What does it mean to build a mind that is not a copy of our own?

Today, we are excited to announce that Sequoia is partnering with David Silver and Ineffable Intelligence, a new AI research lab based in London with a singular mission: to make first contact with superintelligence.

Ineffable is building what David calls a superlearner: a system that discovers all knowledge directly through its own experience, from elementary motor skills to profound intellectual breakthroughs. No pre-training. No imitation. Just an agent learning endlessly from the consequences of its own actions in a world built to teach it.

A Reinforcement Learning-based superlearner has the potential to rediscover and then transcend the greatest inventions in human history: language, science, mathematics and technology. Imagine a machine that derives the laws of physics from first principles. That invents new branches of mathematics we never thought to ask about. That designs materials, medicines and computers we don’t yet have the vocabulary to describe. This is the prize David is reaching for.

A Different Path

The current generation of AI was built by training on the entirety of the human internet. It is an extraordinary achievement. But a system trained on human data may also have fundamental limitations.

Ineffable Intelligence is scaling reinforcement learning from a clean base: no pre-training, no human data to shortcut the system. Guided by the Era of Experience as a north star, David is proving that agents trained purely from an environment can develop non-human strategies for reasoning about problems we don’t yet know how to solve.

David led some of the defining breakthroughs in deep reinforcement learning, most famously in the devilishly difficult game of Go. Go is the ultimate machine intelligence test because it cannot be brute-forced by a computer: a combinatorially explosive O(10^170) possible legal board positions vastly exceeds the O(10^80) atoms in the observable universe. It was thought to be simply too hard for machines to solve.

At DeepMind, David drove the key breakthrough that finally solved the game of Go: self-play. Self-play drove the ~800 ELO-point leap that led to the historic AlphaGo vs. Lee Sedol showdown in March 2016. David pushed the idea further still with AlphaGo Zero: removing human pre-training entirely and learning purely through self-play increased the system’s ELO rating from ~3,700 to 5,000+. The result was a system that reached decisively superhuman performance, and with somewhat non-human mannerisms.

That’s the lineage David has spent his career building. He was the lead researcher and technical force behind the Alpha series at DeepMind, where, for a brilliant period, his approach was the dominant paradigm: AlphaGo, AlphaZero, AlphaStar, AlphaProof and more.

Even with the arrival of LLMs, David never stopped believing. He is one of the very few people on earth with the conviction, the technical depth and the team to scale reinforcement learning.

What’s Ahead

The work ahead is hard, the timeline to superintelligence is uncertain, and the bet is genuinely contrarian. That is exactly what excites us. The largest leaps in AI have always come from people willing to ignore the consensus. David has ignored more consensus, more correctly, than almost anyone in the field.

We are honored to co-lead Ineffable’s first round and to partner with David on what may be the most ambitious scientific mission of our generation.