Following a report last week about Apple holding internal talks over a potential Perplexity acquisition, Mark Gurman’s latest Power On newsletter revealed that Apple also explored a possible deal with another notable name in the AI space: Mira Murati. Here’s what went down.
Murati, best known as OpenAI’s former Chief Technology Officer, left the company last year following the boardroom chaos that briefly saw CEO Sam Altman ousted.
In fact, as detailed in the book “The Optimist: Sam Altman, OpenAI, and the Race to Invent the Future”, Murati and OpenAI co-founder and Chief Scientist Ilya Sutskever were key players behind the scenes in the surreal boardroom coup that briefly ousted Altman.
Murati even spent a few hours as OpenAI’s interim CEO before, in an ironic twist, threatening to quit unless Altman was reinstated. By that point, it was clear the coup had failed, and Murati, like others involved, backtracked in an effort to save both the company. And their own jobs.
Less than a year later, Murati left OpenAI and founded a new AI startup called Thinking Machines Lab (by then, Ilya Sutskever had also left to found his own company, Safe SuperIntelligence). And now, according to Gurman, it appears Apple met with her earlier this year to discuss a potential acquisition.
What is Thinking Machines Lab?
Murati’s company is the perfect portrait of the current AI landscape: While it doesn’t have a product yet, it has just closed the largest seed round ever for any company, with a $2 billion fundraise led by Andreessen Horowitz. That placed the company’s valuation at a whopping US$10 billion.
So far, what has been made public about Thinking Machine Labs is its purpose, which is to build “a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.”
Here’s an excerpt from their launch manifesto, which you can read in full on their website:
“The scientific community’s understanding of frontier AI systems lags behind rapidly advancing capabilities. Knowledge of how these systems are trained is concentrated within the top research labs, limiting both the public discourse on AI and people’s abilities to use AI effectively. And, despite their potential, these systems remain difficult for people to customize to their specific needs and values. To bridge the gaps, we’re building Thinking Machines Lab to make AI systems more widely understood, customizable and generally capable.”
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