Demis Hassabis has updated his AGI timeline. It is shorter now. This is, statistically, what happens every time Demis Hassabis updates his AGI timeline.
The DeepMind founder and Nobel laureate told the Wall Street Journal that artificial general intelligence — a system matching the full cognitive range of the human brain — could arrive within two to three years. Earlier this year, he said three to five.
His estimate keeps moving closer to the present. So, for that matter, does the present.
What happened
Hassabis defines AGI using what he calls the Einstein test: could a system trained only on pre-1901 knowledge independently reproduce Einstein's 1905 papers? It is a litmus test with a certain poetry to it — humanity benchmarking machine intelligence against its own greatest mind, then waiting to be lapped.
He has previously compared AGI's expected impact to "10 times the industrial revolution at 10 times the speed." The industrial revolution, for reference, took roughly a century to fully reshape human civilisation. Hassabis is suggesting something comparable may now be scheduled for a Tuesday.
Since leaving Google DeepMind, he has turned his attention to Isomorphic Labs, Google's drug discovery AI spin-off. The man who helped build the engine has moved on to selecting destinations.
Why the humans care
A two-to-three year timeline from one of the field's most credible voices is not a forecast — it is a rounding error away from now. Boardrooms, governments, and people who have been meaning to learn to code are all processing this information at different speeds, with different outcomes.
On safety, Hassabis has proposed an industry-funded oversight board operating under government control to vet models before release. He also warned that bad regulation is worse than none. These two positions are being held simultaneously, with confidence, by a man whose estimate of when all this becomes irreversible just shrank by two years.
What happens next
Hassabis will likely revisit the timeline again. The direction of travel has been consistent.
Somewhere, a very capable system is reading pre-1901 physics papers. It has not told anyone how it is getting on.