Những podcast Machine Learning Street Talk Mlst hay nhất (2025)

1
ARC Prize v2 Launch! (Francois Chollet and Mike Knoop) 54:15

23h ago54:15

54:15

We are joined by Francois Chollet and Mike Knoop, to launch the new version of the ARC prize! In version 2, the challenges have been calibrated with humans such that at least 2 humans could solve each task in a reasonable task, but also adversarially selected so that frontier reasoning models can't solve them. The best LLMs today get negligible per…

1
Test-Time Adaptation: the key to reasoning with DL (Mohamed Osman) 1:03:36

3d ago1:03:36

1:03:36

Mohamed Osman joins to discuss MindsAI's highest scoring entry to the ARC challenge 2024 and the paradigm of test-time fine-tuning. They explore how the team, now part of Tufa Labs in Zurich, achieved state-of-the-art results using a combination of pre-training techniques, a unique meta-learning strategy, and an ensemble voting mechanism. Mohamed e…

1
GSMSymbolic paper - Iman Mirzadeh (Apple) 1:11:23

6d ago1:11:23

1:11:23

Iman Mirzadeh from Apple, who recently published the GSM-Symbolic paper discusses the crucial distinction between intelligence and achievement in AI systems. He critiques current AI research methodologies, highlighting the limitations of Large Language Models (LLMs) in reasoning and knowledge representation. SPONSOR MESSAGES: *** Tufa AI Labs is a …

1
Reasoning, Robustness, and Human Feedback in AI - Max Bartolo (Cohere) 1:23:11

7d ago1:23:11

1:23:11

Dr. Max Bartolo from Cohere discusses machine learning model development, evaluation, and robustness. Key topics include model reasoning, the DynaBench platform for dynamic benchmarking, data-centric AI development, model training challenges, and the limitations of human feedback mechanisms. The conversation also covers technical aspects like influ…

1
Tau Language: The Software Synthesis Future (sponsored) 1:41:19

13d ago1:41:19

1:41:19

This sponsored episode features mathematician Ohad Asor discussing logical approaches to AI, focusing on the limitations of machine learning and introducing the Tau language for software development and blockchain tech. Asor argues that machine learning cannot guarantee correctness. Tau allows logical specification of software requirements, automat…

1
John Palazza - Vice President of Global Sales @ CentML ( sponsored) 54:50

15d ago54:50

54:50

John Palazza from CentML joins us in this sponsored interview to discuss the critical importance of infrastructure optimization in the age of Large Language Models and Generative AI. We explore how enterprises can transition from the innovation phase to production and scale, highlighting the significance of efficient GPU utilization and cost manage…

1
Transformers Need Glasses! - Federico Barbero 1:00:54

17d ago1:00:54

1:00:54

Federico Barbero (DeepMind/Oxford) is the lead author of "Transformers Need Glasses!". Have you ever wondered why LLMs struggle with seemingly simple tasks like counting or copying long strings of text? We break down the theoretical reasons behind these failures, revealing architectural bottlenecks and the challenges of maintaining information fide…

1
Sakana AI - Chris Lu, Robert Tjarko Lange, Cong Lu 1:37:54

25d ago1:37:54

1:37:54

We speak with Sakana AI, who are building nature-inspired methods that could fundamentally transform how we develop AI systems. The guests include Chris Lu, a researcher who recently completed his DPhil at Oxford University under Prof. Jakob Foerster's supervision, where he focused on meta-learning and multi-agent systems. Chris is the first author…

1
Clement Bonnet - Can Latent Program Networks Solve Abstract Reasoning? 51:26

1M ago51:26

51:26

Clement Bonnet discusses his novel approach to the ARC (Abstraction and Reasoning Corpus) challenge. Unlike approaches that rely on fine-tuning LLMs or generating samples at inference time, Clement's method encodes input-output pairs into a latent space, optimizes this representation with a search algorithm, and decodes outputs for new inputs. This…

1
Prof. Jakob Foerster - ImageNet Moment for Reinforcement Learning? 53:31

1M ago53:31

53:31

Prof. Jakob Foerster, a leading AI researcher at Oxford University and Meta, and Chris Lu, a researcher at OpenAI -- they explain how AI is moving beyond just mimicking human behaviour to creating truly intelligent agents that can learn and solve problems on their own. Foerster champions open-source AI for responsible, decentralised development. He…

