I first heard people seriously discussing the prospect of “running” a brain in silico back in 2023. Their aim was to emulate, or replicate, all the biological processes of a human brain entirely on a computer.
In that same year, the Wellcome Trust released a report on what it would take to map the mouse connectome: all 70 million neurons. They estimated that imaging would cost $200-300 million and that human proofreading, or ensuring that automated traces between neurons were correct, would cost an additional $7-21 billion. Collecting the images would require 20 electron microscopes running continuously, in parallel, for about five years and occupy about 500 petabytes. The report estimated that mapping the full mouse connectome would take up to 17 years of work.
Given this projection — not to mention the added complexity of scaling this to human brains — I remember finding the idea of brain emulation absurd. Without a map of how neurons in the brain connect with each other, any effort to emulate a brain computationally would prove impossible. But after spending the past year researching the possibility (and writing a 175-page report about it), I’ve updated my views. — Read More
Daily Archives: January 27, 2026
The Duelling Rhetoric at the AI Frontier
At Davos 2026, Anthropic CEO Dario Amodei told a room full of the world’s most influential investors that AI would replace “most, maybe all” of what software engineers do within six to twelve months. A few hours later, Google DeepMind CEO Demis Hassabis took the same stage and said current AI systems are “nowhere near” human-level intelligence, and that we probably need “one or two more breakthroughs” before AGI arrives.
Both men run frontier AI labs. Both have access to roughly the same benchmarks, papers, and internal capabilities data. Yet their public forecasts diverge so dramatically that at least one of them must be either wrong or strategically misleading. The interesting question is which, and why. — Read More