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PERSON DIRECTORY

Demis Hassabis

Demis Hassabis appears in 5 indexed conversations across Hard Fork, 20VC, All-In. This directory brings every appearance, source, TL;DR, digest, and transcript into one searchable feed.

5 EPISODES4 SHOWS
3 episodes2 active
Language
Hard ForkEN · 27 min

Google's Gemini 3 Is Here: A Special Early Look

Demis HassabisJosh Woodward

Gemini 3 Pro lifted Humanity’s Last Exam performance from 21.6% to 37.5% and is moving beyond chatbot answers toward software generated on demand, including custom interfaces and an agent under testing.Its availability across Gemini, Search’s AI Mode, and developer products makes distribution and cost-to-performance central, while missing Docs and Gmail integrations, limited agent evidence, cyber risk, and Google’s unchanged five-to-10-year AGI forecast remain key watchpoints.

Lex Fridman PodcastEN · 155 min

Demis Hassabis: Future of AI, Simulating Reality, Physics and Video Games | Lex Fridman Podcast #475

Lex FridmanDemis Hassabis

Demis Hassabis argues that natural systems contain exploitable structure, allowing classical learning to navigate spaces as large as roughly 10^170 Go positions and 10^300 protein structures.Veo 3’s passive observation of liquids, materials, and human dynamics suggests useful intuitive physics, while AlphaEvolve and the virtual-cell roadmap extend model-guided search into science and engineering.Hassabis assigns a 50% chance to AGI within five years, but compute demand, safety research, labor disruption, and whether scaling needs another architectural leap remain important uncertainties.

Hard ForkEN · 74 min

Google DeepMind C.E.O. Demis Hassabis on Living in an A.I. Future | EP 137

Demis Hassabis

Google is shifting Search toward an AI workbench as Gemini reaches 400 million monthly users and AI Mode fans queries across dozens of websites, but its $250 frontier tier has no settled successor to blue-link economics.Demis Hassabis places most AGI probability five to 10 years out, while AlphaEvolve shows how evaluated model proposals can improve code, chip design, scheduling, and matrix multiplication.Agent deployment and controllability are the key unresolved risks as capable systems may emerge in two or three years.