OpenAI is showing that the AI race is survival of the richest
The startup race to build powerful AI models looks set to get a whole lot more expensive.
OpenAI, which last year secured $10 billion, is said to be in talks to raise additional billions.
Its rush for new capital is a sign that the AI race will be survival of the richest for startups.
The battle among frontier AI companies in startupland is looking more and more like survival of the richest. Just take a look at the latest from OpenAI.
On Wednesday, Bloomberg reported that the poster company of the generative-AI boom was in talks to raise $6.5 billion from investors at a $150 billion valuation. It's also said to be in separate talks with banks over a debt raise through a $5 billion revolving credit facility.
At a $150 billion valuation, OpenAI would almost double the $86 billion value it held during a tender offer earlier this year. It would also vault the company closer to the heights of Elon Musk's SpaceX, reported to be valued at $210 billion, and TikTok's parent company, ByteDance, said to be worth almost $230 billion.
It's a sign of just how far OpenAI has come since November 2022, when its CEO, Sam Altman, described ChatGPT as "an early demo of what's possible." It's also a sign of just how expensive the business of training and running AI models is getting.
Generative AI is a cash-guzzler
It was only last year that OpenAI disclosed it had secured a $10 billion investment from Microsoft in a deal that extended a partnership struck in 2019.
Back then, in January 2023, OpenAI said it had worked with Microsoft to "build multiple supercomputing systems" — powered by the tech giant's Azure cloud platform — that could be used to train its models. OpenAI said it would use that $10 billion investment to boost these systems.
Since OpenAI launched ChatGPT in late 2022, it's become evident that making the large language models behind generative-AI applications smarter — a fundamental goal — is an expensive endeavor.
Just look at the spending of Big Tech firms working to improve their AI models. In the latest quarter alone, the total capital expenditures of Alphabet, Amazon, Meta, and Microsoft hit $52.9 billion, almost double what they spent in the same quarter in 2023, per The Wall Street Journal.
Much of that has been directed toward assets critical for strengthening their AI, such as buying expensive chips from the likes of Nvidia and building data centers to host those chips for training and inference.
While privately held startups working on large language models, or LLMs, aren't in the business of building data centers like Big Tech's cloud players, they're trying to secure as many powerful chips as they can to ensure they have enough computing power to build their next-generation models.
Industry projections indicate just how expensive this is going to get. Earlier this year, Dario Amodei, the CEO of the OpenAI rival Anthropic, predicted that within two years training AI models could cost $10 billion — and that pretty soon that could hit $100 billion.
This is a tricky situation for startups, of course, given that they don't have quite the same deep pockets as their publicly traded counterparts. Their traditional funding sources in venture capital may not suffice.
Bloomberg's report said OpenAI had lined up blue-chip names including Apple, Microsoft, and Nvidia as potential backers for its investment round, alongside the lead investor, Thrive Capital. That raises the bar for the handful of startup competitors it faces.
Anthropic seems to have gotten the memo. It raised $2.75 billion from Amazon in March, taking its total raised from the Big Tech firm to $4 billion. It was last valued at $18.4 billion.
OpenAI's top European rival, Mistral, raised fresh capital at a $6.2 billion valuation in June; its funding round was peppered with big corporate names such as Nvidia and Samsung alongside VC heavyweights such as A16z and Lightspeed.
It remains to be seen which companies will stay the course. Consolidation has struck the AI industry in recent months as some top startups trying to build AI models have been gutted.
In August, for instance, news emerged that Google had hired Noam Shazeer, a former Googler who was most recently the CEO of Character AI, and secured a licensing agreement for its LLM technology.
As my colleagues Ben Bergman and Sri Muppidi noted last month, Character AI's growth "has not been blockbuster and revenue is minimal" — as a result, it "did not have enough momentum to raise another big round in today's ultracompetitive funding environment."
This looks to be the key challenge for startups seeking to get an edge in LLMs and cut into OpenAI's lead, especially as profit remains a distance away. Altman has reportedly suggested that OpenAI's annualized revenue is on track to be $3.4 billion this year, though it's not profitable.
In a recent episode of the "No Priors" podcast, the tech investor Elad Gil suggested that "enormous capital moats are emerging" among startups looking to scale their LLMs. The goal for many, of course, is AI that is as intelligent as humans.
"Everybody's partnering up, and so it's a really interesting question to ask," Gil said. "For all the other players in the market, where are they going to get these ever rising amounts of capital, and who do they partner with?"
AI startups serious about progressing on LLMs will need to figure out the answer to this pretty quickly. Failure may lie ahead if they don't.
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