ÜBER DIESEN PODCAST 🔗
Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship show covers current affairs in AI, cognitive science, neuroscience and philosophy of mind with in-depth analysis. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI, and we touch on all of the main ideas in the field with the hype surgically removed. MLST is run by Tim Scarfe, Ph.D (https://www.linkedin.com/in/ecsquizor/) and features regular appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).
Aktualisierungshäufigkeit:
every 4 days
Durchschnittliche Audiolänge:
91 minutes
Gastinterviews
Hat Sponsoren
Englisch
Vereinigte Staaten
276 Folgen
seit 24. April 2020
episodic
AUDIENCE OF THIS PODCAST 🔗
~68.98% of listeners are from United Kingdom.
🇬🇧
GB
68.98%
🇺🇸
US
15.57%
🇩🇪
DE
3.75%
🇨🇦
CA
1.44%
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FR
1.11%
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SG
0.72%
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NL
0.60%
🇵🇱
PL
0.60%
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IN
0.53%
🇮🇸
IS
0.48%
🇦🇺
AU
0.38%
🇸🇪
SE
0.36%
🇪🇸
ES
0.34%
🇨🇭
CH
0.27%
🇫🇮
FI
0.25%
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CO
0.22%
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HK
0.22%
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IE
0.21%
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BE
0.19%
🇯🇵
JP
0.19%
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BR
0.18%
🇵🇹
PT
0.18%
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NG
0.17%
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VN
0.16%
🇮🇹
IT
0.13%
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AT
0.13%
🇳🇿
NZ
0.13%
🇦🇷
AR
0.12%
🇷🇴
RO
0.12%
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ID
0.12%
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KE
0.10%
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ZA
0.10%
Others
1.95%
* Data source: directly measured on Listen Notes. in Echtzeit
NEUESTE FOLGEN 🔗
Joscha Bach is a cognitive scientist and the founder of the California Institute for Machine Consciousness.
SPONSOR:
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Parallel is a single platform for all your agentic research: web search built for AI agents, with Pareto-optimal quality, cost and speed.
Get started: https://parallel.ai/mlst
-…
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FRÜHERE EPISODEN 🔗
Kevin Hartnett is the author of *The Proof in the Code*.SPONSOR:---Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Applications for Batch 1 are now open.Apply now: https://cyber.fund---In 1998 Thomas Hales finished a proof of the Kepler conjecture that…
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 mutations only need to be useful about 1% of the time for the search to keep making progress.Akarsh is…
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 on reasoning to the best answer. Shawn describes an audio-native model (Dialog-RSN-1) that first pr…
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 free with the Parallel MCP server and $5 of credits every month: https://parallel.ai/mlst?utm_sourc…
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 Zhengyao Jiang what the reported gains over two years of human engineering actually demonstrate.The dis…
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 datasets drawn from a prior over structural causal models, rather than on real data. At prediction …
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, after helping research the Yann LeCun and Randall Balestriero episode on interpolation.
SPONSOR:
---
C…
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, generate one, and produce robot actions.
He walks Tim through the architecture. A vision language mode…
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 models rather than one end-to-end system.
IN PARTNERSHIP WITH MISTRAL AI:
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This episode was produced…
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