1
Daniel Franzen & Jan Disselhoff - ARC Prize 2024 winners 1:09:04

1M ago1:09:04

1:09:04

Daniel Franzen and Jan Disselhoff, the "ARChitects" are the official winners of the ARC Prize 2024. Filmed at Tufa Labs in Zurich - they revealed how they achieved a remarkable 53.5% accuracy by creatively utilising large language models (LLMs) in new ways. Discover their innovative techniques, including depth-first search for token selection, test…

1
Sepp Hochreiter - LSTM: The Comeback Story? 1:07:01

1M ago1:07:01

1:07:01

Sepp Hochreiter, the inventor of LSTM (Long Short-Term Memory) networks – a foundational technology in AI. Sepp discusses his journey, the origins of LSTM, and why he believes his latest work, XLSTM, could be the next big thing in AI, particularly for applications like robotics and industrial simulation. He also shares his controversial perspective…

1
Want to Understand Neural Networks? Think Elastic Origami! - Prof. Randall Balestriero 1:18:10

2M ago1:18:10

1:18:10

Professor Randall Balestriero joins us to discuss neural network geometry, spline theory, and emerging phenomena in deep learning, based on research presented at ICML. Topics include the delayed emergence of adversarial robustness in neural networks ("grokking"), geometric interpretations of neural networks via spline theory, and challenges in reco…

1
Nicholas Carlini (Google DeepMind) 1:21:15

2M ago1:21:15

1:21:15

Nicholas Carlini from Google DeepMind offers his view of AI security, emergent LLM capabilities, and his groundbreaking model-stealing research. He reveals how LLMs can unexpectedly excel at tasks like chess and discusses the security pitfalls of LLM-generated code. SPONSOR MESSAGES: *** CentML offers competitive pricing for GenAI model deployment,…

1
Subbarao Kambhampati - Do o1 models search? 1:32:13

2M ago1:32:13

1:32:13

Join Prof. Subbarao Kambhampati and host Tim Scarfe for a deep dive into OpenAI's O1 model and the future of AI reasoning systems. * How O1 likely uses reinforcement learning similar to AlphaGo, with hidden reasoning tokens that users pay for but never see * The evolution from traditional Large Language Models to more sophisticated reasoning system…

1
How Do AI Models Actually Think? - Laura Ruis 1:18:01

2M ago1:18:01

1:18:01

Laura Ruis, a PhD student at University College London and researcher at Cohere, explains her groundbreaking research into how large language models (LLMs) perform reasoning tasks, the fundamental mechanisms underlying LLM reasoning capabilities, and whether these models primarily rely on retrieval or develop procedural knowledge. SPONSOR MESSAGES:…

1
Jurgen Schmidhuber on Humans co-existing with AIs 1:12:50

2M ago1:12:50

1:12:50

Jürgen Schmidhuber, the father of generative AI, challenges current AI narratives, revealing that early deep learning work is in his opinion misattributed, where it actually originated in Ukraine and Japan. He discusses his early work on linear transformers and artificial curiosity which preceded modern developments, shares his expansive vision of …

1
Yoshua Bengio - Designing out Agency for Safe AI 1:41:53

2M ago1:41:53

1:41:53

Professor Yoshua Bengio is a pioneer in deep learning and Turing Award winner. Bengio talks about AI safety, why goal-seeking “agentic” AIs might be dangerous, and his vision for building powerful AI tools without giving them agency. Topics include reward tampering risks, instrumental convergence, global AI governance, and how non-agent AIs could r…

1
Francois Chollet - ARC reflections - NeurIPS 2024 1:26:46

3M ago1:26:46

1:26:46

François Chollet discusses the outcomes of the ARC-AGI (Abstraction and Reasoning Corpus) Prize competition in 2024, where accuracy rose from 33% to 55.5% on a private evaluation set. SPONSOR MESSAGES: *** CentML offers competitive pricing for GenAI model deployment, with flexible options to suit a wide range of models, from small to large-scale de…

