Earley AI Podcast
In this podcast hosts Seth Earley invites a broad array of thought leaders and practitioners to talk about what's possible in artificial intelligence as well as what is practical in the space as we move toward a world where AI is embedded in all aspects of our personal and professional lives. They explore what's emerging in technology, data science, and enterprise applications for artificial intelligence and machine learning and how to get from early-stage AI projects to fully mature applications. Seth is founder & CEO of Earley Information Science and the award-winning author of "The AI Powered Enterprise."
Earley AI Podcast
Earley AI Podcast - Episode 97: Biological Computing, Brain-Derived Algorithms, and the Future of AI Efficiency with Alex Ksendzovsky
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Why Making AI More Biological May Be the Most Consequential Development in the History of Computing
Guest: Alex Ksendzovsky, CEO and Co-Founder at The Biological Computing Company
Host: Seth Earley, CEO at Earley Information Science
Published on: August 14, 2026
In this episode, Seth Earley speaks with Alex Ksendzovsky, CEO and Co-Founder of The Biological Computing Company, a neurosurgeon and neuroscientist who spent nearly two decades studying how the brain processes information - including implanting electrodes into human brains to understand epilepsy and growing neurons in a dish to study them at the molecular level. They explore why the AI field diverged sharply from biology in the 1980s and what was left behind, how TBC grows real brain cells on electrode arrays to derive mathematical principles that improve AI algorithms, what a 13-20% improvement in video generation quality and a 4-5x efficiency gain means against an industry where 1-2% counts as significant, and where biological computing is headed in the next decade and beyond. This is one of the most technically ambitious and genuinely novel conversations the podcast has had.
Key Takeaways:
- AI diverged sharply from biology in the 1980s when backpropagation was introduced - it produced highly performant systems but at the cost of massive energy inefficiency that the brain solved hundreds of millions of years ago.
- TBC grows hundreds of thousands of neurons on electrode arrays with 4,096 electrodes, encodes information as electrical patterns, and derives mathematical principles from how those neurons actually process and represent that information.
- The adapter products built from these biological principles plug into existing transformer architectures and produce 13-20% improvements in video quality metrics where a 1-2% improvement is considered publication-worthy.
- On efficiency, TBC's adapters currently produce a 4-5x improvement in frames per second - and when combined with existing optimization strategies, the two approaches are synergistic rather than conflicting.
- The catastrophic forgetting problem - AI's inability to learn continuously without losing what was previously learned - is one TBC is directly attacking by studying how biological synapses change during closed-loop learning and deriving new learning rules from that process.
- The brain is millions of times more efficient than silicon; even capturing a minuscule portion of that through biologically-derived principles has produced gains that suggest the ceiling for this approach is enormous.
- The ethical framework is clear: the cultured neurons used in TBC's experiments are fundamentally different from a brain - lacking the three-dimensional structure, scale, and emergent properties associated with sentience - and TBC actively works with bioethicists to maintain those guardrails.
Insightful Quotes:
"Moving forward past the 1980s into 2026, you have extremely performant AI systems, but they're being trained with brute force and they're extremely inefficient. At TBC, we think the reason for this is because they became extremely non-biological." - Alex Ksendzovsky
"Just making it a tiny, tiny bit more biological reached these massive gains. It's a testament to the complexity of how the brain operates, and the more of these principles and primitives we can derive and apply, the more improvements we'll get in terms of performance and efficiency." - Alex Ksendzovsky
"The gap is not a coincidence. It's a result of hundreds of millions of years of evolution solving the same problems that we are now trying to solve in silicon." - Seth Earley
Tune in to discover why biological computing may be the most consequential and least-understood frontier in AI infrastructure today - and what it means for the energy crisis that is already shaping every data center investment being made.
Links
LinkedIn: https://www.linkedin.com/in/alexander-ksendzovsky-31732711/
Website: https://www.tbc.co
Blog: https://www.tbc.co/blog
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