We Are Massively Underinvesting in the Human Brain | Dr. Adam Marblestone
New episode with Dr. Adam Marblestone, CEO and co-founder of Convergent Research. Adam is an extraordinary catalyst and accelerant for science: he has influenced or routed billions in funding, he helped start significant companies and scientific subfields, and he is the world’s go-to person for neuroscience roadmapping. This year, the NSF launched a $1.5B X-Labs initiative inspired by the FRO model Adam pioneered. Though he started with neuroscience, today he helps organize scientific endeavors across many fields, including AI, math, biology, climate, astrophysics, and more.Adam proposes that fields like neurotech, whole-brain emulation, cryo, and nanotech are severely limited by capital and coordination — not ideas. Connectomics is a clear case. He argues that mapping the brain's full wiring diagram is the approach most poised-to-scale and still extremely neglected. Costs for a molecularly annotated mouse connectome have come down orders of magnitude, from an estimated $10B to $100M–200M, Adam suggests, with a human connectome perhaps costing around $1B–2B. The cost curve of connectomes is similar to transistors and gene sequencing: once it is low enough, we get extraordinary outcomes for humanity. Near-term applications could pay for it: new drug targets for brain disease, insights for AI development, emulations, and even “control knobs” for mood and focus we haven’t identified yet.In this episode, we go deep on many topics in neurotech and beyond: what the brain can do that computers still can't; what neuroscience could teach AI; how you'd actually map a whole mammal brain; how far today's fly-brain simulations really get toward an upload; what it would take to move mind uploading beyond the fringe or science; where brain-computer interfaces go next; nanotech, reversible cryonics, AI doing its own ML research, and even predictive, agent-based economics. I'm very excited to have Adam on the podcast. Hope you enjoy! Other links to this episode and references below.Sections00:00:00 Introduction00:01:40 What are the grand challenges of neurotech? 00:04:50 What the brain does that computers still can't (on a few bananas a day)00:14:43 The neuroscience overhang: why brains learn from so little data00:26:29 How to record and map the brain: DNA "ticker tape," ultrasound, and the unexplored map00:40:29 Why connectomics is the area most poised to scale00:47:54 How whole-brain connectomics works, end to end00:55:27 Simulating the fly brain: how far does it actually get us?00:57:51 What would it cost to map a mammal's brain?00:59:55 What will be connectomics' ChatGPT moment?01:04:35 What a connectome unlocks: disease, drug targets, and the brain's control knobs01:14:20 Scaling up to the human brain — a faster timeline than expected01:17:34 Mapping activity, and what the fly connectome has revealed01:27:55 What you could build with today's connectome01:35:29 Why uploading may be one of civilization's great cornerstones and transitions01:42:43 Optimistic visions of a future with uploading01:49:12 Beyond neurotech: virtual cells, nanotech, and AI-driven science02:15:29 BCIs today: semi-invasive devices, ultrasound, and what's on the horizon02:22:44 Why science is capital-and coordination-limited, not idea-limitedEpisode Links:YouTube: https://youtu.be/X0B_GWTuEFoSubstack: https://www.juanbenetpodcast.com/p/mapping-the-brain-simulating-it-uploadingLinks From the Podcast EpisodeGuest & OrganizationsAdam Marblestone: https://www.adammarblestone.org/Convergent Research: https://www.convergentresearch.org/Focused Research Organizations: https://www.convergentresearch.org/about-frosResearch Papers & Technical ReferencesPhysical principles for scalable neural recording, Marblestone et al. (2013): https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2013.00137/fullConneconomics: the economics of dense, large-scale, high-resolution neural connectomics, Marblestone et al. (2013): https://www.biorxiv.org/content/10.1101/001214v4Referenced External Papers & Projects:Neural dust: an ultrasonic, low power solution for chronic brain-machine interfaces, Seo et al. (2013): https://arxiv.org/abs/1307.2196A drosophila computational brain model reveals sensorimotor processing, Shiu et al. (2024): https://www.nature.com/articles/s41586-024-07763-9ConnectomeBench: can LLMs proofread the connectome?, Brown et al. (2025): https://arxiv.org/abs/2511.05542E11 Bio — PRISM technology for self-correcting neuron tracing (2025): https://www.e11.bio/blog/prismZAPBench — Zebrafish activity prediction benchmark (Google Research): https://research.google/blog/improving-brain-models-with-zapbench/Connectome-seq: high-throughput mapping of neuronal connectivity at single-synapse resolution via barcode sequencing (2026): https://www.nature.com/articles/s41592-026-03026-9Wellcome: Scaling up connectomics: https://wellcome.org/insights/reports/scaling-connectomicsMICrONS Explorer: A virtual observatory of the cortex: https://www.microns-explorer.org/Decoupled Neural Interfaces using Synthetic Gradients, Jaderberg et al. (2016): https://arxiv.org/abs/1608.05343Neuronal wiring diagram of an adult brain, FlyWire (2024): https://www.nature.com/articles/s41586-024-07558-yAtomically precise mechanosynthesis of carbon structures on hydrogenated Si(100) by inverted-mode STM, CBN Nano (2026) https://arxiv.org/abs/2605.27250Ultrasound imaging of the brain, Aleph Neuro (2026): https://alephneuro.com/blog/ultrasound-brainOpenwater (Mary Lou Jepsen): https://www.openwater.health/Janelia Research Campus: https://www.hhmi.org/research/janeliaJanelia's Danionella bet (2026): https://www.science.org/content/article/how-ai-1-billion-and-transparent-fish-could-transform-neuroscienceNSF X-Labs: https://www.nsf.gov/funding/initiatives/nsf-x-labsEdison Scientific (FutureHouse spinout; "Kosmos"): https://edisonscientific.com/Isomorphic Labs (Max Jaderberg): https://www.isomorphiclabs.com/people/max-jaderberg-phdAI 2027 (Daniel Kokotajlo et al.): https://ai-2027.com/AI 2040: Plan A (Daniel Kokotajlo et al.): https://blog.aifutures.org/p/ai-2040-plan-aBooks & MediaA Brief History of Intelligence - Max Bennett: https://www.harpercollins.com/products/a-brief-history-of-intelligence-max-s-bennettThe Age of Em - Robin Hanson: https://ageofem.com/We Are Legion (We Are Bob) - Dennis E. Taylor: https://www.simonandschuster.com/books/We-Are-Legion-(We-Are-Bob)/Dennis-E-Taylor/Bobiverse/9781668221570The City and the Stars - Arthur C. Clarke: https://www.abebooks.com/first-edition/CITY-STARS-Clarke-Arthur-C-Harcourt/31156927660/bdPermutation City - Greg Egan: https://www.gregegan.net/PERMUTATION/Permutation.htmlMaking Sense of Chaos - J. Doyne Farmer: https://yalebooks.yale.edu/book/9780300283327/making-sense-of-chaos/Pantheon (AMC): https://www.primevideo.com/detail/0JEZES1SSNVQCQHEYC282VFK2WJuan & Protocol LabsJuan Benet on X: https://x.com/juanbenetJuan Benet Podcast: https://juanbenetpodcast.comProtocol Labs: https://pl.xyzPL Neuro: https://plneuro.xyzDisclaimer: https://bit.ly/PodcastDisclaimer