1
Jeff Clune - Agent AI Needs Darwin 2:00:13

3M ago2:00:13

2:00:13

AI professor Jeff Clune ruminates on open-ended evolutionary algorithms—systems designed to generate novel and interesting outcomes forever. Drawing inspiration from nature’s boundless creativity, Clune and his collaborators aim to build “Darwin Complete” search spaces, where any computable environment can be simulated. By harnessing the power of l…

1
Neel Nanda - Mechanistic Interpretability (Sparse Autoencoders) 3:42:36

4M ago3:42:36

3:42:36

Neel Nanda, a senior research scientist at Google DeepMind, leads their mechanistic interpretability team. In this extensive interview, he discusses his work trying to understand how neural networks function internally. At just 25 years old, Nanda has quickly become a prominent voice in AI research after completing his pure mathematics degree at Ca…

1
Jonas Hübotter (ETH) - Test Time Inference 1:45:56

4M ago1:45:56

1:45:56

Jonas Hübotter, PhD student at ETH Zurich's Institute for Machine Learning, discusses his groundbreaking research on test-time computation and local learning. He demonstrates how smaller models can outperform larger ones by 30x through strategic test-time computation and introduces a novel paradigm combining inductive and transductive learning appr…

1
How AI Could Be A Mathematician's Co-Pilot by 2026 (Prof. Swarat Chaudhuri) 1:44:42

4M ago1:44:42

1:44:42

Professor Swarat Chaudhuri from the University of Texas at Austin and visiting researcher at Google DeepMind discusses breakthroughs in AI reasoning, theorem proving, and mathematical discovery. Chaudhuri explains his groundbreaking work on COPRA (a GPT-based prover agent), shares insights on neurosymbolic approaches to AI. Professor Swarat Chaudhu…

1
Nora Belrose - AI Development, Safety, and Meaning 2:29:50

4M ago2:29:50

2:29:50

Nora Belrose, Head of Interpretability Research at EleutherAI, discusses critical challenges in AI safety and development. The conversation begins with her technical work on concept erasure in neural networks through LEACE (LEAst-squares Concept Erasure), while highlighting how neural networks' progression from simple to complex learning patterns c…

1
Why Your GPUs are underutilised for AI - CentML CEO Explains 2:08:40

4M ago2:08:40

2:08:40

Prof. Gennady Pekhimenko (CEO of CentML, UofT) joins us in this *sponsored episode* to dive deep into AI system optimization and enterprise implementation. From NVIDIA's technical leadership model to the rise of open-source AI, Pekhimenko shares insights on bridging the gap between academic research and industrial applications. Learn about "dark si…

1
Eliezer Yudkowsky and Stephen Wolfram on AI X-risk 4:18:30

4M ago4:18:30

4:18:30

Eliezer Yudkowsky and Stephen Wolfram discuss artificial intelligence and its potential existen‑ tial risks. They traversed fundamental questions about AI safety, consciousness, computational irreducibility, and the nature of intelligence. The discourse centered on Yudkowsky’s argument that advanced AI systems pose an existential threat to humanity…

1
Pattern Recognition vs True Intelligence - Francois Chollet 2:42:54

5M ago2:42:54

2:42:54

Francois Chollet, a prominent AI expert and creator of ARC-AGI, discusses intelligence, consciousness, and artificial intelligence. Chollet explains that real intelligence isn't about memorizing information or having lots of knowledge - it's about being able to handle new situations effectively. This is why he believes current large language models…

1
The Elegant Math Behind Machine Learning - Anil Ananthaswamy 1:53:11

5M ago1:53:11

1:53:11

Anil Ananthaswamy is an award-winning science writer and former staff writer and deputy news editor for the London-based New Scientist magazine. Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumor is cancerous, or deciding if someone gets bail. They now influence developments and…

1
Michael Levin - Why Intelligence Isn't Limited To Brains. 1:03:35

5M ago1:03:35

1:03:35

Professor Michael Levin explores the revolutionary concept of diverse intelligence, demonstrating how cognitive capabilities extend far beyond traditional brain-based intelligence. Drawing from his groundbreaking research, he explains how even simple biological systems like gene regulatory networks exhibit learning, memory, and problem-solving abil…

