OpenAI’s “Thinking” Model and $150B Valuation

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OpenAI is reportedly in talks to raise $7b at a $150b valuation led by Josh Kushner’s Thrive Capital joined by Microsoft, Apple, Nvidia and Emirati VC MGX. It also aims to secure a $5b credit from banks.

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THE HOTTEST THING IN TECH
OpenAI’s “Thinking” Model and $150B Valuation

It’s been another big news week for OpenAI. We got updated details about the fundraising efforts (now $7b at a $150B valuation) and the release of the o1 reasoning model. An OpenAI exec also said ChatGPT passed 11 million paying subscribers, implying it is generating at least $225M a month. So is this new model really revolutionary, and more importantly, does any of this justify a $150B valuation?

A Reasoning Model

The release of OpenAI’s o1 (codename “strawberry”) model family is getting a lot of hype. It’s a group of language models (small and large) that are supposed to have more reasoning capabilities. What OpenAI claims makes these models different is their ability to fact-check itself & "think" before responding to reach better outcomes on complex problems than previous models in science, coding, and math.

In other words o1 is slower, on purpose. It takes 5-10 seconds to think before answering. OpenAI claims this offers major improvements in PhD-Level physics questions. But here’s the kicker, it’s ~100x more expensive than GPT-4o mini.

UX and Paradigm Shift

But, this implies what we have here is more of an orchestration and UX improvement than any real improvement in the model. AI expert Jim Fan said “We are finally seeing the paradigm of inference-time scaling popularized and deployed in production.” So perhaps as Sam Altman also claims, this is the start of a new paradigm for consumer AI models, but what is being offered is hardly new technology.

Earlier this year, AI startup OpenPipe released their MoA “mixture of agents” approach—a re-prompted chain of thought orchestration. It keeps asking questions and then feeds them back in over and over to "think" before it gets to an answer. Running it on small open source models like Llama, it outperformed GPTs. But it’s super slow and expensive. Sound familiar? In summary, it may make life easier for some with money and no time to set and forget functions by calling an OpenAI API to get an expensive, slow answer that's better than ChatGPT. But it won’t seriously change life for most serious AI developers at this stage.

“Concerning Capabilities”

This has also raised some concerns that this model is too good, and therefore dangerous. The o1 model safety card reveals a range of “concerning capabilities”, including scheming, reward hacking, and biological weapon creation. But, is this really just branding to make o1 appear smarter than it is? There is no evidence yet it poses a significant danger. It’s still relevant that OpenAI may be inching towards models that might be too risky to release. If they are, they are likely not the only ones, so it doesn’t seem like there is much that can be done to prevent it at this point.

So, About that $150B Valuation…

OpenAI is reportedly in talks to raise $7b at a $150b valuation led by Josh Kushner’s Thrive Capital. It also aims to secure a $5b credit from banks. So is an estimated 18x revenue multiple justified? As Martin Peers says, it likely isn’t so important for the big tech firms like Apple, Microsoft and Nvidia (or Emirati VC MGX) being a strategic, rather than an appreciation play for them. For individual investors, though, it makes a lot less sense. Unless of course, it’s a long-term bet on the costs of AI compute, energy and other overheads dropping exponentially to increase profit margins.

"We’re finally seeing the paradigm of inference-time scaling popularized & deployed in production. There're only 2 techniques that scale indefinitely with compute: learning & search. It's time to shift focus to the latter.”

Dr Jim Fan, Sr. Research Manager & Lead of Embodied AI (GEAR Lab)

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