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In this episode of The CTO Show with Mehmet, Mehmet sits down with Ewelina Kurtys, Strategic Advisor at FinalSpark, to explore one of the most radical frontiers in technology: biological computing powered by living neurons. FinalSpark is building next-generation processors using human neurons instead of silicon, aiming to solve AI’s biggest challenge: energy efficiency and scalability. From AI infrastructure to neuroscience, ethics, and commercialization, this conversation dives deep into what it really takes to move computing beyond chips and into biology. ⸻ About the Guest: Ewelina Kurtys Ewelina Kurtys is a neuroscientist and Strategic Advisor at FinalSpark. With a background spanning academia, startups, and artificial intelligence, she now works at the intersection of AI, hardware, and biology. At FinalSpark, she helps shape the strategy behind building the world’s first remote-access biocomputing platform using living neurons. / ewelinakurtys ⸻ 🔍 Key Takeaways • Why silicon is reaching its physical and economic limits • How living neurons are up to 1 million times more energy efficient than traditional chips • The hidden cost of AI and why current models are unsustainable • How biological processors are programmed and trained • Why biocomputing may reshape AI infrastructure • The ethical and regulatory dimensions of using human cells • Why centralized “bio-servers” may replace traditional data centers • What it takes to commercialize deep science innovation ⸻ 🎯 What You’ll Learn By listening to this episode, you will learn: • How biological computing works in practice • Why AI’s future depends on new hardware paradigms • What makes neurons powerful information processors • How startups can compete with Big Tech through radical innovation • The investment and research timeline behind deep tech breakthroughs • How biocomputing could reduce AI’s carbon footprint • Where philosophy, ethics, and engineering intersect ⸻ ⏱️ Episode Highlights & Timestamps 00:00 – Introduction to biocomputing and FinalSpark 02:00 – Why living neurons beat silicon on efficiency 04:00 – From AI software to biological hardware 06:00 – The real cost of running large AI models 08:00 – How neurons are programmed and trained 10:00 – Using dopamine and chemical signals for learning 12:00 – Sourcing stem cells and neuron lifespan 14:00 – Commercial use cases for bio-computers 15:00 – Why portable bio-AI is unlikely (for now) 17:00 – Climate impact and energy efficiency 18:30 – Open innovation and university partnerships 20:30 – Ethics and public perception 22:00 – Responding to skeptics 23:00 – Is it still “artificial” intelligence? 24:30 – Brain-computer interfaces and future implications 26:00 – The 10-year roadmap and funding plans 27:30 – Advice for young scientists 28:30 – Where to learn more ⸻ 📚 Resources Mentioned • FinalSpark Website: https://finalspark.com • FinalSpark Research Paper (Frontiers): https://www.frontiersin.org/journals/...