, while promising the new structure would “multiply” the donations that previously supported the nonprofit.
“Our plan would result in one of the best resourced nonprofits in history,” OpenAI said. (During its latest funding round, OpenAI was valued at $157 billion.)
OpenAI claimed the nonprofit’s mission would be more sustainable under the proposed changes, as the costs of AI innovation only continue to compound. The new structure would set the PBC up to control OpenAI’s operations and business while the nonprofit would “hire a leadership team and staff to pursue charitable initiatives in sectors such as health care, education, and science,” OpenAI said.
Some of OpenAI’s rivals, such as Anthropic and Elon Musk’s xAI, use a similar corporate structure, OpenAI noted.
Critics had previously pushed back on this plan, arguing that humanity may be better served if the nonprofit continues controlling the for-profit arm of OpenAI. But OpenAI argued that the old way made it hard for the Board “to directly consider the interests of those who would finance the mission and does not enable the non-profit to easily do more than control the for-profit.
Enlarge/ Elon Musk, chief executive officer of Tesla Inc., during a fireside discussion on artificial intelligence risks with Rishi Sunak, UK prime minister, in London, UK, on Thursday, Nov. 2, 2023.
On Monday, Elon Musk announced the start of training for what he calls “the world’s most powerful AI training cluster” at xAI’s new supercomputer facility in Memphis, Tennessee. The billionaire entrepreneur and CEO of multiple tech companies took to X (formerly Twitter) to share that the so-called “Memphis Supercluster” began operations at approximately 4: 20 am local time that day.
Musk’s xAI team, in collaboration with X and Nvidia, launched the supercomputer cluster featuring 100,000 liquid-cooled H100 GPUs on a single RDMA fabric. This setup, according to Musk, gives xAI “a significant advantage in training the world’s most powerful AI by every metric by December this year.”
Given issues with xAI’s Grok chatbot throughout the year, skeptics would be justified in questioning whether those claims will match reality, especially given Musk’s tendency for grandiose, off-the-cuff remarks on the social media platform he runs.
Power issues
According to a report by News Channel 3 WREG Memphis, the startup of the massive AI training facility marks a milestone for the city. WREG reports that xAI’s investment represents the largest capital investment by a new company in Memphis’s history. However, the project has raised questions among local residents and officials about its impact on the area’s power grid and infrastructure.
WREG reports that Doug McGowen, president of Memphis Light, Gas and Water (MLGW), previously stated that xAI could consume up to 150 megawatts of power at peak times. This substantial power requirement has prompted discussions with the Tennessee Valley Authority (TVA) regarding the project’s electricity demands and connection to the power system.
The TVA told the local news station, “TVA does not have a contract in place with xAI. We are working with xAI and our partners at MLGW on the details of the proposal and electricity demand needs.”
The local news outlet confirms that MLGW has stated that xAI moved into an existing building with already existing utility services, but the full extent of the company’s power usage and its potential effects on local utilities remain unclear. To address community concerns, WREG reports that MLGW plans to host public forums in the coming days to provide more information about the project and its implications for the city.
For now, Tom’s Hardware reports that Musk is side-stepping power issues by installing a fleet of 14 VoltaGrid natural gas generators that provide supplementary power to the Memphis computer cluster while his company works out an agreement with the local power utility.
As training at the Memphis Supercluster gets underway, all eyes are on xAI and Musk’s ambitious goal of developing the world’s most powerful AI by the end of the year (by which metric, we are uncertain), given the competitive landscape in AI at the moment between OpenAI/Microsoft, Amazon, Apple, Anthropic, and Google. If such an AI model emerges from xAI, we’ll be ready to write about it.
This article was updated on July 24, 2024 at 1: 11 pm to mention Musk installing natural gas generators onsite in Memphis.
Enlarge/ Tesla will have to rely on its Dojo supercomputer for a while longer after CEO Elon Musk diverted 12,000 Nvidia GPU clusters to X instead.
Tesla
Elon Musk is yet again being accused of diverting Tesla resources to his other companies. This time, it’s high-end H100 GPU clusters from Nvidia. CNBC’s Lora Kolodny reports that while Tesla ordered these pricey computers, emails from Nvidia staff show that Musk instead redirected 12,000 GPUs to be delivered to his social media company X.
It’s almost unheard of for a profitable automaker to pivot its business into another sector, but that appears to be the plan at Tesla as Musk continues to say that the electric car company is instead destined to be an AI and robotics firm instead.
Does Tesla make cars or AI?
That explains why Musk told investors in April that Tesla had spent $1 billion on GPUs in the first three months of this year, almost as much as it spent on R&D, despite being desperate for new models to add to what is now an old and very limited product lineup that is suffering rapidly declining sales in the US and China.
Despite increasing federal scrutiny here in the US, Tesla has reduced the price of its controversial “full-self driving” assist, and the automaker is said to be close to rolling out the feature in China. (Questions remain about how many Chinese Teslas would be able to utilize this feature given that a critical chip was left out of 1.2 million cars built there during the chip shortage.)
Perfecting this driver assist would be very valuable to Tesla, which offers FSD as a monthly subscription as an alternative to a one-off payment. The profit margins for subscription software services vastly outstrip the margins Tesla can make selling physical cars, which dropped to just 5.5 percent for Q1 2024. And Tesla says that massive GPU clusters are needed to develop FSD’s software.
