The funding round, announced Monday (April 27) and co-led by Sequoia Capital and Lightspeed Venture Partners, will help Silver and his company develop a so-called “superlearner.”
“Ineffable is building a system designed to generate knowledge from its own experience,” Lightspeed said on its website. “One that learns not by extrapolating from human examples but by acting in engineering environments and learning from the signals those environments return. The founding bet is that this approach can eventually produce the kind of knowledge currently locked behind human limits: theorems we have not yet proved, scientific frameworks we do not yet have language for.”
In a mission statement on its website, Ineffable predicts the superlearner will “rediscover and then transcend” history’s greatest inventions, like language and science and mathematics.
“If successful, this will represent a scientific breakthrough of comparable magnitude to Darwin: where his law explained all Life, our law will explain and build all Intelligence,” the company said.
Silver was a central figure behind the development of DeepMind’s AlphaGo, the first AI system to defeat a human master at the Chinese game of Go.
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It’s a game that contains a jaw-dropping amount of moves, as PYMNTS wrote at the time: 1 duocennovemnonagintillion, or 10 to the power of 900, a figure greater than the number of subatomic particles thought to exist in the universe.
That victory, Lightspeed said, “proved something the field had argued about for decades: that a system could generate knowledge its architects did not have.”
In other AI news, PYMNTS wrote Monday about rising appetite for agentic commerce, with research showing that nearly half of consumers say they’re interested in letting AI agents handle things like meal planning and grocery shopping.
As demand picks up, payment infrastructure is becoming the crucial layer that guides whether agentic commerce can operate seamlessly and securely.
“Yet most existing systems weren’t designed for this environment. Legacy payment infrastructure, built for human-initiated, linear transactions, struggles to support the high-velocity, cross-platform activity generated by autonomous agents,” PYMNTS added. “These systems often lack the flexibility to process parallel transactions, enforce granular controls or adapt in real time, creating friction when speed and precision matter most.”