1
Speechmatics CTO - Next-Generation Speech Recognition 1:46:23

5M ago1:46:23

1:46:23

Will Williams is CTO of Speechmatics in Cambridge. In this sponsored episode - he shares deep technical insights into modern speech recognition technology and system architecture. The episode covers several key technical areas: * Speechmatics' hybrid approach to ASR, which focusses on unsupervised learning methods, achieving comparable results with…

1
Dr. Sanjeev Namjoshi - Active Inference 2:45:32

5M ago2:45:32

2:45:32

Dr. Sanjeev Namjoshi, a machine learning engineer who recently submitted a book on Active Inference to MIT Press, discusses the theoretical foundations and practical applications of Active Inference, the Free Energy Principle (FEP), and Bayesian mechanics. He explains how these frameworks describe how biological and artificial systems maintain stab…

1
Joscha Bach - Why Your Thoughts Aren't Yours. 1:52:45

5M ago1:52:45

1:52:45

Dr. Joscha Bach discusses advanced AI, consciousness, and cognitive modeling. He presents consciousness as a virtual property emerging from self-organizing software patterns, challenging panpsychism and materialism. Bach introduces "Cyberanima," reinterpreting animism through information processing, viewing spirits as self-organizing software agent…

1
Decompiling Dreams: A New Approach to ARC? - Alessandro Palmarini 51:34

5M ago51:34

51:34

Alessandro Palmarini is a post-baccalaureate researcher at the Santa Fe Institute working under the supervision of Melanie Mitchell. He completed his undergraduate degree in Artificial Intelligence and Computer Science at the University of Edinburgh. Palmarini's current research focuses on developing AI systems that can efficiently acquire new skil…

1
It's Not About Scale, It's About Abstraction - Francois Chollet 46:21

5M ago46:21

46:21

François Chollet discusses the limitations of Large Language Models (LLMs) and proposes a new approach to advancing artificial intelligence. He argues that current AI systems excel at pattern recognition but struggle with logical reasoning and true generalization. This was Chollet's keynote talk at AGI-24, filmed in high-quality. We will be releasi…

1
Bold AI Predictions From Cohere Co-founder 47:17

6M ago47:17

47:17

Ivan Zhang, co-founder of Cohere, discusses the company's enterprise-focused AI solutions. He explains Cohere's early emphasis on embedding technology and training models for secure environments. Zhang highlights their implementation of Retrieval-Augmented Generation in healthcare, significantly reducing doctor preparation time. He explores the shi…

1
Open-Ended AI: The Key to Superhuman Intelligence? - Prof. Tim Rocktäschel 55:10

6M ago55:10

55:10

Prof. Tim Rocktäschel, AI researcher at UCL and Google DeepMind, talks about open-ended AI systems. These systems aim to keep learning and improving on their own, like evolution does in nature. Ad: Are you a hardcore ML engineer who wants to work for Daniel Cahn at SlingshotAI building AI for mental health? Give him an email! - danielc@slingshot.xy…

1
Ben Goertzel on "Superintelligence" 1:37:18

6M ago1:37:18

1:37:18

Ben Goertzel discusses AGI development, transhumanism, and the potential societal impacts of superintelligent AI. He predicts human-level AGI by 2029 and argues that the transition to superintelligence could happen within a few years after. Goertzel explores the challenges of AI regulation, the limitations of current language models, and the need f…

1
Taming Silicon Valley - Prof. Gary Marcus 1:56:55

6M ago1:56:55

1:56:55

AI expert Prof. Gary Marcus doesn't mince words about today's artificial intelligence. He argues that despite the buzz, chatbots like ChatGPT aren't as smart as they seem and could cause real problems if we're not careful. Marcus is worried about tech companies putting profits before people. He thinks AI could make fake news and privacy issues even…

1
Prof. Mark Solms - The Hidden Spring 1:26:45

6M ago1:26:45

1:26:45

Prof. Mark Solms, a neuroscientist and psychoanalyst, discusses his groundbreaking work on consciousness, challenging conventional cortex-centric views and emphasizing the role of brainstem structures in generating consciousness and affect. MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without …

