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Using Living Neurons to Power AI
How FinalSpark is creating biocomputers that are one million times more efficient than digital
- September 29, 2025
Imagine AI running not on silicone, but on biology. Our latest Energy Superhero, neuroscientist Dr. Ewelina Kurtys, is helping build a biocomputer using living neurons, the same building blocks as the human brain. The goal? Energy efficiency. Working at startup FinalSpark, Dr. Kurtys and her team are solving one of the greatest challenges of our day: the massive energy consumption of artificial intelligence. Dr. Kurtys and the Final Spark team’s biologically-based systems could completely revolutionize how we think about computing, considering neurons are up to one million times more energy efficient than current digital hardware.
In this episode, Dr. Kurtys discusses the groundbreaking work of FinalSpark and the potential impact on the future of energy and AI:
- Dr. Kurtys’ vast experience spans neuroscience, brain imaging, biocomputing, and more. She graduated with degrees in pharmacy and biotechnology in Poland, completed international research projects in pharmacology and microbiology, and obtained a PhD in neuroscience and brain imaging in the Netherlands.
- FinalSpark’s technology takes advantage of the radical efficiency of biological systems compared to digital. While a human brain can run all day on the energy equivalent of a banana, simulating a brain on digital computers would require the power output of a small nuclear plant. Living neurons are much more efficient and process information in a totally different way than digital counterparts. Biocomputing has incredible potential to decouple the growth of AI from unsustainable increases in energy demand.
- Dr. Kurtys says there are significant challenges, primarily the difficulty of “programming” neurons. Unlike digital systems, we do not yet fully understand how neurons encode information. The team uses a trial-and-error approach, stimulating neurons and analyzing their complex electrical signals (spikes) to learn how to influence their behavior. Looking forward, FinalSpark hopes to achieve controlled learning in a lab setting and ultimately scale the technology to create a fully functional biocomputer.
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