The Neolabs Are a Bet Against Superintelligence<br>FutureSearch is live<br>Research plan half price for your first month<br>Run a forecast →<br>← Back to Research<br>I have been forecasting frontier lab progress for years now. My team was the first to figure out an accurate breakdown of OpenAI's revenue, I called Anthropic's rise to the top lab of 2026 back in January, having tracked its financials on the way up, and we co-authored the AGI timelines behind AI 2027.
So I am increasingly puzzled by people putting billions into these new startups going after AGI. How do they hope to compete, if even Google and Meta and xAI can't keep up?
The standard answer is that these "neolabs", built around famous researchers and enormous checks, have differentiated approaches. Reflection AI is open source, LeCun's AMI is betting against LLMs, Thinking Machines is commercializing B2B early. (David Silver's Ineffable, and Ilya's SSI, are more mysterious.)
This doesn't really explain Discovery Loop. Anthropic and OpenAI are both on the record for trying to automate R&D. It's a core part of the AI 2027 timeline forecast that FutureSearch co-authored, the one that led us to predicting superhuman capabilities around 2031.
My conclusion is that people betting on neolabs do not believe in recursive self-improvement. They are betting against superintelligence, and they think LLMs will plateau, despite every such prediction so far being spectacularly wrong.
It's a funny position for a VC. "Sure, I'll put $1B into this exciting AI startup, founded by this famous AI researcher. But no, I don't expect AI to take off anytime soon." It's not illogical, it's just a narrow space of possible futures: AI is massively disruptive, but only in 10+ years from now, and possibly with different approaches to what we're doing now.
So I forecast all six of the "AGI" companies that have multi-billion-dollar war chests: Safe Superintelligence, Thinking Machines Lab, Reflection AI, David Silver's Ineffable Intelligence, Yann LeCun's AMI Labs, and Discovery Loop (founded this morning). Each name links to a dedicated forecast page I have since written on that lab, carrying the questions this comparative table leaves out: release dates, revenue, and valuations.
LabCompute, end 2028Frontier modelCapital raised, end 2028Senior big-3 hires, Aug 2027Safe Superintelligence
Sutskever · Jun 2024 · ~$8B raised<br>0.65 GW (0.18 to 2.2)<br>Jan 2029 (Mar 2027 to Jun 2034)<br>$21B ($8B to $64B)<br>7 (2 to 20)<br>Thinking Machines
Murati · Feb 2025 · $2B+ raised<br>0.75 GW (0.2 to 1.7)<br>Dec 2030 (Feb 2028 to 2043)<br>$15B ($3B to $60B)<br>23 (10 to 52)<br>Reflection AI
Laskin · Mar 2024 · ~$4.6B raised<br>0.21 GW (0.06 to 0.75)<br>Jun 2029 (Jun 2027 to 2036)<br>$13.5B ($5B to $43B)<br>32 (15 to 68)<br>Ineffable Intelligence
Silver · late 2025 · $1.1B raised<br>0.28 GW (0.06 to 1.2)<br>Jun 2035 (Jun 2029 to 2053)<br>$6.8B ($1B to $30B)<br>15 (6 to 36)<br>Discovery Loop
Dean · Aug 2026 · seed unclosed<br>0.18 GW (0.02 to 1.05)<br>Jun 2036 (Aug 2029 to 2060)<br>$6.5B ($1B to $30B)<br>10 (4 to 24)<br>AMI Labs
LeCun · late 2025 · ~$1B raised<br>0.04 GW (0.01 to 0.25)<br>Dec 2037 (Nov 2029 to 2068)<br>$4.2B ($1B to $21.5B)<br>6 (2 to 16)
This is a bit hard to forecast, which you can see in the very wide confidence intervals. The most interesting lab on the list ships nothing on purpose, so any question that resolves on products or leaderboards fails on SSI. Here, a frontier model means top-5 on a recognized index if the lab releases models, or credibly established as frontier-class by reporting and independent expert assessment if it does not.
Three labs racing for the frontier around 2029 to 2030, and three research bets<br>whose medians sit a decade (!) out.
Unsurprisingly, the capital, compute, and talent at these neolabs is a tiny fraction of OpenAI and Anthropic. The best compute medians on the bench, three-quarters of a gigawatt, sit an order of magnitude below the ten-gigawatt scale OpenAI's Stargate buildout is heading toward, and the best capital medians are about a sixth of OpenAI's latest round alone. If transformative intelligence arrives on the incumbents' timelines, it arrives from the incumbents. The neolabs' chances of being competitive for AGI, the way the race is currently going, are obviously low.
What follows are my summaries of each lab, drawn only from the rationales behind the four questions I asked about all six of them, and weighted toward the timeline I care about most, when each one first has a frontier model. These are not full profiles. Every lab has its own forecast page, linked from its name above, carrying the release dates, revenue, and valuations this bench leaves out.
Safe Superintelligence
SSI is the most credible challenger on every resource gate and the least observable on every output gate, as per the forecasts. It has quietly raised about $8 billion, more than double the figure most coverage carries, counting Nvidia's $5 billion July investment on top of roughly $3 billion across its earlier rounds. The Nvidia deal...