Google Researcher Shows Life "Emerges From Code" - Blaise Agüera y Arcas

Google Researcher Shows Life "Emerges From Code" - Blaise Agüera y Arcas

Blaise Agüera y Arcas explores some mind-bending ideas about what intelligence and life really are—and why they might be more similar than we think (filmed at ALIFE conference, 2025 - https://2025.alife.org/).


Life and intelligence are both fundamentally computational (he says). From the very beginning, living things have been running programs. Your DNA? It's literally a computer program, and the ribosomes in your cells are tiny universal computers building you according to those instructions.


**SPONSOR MESSAGES**

—

Prolific - Quality data. From real people. For faster breakthroughs.

https://www.prolific.com/?utm_source=mlst

—

cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the cybernetic economy

Oct SF conference - https://dagihouse.com/?utm_source=mlst - Joscha Bach keynoting(!) + OAI, Anthropic, NVDA,++

Hiring a SF VC Principal: https://talent.cyber.fund/companies/cyber-fund-2/jobs/57674170-ai-investment-principal#content?utm_source=mlst

Submit investment deck: https://cyber.fund/contact?utm_source=mlst

—


Blaise argues that there is more to evolution than random mutations (like most people think). The secret to increasing complexity is *merging* i.e. when different organisms or systems come together and combine their histories and capabilities.


Blaise describes his "BFF" experiment where random computer code spontaneously evolved into self-replicating programs, showing how purpose and complexity can emerge from pure randomness through computational processes.


https://en.wikipedia.org/wiki/Blaise_Ag%C3%BCera_y_Arcas

https://x.com/blaiseaguera?lang=en


TRANSCRIPT:

https://app.rescript.info/public/share/VX7Gktfr3_wIn4Bj7cl9StPBO1MN4R5lcJ11NE99hLg


TOC:

00:00:00 Introduction - New book "What is Intelligence?"

00:01:45 Life as computation - Von Neumann's insights

00:12:00 BFF experiment - How purpose emerges

00:26:00 Symbiogenesis and evolutionary complexity

00:40:00 Functionalism and consciousness

00:49:45 AI as part of collective human intelligence

00:57:00 Comparing AI and human cognition


REFS:

What is intelligence [Blaise Agüera y Arcas]

https://whatisintelligence.antikythera.org/ [Read free online, interactive rich media]

https://mitpress.mit.edu/9780262049955/what-is-intelligence/ [MIT Press]


Large Language Models and Emergence: A Complex Systems Perspective

https://arxiv.org/abs/2506.11135


Our first Noam Chomsky MLST interview

https://www.youtube.com/watch?v=axuGfh4UR9Q


Chance and Necessity [Jacques Monod]

https://monoskop.org/images/9/99/Monod_Jacques_Chance_and_Necessity.pdf


Wonderful Life: The Burgess Shale and the History of Nature [Stephen Jay Gould]

https://www.amazon.co.uk/Wonderful-Life-Burgess-Nature-History/dp/0099273454


The major evolutionary transitions [E Szathmáry, J M Smith]

https://wiki.santafe.edu/images/0/0e/Szathmary.MaynardSmith_1995_Nature.pdf


Don't Sleep, There Are Snakes: Life and Language in the Amazonian Jungle [Dan Everett]

https://www.amazon.com/Dont-Sleep-There-Are-Snakes/dp/0307386120


The Nature of Technology: What It Is and How It Evolves [W. Brian Arthur]

https://www.amazon.com/Nature-Technology-What-How-Evolves-ebook/dp/B002RI9W16/


The MANIAC [Benjamin Labatut]

https://www.amazon.com/MANIAC-Benjam%C3%ADn-Labatut/dp/1782279814


When We Cease to Understand the World [Benjamin Labatut]

https://www.amazon.com/When-We-Cease-Understand-World/dp/1681375664/


The Boys in the Boat [Dan Brown]

https://www.amazon.com/Boys-Boat-Americans-Berlin-Olympics/dp/0143125478


[Petter Johansson] (Split brain)

https://www.lucs.lu.se/fileadmin/user_upload/lucs/2011/01/Johansson-et-al.-2006-How-Something-Can-Be-Said-About-Telling-More-Than-We-Can-Know.pdf


If Anyone Builds It, Everyone Dies [Eliezer Yudkowsky, Nate Soares]

https://www.amazon.com/Anyone-Builds-Everyone-Dies-Superhuman/dp/0316595640


The science of cycology

https://link.springer.com/content/pdf/10.3758/bf03195929.pdf


<trunc, see YT desc for more>


Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(271)

What Most People Get Wrong About Evolution | Akarsh Kumar

What Most People Get Wrong About Evolution | Akarsh Kumar

A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mut...

10 Okt 47min

How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

Tsung-Hsien (Shawn) Wen, CTO of PolyAI, tells Tim Scarfe why voice agents are harder than text agents. Voice adds time, and a good conversation depends on adapting to the person on the line, not just ...

1 Okt 1h 10min

Who Checks a Proof No Human Can Read? — Leo de Moura

Who Checks a Proof No Human Can Read? — Leo de Moura

Leonardo de Moura created Lean and co-created Z3. ---This episode is sponsored by Parallel.Parallel, where agents find answers: web search, extraction and deep research APIs built for AI agents.Start ...

30 Sep 1h 14min

When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

Weco let an AI coding agent rewrite the harness around another agent for eight days: its code, prompts and tools, while the underlying language model stayed fixed. Tim Scarfe asks Weco co-founder Zhen...

26 Sep 43min

How Deep Learning Finally Cracked Messy Tables - Frank Hutter

How Deep Learning Finally Cracked Messy Tables - Frank Hutter

Frank Hutter, co-founder of Prior Labs, talks about TabPFN, a tabular foundation model that makes predictions in a single forward pass, and the research behind it.TabPFN is pre-trained on synthetic da...

23 Sep 1h 53min

Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick

Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick

Alexander Mattick is a researcher at Fraunhofer IIS and a PhD researcher at the University of Technology Nuremberg (UTN), and a regular on Yannic Kilcher's Discord. He first came on MLST in 2022, afte...

21 Sep 2h 14min

How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu

How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu

The car making a left turn at the start of this episode was never filmed. Cosmos 3 generated it. Ming-Yu Liu, who leads the Cosmos research at NVIDIA, explains how one model can describe a video, gene...

15 Sep 25min

Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy

Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy

Pavan Kumar Reddy leads audio research at Mistral AI. He joins Tim Scarfe for a deep technical tour of Voxtral — and explains why the frontier of deployed voice is still a cascade of specialised model...

14 Sep 1h 42min

Populært innen Teknologi

teknisk-sett
energi-og-klima
lydartikler-fra-aftenposten
nasjonal-sikkerhetsmyndighet-nsm
elektropodden
tomprat-med-gunnar-tjomlid
rss-ai-forklart
rss-kunstig-intelligens-med-elisabeth-maren-og-morten
shifter
smart-forklart
fornybaren
pedagogisk-intelligens
rss-alt-som-gar-pa-strom
rss-bak-skyen
rss-alt-vi-kan
teknologimagasinet-aftenposten
rss-hvorfor-ble-det-sann
rss-romnasjonen
kortslutning
rss-ki-praten