Singularity is reading David Silver’s $1.1B raise as a post-LLM swing

r/singularity pushed this story up because David Silver is not just another founder with a large round. He is the DeepMind researcher associated with DQN, AlphaGo, AlphaZero, MuZero, and AlphaStar, which means the post immediately read as more than startup theater. According to TechCrunch, Silver’s new company Ineffable Intelligence has raised $1.1 billion at a $5.1 billion valuation to pursue a model that learns without relying on human data.

The core idea is the part that made the thread stick. TechCrunch says Ineffable wants to build a “superlearner” that acquires knowledge and skills through reinforcement learning and trial-and-error rather than from piles of human-generated examples. That lands directly in Silver’s historical lane. At DeepMind, he worked on systems that learned from experience and defeated top human or computer players in games without being shown human strategies first. Reddit readers read this as a serious attempt to attack the limits of today’s LLM recipe rather than just scale it one more turn.

The financial scale also mattered. The article says the round included Sequoia, Lightspeed, Google, Nvidia, and others, and it places Ineffable inside a broader cluster of London-based labs founded by star researchers leaving established groups. That fed a second conversation in the thread: DeepMind’s alumni network is now functioning as its own startup ecosystem, and some readers see that as a sign that the next wave of high-end AI labs may spin out from research prestige as much as from product traction.

Community discussion split between excitement and concern. Some commenters treated the move as a tragedy for DeepMind because so much of its identity was tied to Silver’s research arc. Others zeroed in on the harder question: if a system learns from its own experience instead of human data, what does alignment or controllability look like? That is why the post traveled. A huge number always gets attention, but this thread kept moving because readers saw a familiar RL figure taking a direct shot at the assumptions underneath the current LLM stack.