This interview was recorded for GOTO State of the Art in January 2026.
https://gotopia.tech

Read the full transcription of this interview here:
https://gotopia.tech/articles/423

Dr. Ewelina Kurtys - Strategic Advisor on Frontier Technologies at FinalSpark
Charles Humble - Freelance Techie, Podcaster, Editor, Author & Consultant

RESOURCES
Ewelina
https://x.com/ewelina_kurtys
https://github.com/ewelinaewela
https://www.linkedin.com/in/ewelinakurtys
https://www.ewelinakurtys.com

Charles
https://bsky.app/profile/charleshumble.bsky.social
https://linkedin.com/in/charleshumble
https://mastodon.social/@charleshumble
https://conissaunce.com

Links
https://finalspark.com
https://www.linkedin.com/pulse/biologically-inspired-computing-dr-ewelina-kurtys-udnhe
https://finalspark.com/finalspark-6-month-research-technology-update
https://finalspark.com/first-publication-from-a-neuroplatform-user

DESCRIPTION
Dr. Ewelina Kurtys, Strategy Advisor at FinalSpark, discusses the revolutionary potential of biological computing with host Charles Humble.

The conversation explores FinalSpark's ambitious goal to build computers using living neurons that are 1 million times more energy efficient than current digital systems. Ewelina explains the technical challenges of working with brain organoids, the ethical considerations of using human stem cells, and why biological neurons could dramatically reduce AI costs while offering unique advantages for complex tasks like generative AI.
The interview covers everything from neural encoding and plasticity to consciousness and the deterministic nature of the brain.

RECOMMENDED BOOKS
Robert M. Sapolsk • Determined • https://amzn.to/4akv2gi
Jin Xu • Biological Computing • https://amzn.to/4a4Wwp9


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An interview with Dr. Ewelina Kurtys, strategy advisor to Final Spark, exploring the frontier of biological computing. Final Spark is building computers from living neurons, claiming they are 1 million times more energy efficient than digital hardware. The conversation covers the current state of their prototypes (organoids of ~10,000 neurons on electrodes), key challenges including neural signal encoding, plasticity-induced experimental variability, and keeping neurons alive (currently ~3 months in lab conditions). The discussion also touches on the potential to dramatically reduce AI inference costs, the 10-year roadmap to a general-purpose biocomputer, ethical questions around consent and consciousness, and how this research could yield medical side-benefits.

State of the Art of Biological Computing • Ewelina Kurtys & Charles Humble