Two hundred thousand human brain cells, grown on a silicon chip, have learned to play the Doom. Not well, mind you. They can spot enemies and shoot them, but can't remember where they've been or plan a route. Reflexes of a gamer, spatial awareness of a goldfish.
Australian biotech Cortical Labs grew the neurons from stem cells, kept them alive in a nutrient bath, and fed the game's video as electrical signals. The neurons fired back patterns mapped to in-game actions. It's a big upgrade from the same team's 2022 DishBrain experiment, which managed Pong. The new CL1 chip houses 800,000 neurons with a six-month lifespan, a Python API, and a $35,000 price tag. The first 115 units ship this year.
Why care? The human brain runs on roughly 20 watts, whilst training a large AI model can consume the output of a small power station. Biology is absurdly efficient, and AI's energy bill is becoming a boardroom problem.
🧐 What's in it for me? Nobody's replacing your laptop with a brain in a jar. But biocomputing could eventually handle specific AI workloads at a fraction of the energy cost. Nearer term, these platforms are already being used for drug testing and disease modelling, potentially reducing reliance on animal trials.
💵 Out of the Lab: Biocomputing is largely pre-revenue and pre-hype, but AI's energy economics are pushing serious money toward biological alternatives.
Cortical Labs, founded by neuroscientist Brett Kagan, has raised $11M and is shipping its first commercial biocomputers this year.
Swiss rival FinalSpark has built a remote biocomputing platform accessible via API, positioning itself as the AWS of wetware.
Neuromorphic chipmaker BrainChip (ASX: BRN) builds silicon that mimics neural architectures and could benefit from the broader brain-inspired computing push.
Until next time, stay curious.
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