Isn’t Tesla desperate for Nvidia GPUs?
Tesla has been developing its own in-house supercomputer for AI, called Dojo. But Musk has previously said that computer could be redundant if Tesla could source more H100s. “If they could deliver us enough GPUs, we might not need Dojo, but they can’t because they’ve got so many customers,” Musk said during a July 2023 investor day.
Which makes his decision to have his other companies jump all the more notable. In December, an internal Nvidia memo seen by CNBC said, “Elon prioritizing X H100 GPU cluster deployment at X versus Tesla by redirecting 12k of shipped H100 GPUs originally slated for Tesla to X instead. In exchange, original X orders of 12k H100 slated for Jan and June to be redirected to Tesla.”
X and the affiliated xAi are developing generative AI products like large language models.
Not the first time
This is not the first time that Musk has been accused of diverting resources (and his time) from publicly held Tesla to his other privately owned enterprises. In December 2022, US Sen. Elizabeth Warren (D-Mass.) wrote to Tesla asking Tesla to explain whether Musk was diverting Tesla resources to X (then called Twitter):
This use of Tesla employees raises obvious questions about whether Mr. Musk is appropriating resources from a publicly traded firm, Tesla, to benefit his own private company, Twitter. This, of course, would violate Mr. Musk’s legal duty of loyalty to Tesla and trigger questions about the Tesla Board’s responsibility to prevent such actions, and may also run afoul other “anti-tunneling rules that aim to prevent corporate insiders from extracting resources from their firms.”
These latest accusations of misuse of Tesla resources come at a time when Musk is asking shareholders to reapprove what is now a $46 billion stock compensation plan.
Grok, the AI language model created by Elon Musk’s xAI, went into wide release last week, and people have begun spotting glitches. On Friday, security tester Jax Winterbourne tweeted a screenshot of Grok denying a query with the statement, “I’m afraid I cannot fulfill that request, as it goes against OpenAI’s use case policy.” That made ears perk up online since Grok isn’t made by OpenAI—the company responsible for ChatGPT, which Grok is positioned to compete with.
Interestingly, xAI representatives did not deny that this behavior occurs with its AI model. In reply, xAI employee Igor Babuschkin wrote, “The issue here is that the web is full of ChatGPT outputs, so we accidentally picked up some of them when we trained Grok on a large amount of web data. This was a huge surprise to us when we first noticed it. For what it’s worth, the issue is very rare and now that we’re aware of it we’ll make sure that future versions of Grok don’t have this problem. Don’t worry, no OpenAI code was used to make Grok.”
In reply to Babuschkin, Winterbourne wrote, “Thanks for the response. I will say it’s not very rare, and occurs quite frequently when involving code creation. Nonetheless, I’ll let people who specialize in LLM and AI weigh in on this further. I’m merely an observer.”
Enlarge/ A screenshot of Jax Winterbourne’s X post about Grok talking like it’s an OpenAI product.
Jason Winterbourne
However, Babuschkin’s explanation seems unlikely to some experts because large language models typically do not spit out their training data verbatim, which might be expected if Grok picked up some stray mentions of OpenAI policies here or there on the web. Instead, the concept of denying an output based on OpenAI policies would probably need to be trained into it specifically. And there’s a very good reason why this might have happened: Grok was fine-tuned on output data from OpenAI language models.
“I’m a bit suspicious of the claim that Grok picked this up just because the Internet is full of ChatGPT content,” said AI researcher Simon Willison in an interview with Ars Technica. “I’ve seen plenty of open weights models on Hugging Face that exhibit the same behavior—behave as if they were ChatGPT—but inevitably, those have been fine-tuned on datasets that were generated using the OpenAI APIs, or scraped from ChatGPT itself. I think it’s more likely that Grok was instruction-tuned on datasets that included ChatGPT output than it was a complete accident based on web data.”
As large language models (LLMs) from OpenAI have become more capable, it has been increasingly common for some AI projects (especially open source ones) to fine-tune an AI model output using synthetic data—training data generated by other language models. Fine-tuning adjusts the behavior of an AI model toward a specific purpose, such as getting better at coding, after an initial training run. For example, in March, a group of researchers from Stanford University made waves with Alpaca, a version of Meta’s LLaMA 7B model that was fine-tuned for instruction-following using outputs from OpenAI’s GPT-3 model called text-davinci-003.
On the web you can easily find several open source datasets collected by researchers from ChatGPT outputs, and it’s possible that xAI used one of these to fine-tune Grok for some specific goal, such as improving instruction-following ability. The practice is so common that there’s even a WikiHow article titled, “How to Use ChatGPT to Create a Dataset.”
It’s one of the ways AI tools can be used to build more complex AI tools in the future, much like how people began to use microcomputers to design more complex microprocessors than pen-and-paper drafting would allow. However, in the future, xAI might be able to avoid this kind of scenario by more carefully filtering its training data.
Even though borrowing outputs from others might be common in the machine-learning community (despite it usually being against terms of service), the episode particularly fanned the flames of the rivalry between OpenAI and X that extends back to Elon Musk’s criticism of OpenAI in the past. As news spread of Grok possibly borrowing from OpenAI, the official ChatGPT account wrote, “we have a lot in common” and quoted Winterbourne’s X post. As a comeback, Musk wrote, “Well, son, since you scraped all the data from this platform for your training, you ought to know.”
