EP 37: Neurons: Future of AI Processing

What if the next generation of computers wasn't made of silicon — but of living human neurons? Not simulated neurons, not artificial neural networks inspired by biology, but actual brain cells grown in a lab, connected to electrodes, and used to process information. That's not science fiction anymore. It's happening right now at FinalSpark, a Swiss startup building the world's first remotely accessible biocomputing platform. In this episode, Sam talks with Dr. Ewelina Kurtys, a neuroscientist with a PhD in brain imaging and a postdoctoral researcher at King's College London, about how living neurons could revolutionise computing — and why they use one million times less energy than silicon-based AI hardware.   ▸  WHAT YOU'LL LEARN ▪  How FinalSpark was founded in 2014 by Fred Jordan and Martin Kutter — and why they pivoted from digital AI to biological computing when they realised the energy and cost problem was unsolvable with silicon ▪  Why 20 watts powers the human brain while silicon-based AI requires megawatts — and what that means for AI's sustainability crisis ▪  The difference between neurons as processors (not power sources) — a crucial distinction most people get wrong ▪  Why biological neural networks learn continuously while digital systems require full model updates — and what that means for energy efficiency ▪  The honest challenge: nobody yet knows exactly how neurons encode information — the biggest scientific hurdle in biocomputing right now ▪  How the I/O interface works: electrodes measuring neural spikes, analog-to-digital converters, researchers writing Python code to control neurons remotely ▪  The remote access breakthrough: researchers in Tokyo or Bristol can log in and control living neurons in Switzerland in real time via browser ▪  Why neurons won't outperform GPUs on speed: biocomputing specialises in efficiency and adaptability, not clock cycles ▪  FinalSpark's current stage: they've stored 1 bit of information and are collaborating with 9 universities on fundamental research ▪  The cost argument: even at 10× lower price than NVIDIA, biocomputers would still generate billions in profit due to energy and infrastructure savings ▪  Bioethics, consent, and regulation: how FinalSpark is working with philosophers now to establish ethical frameworks before biocomputing scales ▪  Why human-machine integration is not new: prosthetics, pacemakers, and smartphones are already blending biology and technology ▪  The hybrid computing future: silicon, quantum, and biocomputing will coexist, each doing what they do best ▪  The real game-changer: cheap, accessible AI for everyone — Ewelina's vision for what biocomputing means for society in 10–20 years.   ▸  LINKS MENTIONED IN THIS EPISODE →  Dr. Ewelina Kurtys on LinkedIn →  Ewelina's Personal Blog & Articles →  FinalSpark (official website) →  FinalSpark Neuroplatform (with live neuron view) →  FinalSpark Team →  Psync (Ewelina's mental wellness startup) →  FinalSpark Contact Form