Machine Learning Street Talk (MLST)

Tim Scarfe

podcasts33+1e4a0eac@anchor.fm

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Booking Overview

Machine Learning Street Talk (MLST) brings high-caliber voices from AI and related sciences to unpack how models work, why the framing matters, and what safety/governance should actually look like. It’s pitched as rigorous, wide-ranging AI analysis with hype removed—often a good platform for policy- and technical experts who want to go deeper than soundbites.

Metrics

Episodes: 253

Frequency: Irregular

Rating: 4.7/5.0

Estimated listeners: 1k-10k

Gender skew: Male

Location: USA

YouTube: 199.0k subscribers

Contact Information

podcasts33+1e4a0eac@anchor.fm

For verified host and producer emails, sign up to view.

Host

Tim Scarfe - Runs Machine Learning Street Talk (MLST) and holds a Ph.D. The show’s description says MLST engages in in-depth discussions with pre-eminent figures in the AI field, covering current affairs in AI ...

Booking Intelligence

Booking Requirements

high
Typical Credentials:  
Senior AI/ML researchers and/or prominent AI policy and governance figures; typically with major publications/technical contributions (e.g., influential papers) or leadership roles in AI safety/policy organizations and government-adjacent experience.
Required Achievements:  
Author/co-author on widely discussed AI measurement, safety, or core ML research, Leadership role in an AI policy/safety advocacy organization, High-profile academic standing (e.g., described by Science as most influential), Contributions to major AI benchmarks or measurement frameworks

Recent Guest Discussions

Brad Carson - AI Governance And Restraint; Legal/accountability Issues In High-stakes Systems; Transparency And Liability When AI Tools Cause Harm; Defense And Policy Leverage.

Prof. Michael I. Jordan - Collective/economic View Of AI Vs AGI Framing; Actionable Explanations; Alphafold Reliability/error Bars; Prediction-powered Inference; Drug Discovery As Incentive Design; Uncertainty And Conformal Prediction.

David Rein - Time Horizons Evidence On AI Timelines; Methodology Vs Adversarial Selection; Specification/compile Analogy; Reliability And Reliability-reward Hacking Connections; Swe-bench And Benchmark Targeting Pathology.

Beth Barnes - Benchmark Measurement And Construct Validity; METR Time Horizons Methodology And Reliability Framing; Reward Hacking And Monitorability; Extrapolation Risk.

Recent Topics

Artificial Intelligence, Machine Learning, Ai Safety, Ai Policy, Cognitive Science

Episodes

Here's the recent few episodes on
Machine Learning Street Talk (MLST)
:

He won a Nobel here for AlphaFold. Then he left. - John Jumper

June 22, 2026

This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlstProtein folding stalled biology for fifty years. A sequence of amino acids dictates a three-dimensional shape, but reading that shape meant a year and roughly $100,000 of crystallography per structure. Then AlphaFold 2 won CASP14 so decisively the organizers called the problem essentially solved.In this documentary cut, John Jumper, who shared the 2024 Nobel Prize in Chemistry...

When AI Decides You're a Threat — Brad Carson

May 31, 2026

Brad Carson was the Army's General Counsel, served two terms in Congress and was Acting Under Secretary of Defense for Personnel and Readiness. He now heads Americans for Responsible Innovation, the AI-policy advocacy group he co-founded. Keith Duggar spends roughly eighty minutes pushing back.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---Carson's whole case rests ...

Intelligence is collective, not artificial — Prof. Michael I. Jordan (UC Berkeley / Inria)

May 21, 2026

Michael I. Jordan, described by Science magazine as the most influential computer scientist alive, has never thought of himself as an AI researcher. In this conversation he explains why that distinction matters.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---Jordan trained as a statistician and cognitive scientist, and his career has been spent building machine learn...

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