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AGI DON’T KNOW

When is AGI coming? These experts have it figured it out.

We’re keeping them honest with the Sherwood News AGI Prediction Tracker.

6/12/25 11:47AM

Updated 7/16/25 9:52AM

Can you feel the AGI? It’s coming.

At least that’s what a lot of big names in AI are saying. While there isn’t even an agreed upon definition of what AGI — artificial general intelligence — is, these AI guys are confident enough to say it is going to happen, and they know when (give or take a few years).

The definition of AGI varies widely. OpenAI’s charter defines it as “highly autonomous systems that outperform humans at most economically valuable work,” while Elon Musk says it’s AI that is “smarter than the smartest human.” Anthropic CEO Dario Amodei thinks AGI is more like a “country of geniuses in a datacenter.”

But the core idea is an AI system that is better than humans at most tasks. The trick is, once someone claims to have achieved AGI, it isn’t clear everyone will agree that they have.

And yes, we did look at what many non-male AI experts have been saying about AGI, but most of them aren't making predictions because a lot of them don't think AGI is a thing that will happen.

Dr. Emily M. Bender, professor of linguistics at The University of Washington, and Dr. Alex Hanna, Director of Research at the Distributed AI Research (DAIR), co-authors of "The AI Con: How to Fight Big Tech's Hype and Create the Future We Want" call out the promises of AGI, and question the true motives of those calling AGI's arrival imminent:

“The term is a vague signifier for a technology that will somehow lead to endless abundance for humankind — and conveniently also a means to avoid accountability as tech moguls make off with billions in capital investment and, more alarmingly, public spending.”

Everyone hedges their bets, and some of the thresholds may be fuzzy, but we’ve been hearing these predictions enough that we felt we needed to track them. From the leaders of Alphabet to Tesla, here’s when the best-known AI thinkers — and those who have the most to gain from the innovation — think AGI is coming.

We’ll keep this tracker updated. Seen one that we’ve missed? Send them our way: keegan@sherwoodmedia.com!

UPDATE (July 16): Added Dr. Alex Hanna to quote attribution.

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Microsoft shares dropped as it announced a revised agreement with OpenAI.

The amended agreement ends revenue-sharing payments from Microsoft to OpenAI, and also ends Microsoft’s exclusive access to OpenAI’s intellectual property (i.e. models and products).

OpenAI’s revenue sharing with Microsoft will end in 2030, is subject to a total cap, and is no longer dependent on its achieving artificial general intelligence.

Amazon, a likely beneficiary of this lack of exclusivity, initially popped on the news but erased those gains.

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China just blew up one of Meta’s key AI bets

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Unlike its tech peers, which can sell AI through cloud services, Meta mainly uses AI to improve its existing ad business rather than as a stand-alone revenue driver. The decision strips away one of Meta’s clearest paths to monetizing AI — leaving it spending like a hyperscaler, without a hyperscaler business model.

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DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

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