A new artificial intelligence startup, Ineffable Intelligence, is reportedly preparing to raise around $1 billion in its first external funding round. The company is led by David Silver, a well known AI researcher who previously spent more than a decade at DeepMind. Multiple reports suggest the round could be led by Sequoia Capital and may value the London-based startup at roughly $4 billion before new funding is added.
One of the standout projects that Silver played a key role in at DeepMind is AlphaGo, an AI model designed to take on the classic board game Go. This groundbreaking algorithm made waves in 2016 when it triumphed over the world’s top player. Fast forward to 2018, and Silver’s team introduced an enhanced version called AlphaZero, which also excelled at chess and shogi.
Both AlphaGo and AlphaZero were developed using reinforcement learning techniques. Silver was part of a team that applied this same approach to train AlphaStar, an AI model specifically tailored for the video game “StarCraft II.” This algorithm marked a significant achievement in research, as “StarCraft II” presents players with incomplete information about the match, making it a more complex challenge than Go in some ways.
Silver’s exit from Google DeepMind late last year sparked a fierce race among venture firms. Sequoia partners Alfred Lin and Sonya Huang reportedly made a trip to London to meet with him shortly after he left. Major tech players like NVIDIA, Google, and Microsoft are also in discussions to get involved.
At the core of Ineffable Intelligence’s approach is reinforcement learning. It is where AI systems improve by interacting with environments rather than learning only from static datasets. Silver helped pioneer this method at DeepMind, enabling systems to master complex games through self play. This stands in contrast to today’s dominant AI models, which rely heavily on massive amounts of human generated text.
In a paper released last year called “Era of Experience,” Silver and computer scientist Richard Sutton made a compelling case that the next big breakthrough will come from systems that learn mainly through experience. They foresee a transition from relying on human-generated data to agents that improve themselves based on their actions and the feedback they receive from their environment.
Industry observers say the size of the potential raise fits a broader pattern. Elite AI researchers with proven breakthroughs are now attracting unprecedented capital before shipping products. If the round closes, it would underline how fiercely investors are competing for frontier AI talent and how willing they are to back long term scientific ambition over immediate commercial returns.