Neuroscience

State of the Art of Biological Computing • Ewelina Kurtys & Charles Humble • GOTO 2026

State of the Art of Biological Computing • Ewelina Kurtys & Charles Humble • GOTO 2026

Dr. Ewelina Kurtys of FinalSpark discusses the ambitious goal of building computers from living neurons, aiming for a 1-million-fold increase in energy efficiency over digital systems. The conversation delves into the technical challenges of neural encoding and plasticity, the use of brain organoids, and the profound ethical and philosophical questions surrounding determinism and consciousness in biological hardware.

Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Professor Mazviita Chirimuuta discusses the philosophical underpinnings of neuroscience, challenging the brain-as-computer metaphor. She introduces 'haptic realism'—a view of knowledge as interactive and constructed—and argues for the inseparability of embodiment, finitude, and true understanding in both humans and AI.

Why Every Brain Metaphor in History Has Been Wrong [SPECIAL EDITION]

Why Every Brain Metaphor in History Has Been Wrong [SPECIAL EDITION]

An exploration of scientific simplification, questioning the metaphors we use to understand the brain and intelligence. This summary delves into the tension between creating useful models and mistaking them for reality, featuring insights on the mind-as-software debate, the limits of prediction versus understanding, and the philosophical underpinnings of our quest for AGI.

929: Dragon Hatchling: The Missing Link Between Transformers and the Brain — with Adrian Kosowski

929: Dragon Hatchling: The Missing Link Between Transformers and the Brain — with Adrian Kosowski

Adrian Kosowski from Pathway introduces the Baby Dragon Hatchling (BDH), a groundbreaking, post-transformer architecture inspired by neuroscience. BDH leverages sparse, positive activation to mimic brain function, offering a path to limitless context, superior reasoning, and unprecedented computational efficiency, potentially solving key limitations of current large language models.

Human Neurons are 1M x Energy Efficient than Digital AI Processors | Dr. Ewelina Kurtys | FinalSpark

Human Neurons are 1M x Energy Efficient than Digital AI Processors | Dr. Ewelina Kurtys | FinalSpark

Dr. Ewelina Kurtys of FinalSpark explains their pioneering work in building biocomputers from living human neurons, which are up to one million times more energy-efficient than traditional silicon chips. The conversation covers the technology of reprogramming skin cells into neurons, the company's growth strategy, and the profound ethical and philosophical questions, such as potential 'Matrix' scenarios, that arise from merging biology with AI.

912: In Case You Missed It in July 2025  — with Jon Krohn (@JonKrohnLearns)

912: In Case You Missed It in July 2025 — with Jon Krohn (@JonKrohnLearns)

A review of five key interviews covering the importance of data-centric AI (DMLR) in specialized fields like law, the challenges of AI benchmarking, strategies for domain-specific model selection using red teaming, the power of AI in predicting human behavior, and the shift towards building causal AI models.