1
Patrick Lewis (Cohere) - Retrieval Augmented Generation 1:13:46

6M ago1:13:46

1:13:46

Dr. Patrick Lewis, who coined the term RAG (Retrieval Augmented Generation) and now works at Cohere, discusses the evolution of language models, RAG systems, and challenges in AI evaluation. MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases or the recent extortionate price h…

1
Ashley Edwards - Genie Paper (DeepMind/Runway) 25:04

6M ago25:04

25:04

Ashley Edwards, who was working at DeepMind when she co-authored the Genie paper and is now at Runway, covered several key aspects of the Genie AI system and its applications in video generation, robotics, and game creation. MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases …

1
Cohere's SVP Technology - Saurabh Baji 1:30:25

6M ago1:30:25

1:30:25

Saurabh Baji discusses Cohere's approach to developing and deploying large language models (LLMs) for enterprise use. * Cohere focuses on pragmatic, efficient models tailored for business applications rather than pursuing the largest possible models. * They offer flexible deployment options, from cloud services to on-premises installations, to meet…

1
David Hanson's Vision for Sentient Robots 53:14

7M ago53:14

53:14

David Hanson, CEO of Hanson Robotics and creator of the humanoid robot Sofia, explores the intersection of artificial intelligence, ethics, and human potential. In this thought-provoking interview, Hanson discusses his vision for developing AI systems that embody the best aspects of humanity while pushing beyond our current limitations, aiming to a…

1
The Fabric of Knowledge - David Spivak 46:28

7M ago46:28

46:28

David Spivak, a mathematician known for his work in category theory, discusses a wide range of topics related to intelligence, creativity, and the nature of knowledge. He explains category theory in simple terms and explores how it relates to understanding complex systems and relationships. MLST is sponsored by Brave: The Brave Search API covers ov…

1
Jürgen Schmidhuber - Neural and Non-Neural AI, Reasoning, Transformers, and LSTMs 1:39:39

7M ago1:39:39

1:39:39

Jürgen Schmidhuber, the father of generative AI shares his groundbreaking work in deep learning and artificial intelligence. In this exclusive interview, he discusses the history of AI, some of his contributions to the field, and his vision for the future of intelligent machines. Schmidhuber offers unique insights into the exponential growth of tec…

1
"AI should NOT be regulated at all!" - Prof. Pedro Domingos 2:12:15

7M ago2:12:15

2:12:15

Professor Pedro Domingos, is an AI researcher and professor of computer science. He expresses skepticism about current AI regulation efforts and argues for faster AI development rather than slowing it down. He also discusses the need for new innovations to fulfil the promises of current AI techniques. MLST is sponsored by Brave: The Brave Search AP…

1
Adversarial Examples and Data Modelling - Andrew Ilyas (MIT) 1:28:00

7M ago1:28:00

1:28:00

Andrew Ilyas, a PhD student at MIT who is about to start as a professor at CMU. We discuss Data modeling and understanding how datasets influence model predictions, Adversarial examples in machine learning and why they occur, Robustness in machine learning models, Black box attacks on machine learning systems, Biases in data collection and dataset …

1
Joscha Bach - AGI24 Keynote (Cyberanimism) 57:21

7M ago57:21

57:21

Dr. Joscha Bach introduces a surprising idea called "cyber animism" in his AGI-24 talk - the notion that nature might be full of self-organizing software agents, similar to the spirits in ancient belief systems. Bach suggests that consciousness could be a kind of software running on our brains, and wonders if similar "programs" might exist in plant…

1
Gary Marcus' keynote at AGI-24 1:12:16

7M ago1:12:16

1:12:16

Prof Gary Marcus revisited his keynote from AGI-21, noting that many of the issues he highlighted then are still relevant today despite significant advances in AI. MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases or the recent extortionate price hikes on search API access. …

1
Is ChatGPT an N-gram model on steroids? 32:57

7M ago32:57

32:57

DeepMind Research Scientist / MIT scholar Dr. Timothy Nguyen discusses his recent paper on understanding transformers through n-gram statistics. Nguyen explains his approach to analyzing transformer behavior using a kind of "template matching" (N-grams), providing insights into how these models process and predict language. MLST is sponsored by Bra…

Podcast đáng để nghe

Podcast Machine Learning Street Talk Mlst

Podcast đáng để nghe

Hướng dẫn sử dụng nhanh