38

01:13:41

Computation, Bayesian Model Selection, Interactive Articles •

This week Dr Keith Duggar, Alex Stenlake and Dr Tim Scarfe discuss the theory of computation, intelligence, Bayesian model selection, the intelligence explosion and the the phenomenon of “interactive articles”.

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41

01:58:02

WelcomeAIOverlords (Zak Jost)

We welcome Zak Jost from the WelcomeAIOverlords channel. Zak is an ML research scientist at Amazon. He has a great blog at http://blog.zakjost.com and also a Discord channel at https://discord.gg/xh2chKX WelcomeAIOverlords: https://www.youtube.com/channel/UCxw9_WYmLqlj5PyXu2AWU_g 00:00:00 INTRO START 00:01:07 MAIN SHOW START 00:01:59 ZAK’S STORY 00:05:06 YOUTUBE DISCUSSION 00:24:12 UNDERSTANDING PAPERS 00:29:53 CONTRASTIVE LEARNING INTRO 00:33:00 BOOTSTRAP YOUR […]

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29

01:16:19

The Social Dilemma Part 3 • Dr Rebecca Roache •

This week we join Dr Tim Scarfe, Yannic Kilcher, and Keith Duggar having a conversation with Dr Rebecca Roache in the last of our 3-part series on the social dilemma Netflix film. Rebecca is a senior lecturer in philosophy at Royal Holloway, university of London and has written extensively about the future of friendship.

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38

01:45:37

The Social Dilemma Part 2 – Abhishek Gupta

This week on Machine Learning Street Talk, Dr. Tim Scarfe, Dr. Keith Duggar, Alex Stenlake and Yannic Kilcher have a conversation with the founder and principal researcher at the Montreal AI Ethics institute — Abhishek Gupta. We cover several topics from the Social Dilemma film and AI Ethics in general. 00:00:00 Introduction 00:03:57 Overcome our […]

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49

01:34:34

UK Algoshambles, Neuralink, GPT-3 and Intelligence

This week Dr. Tim Scarfe, Dr. Keith Duggar and Yannic “Lightspeed” Kilcher respond to the “Algoshambles” exam fiasco in the UK where the government were forced to step in to standardise the grades which were grossly inflated by the schools. The schools and teachers are all paid on metrics related to the grades received by […]

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54

01:23:34

Programming Languages, Software Engineering and Machine Learning

This week Dr. Tim Scarfe, Dr. Keith Duggar, Yannic “Lightspeed” Kilcher have a conversation with Microsoft Senior Software Engineer Sachin Kundu. We speak about programming languages including which our favourites are and functional programming vs OOP. Next we speak about software engineering and the intersection of software engineering and machine learning. We also talk about […]

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65

01:02:33

Facebook Research – Unsupervised Translation of Programming Languages

In this episode of Machine Learning Street Talk Dr. Tim Scarfe, Yannic Kilcher and Connor Shorten spoke with Marie-Anne Lachaux, Baptiste Roziere and Dr. Guillaume Lample from Facebook Research (FAIR) in Paris. They recently released the paper “Unsupervised Translation of Programming Languages” which was an exciting new approach to learned translation of programming languages (learned […]

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71

01:12:52

Jordan Edwards: ML Engineering and DevOps on AzureML

This week we had a super insightful conversation with Jordan Edwards, Principal Program Manager for the AzureML team! Jordan is on the coalface of turning machine learning software engineering into a reality for some of Microsoft’s largest customers. ML DevOps is all about increasing the velocity of- and orchastrating the non-interactive phase of- software deployments […]

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55

01:45:42

Robert Lange on NN Pruning and Collective Intelligence

We speak with Robert Lange! Robert is a PhD student at the Technical University Berlin. His research combines Deep Multi-Agent Reinforcement Learning and Cognitive Science to study the learning dynamics of large collectives. He has a brilliant blog where he distils and explains cutting edge ML research. We spoke about his story, economics, multi-agent RL, […]

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64

01:24:08

Capsule Networks and Education

#machinelearning #deeplearning In today’s episode, Dr. Keith Duggar and Dr. Tim Scarfe chat with Alex Stenlake about the education chapter in Kenneth Stanley’s “Greatness cannot be planned” book, and we relate it to our Algoshambes conversation a few weeks ago. We debate whether objectives in education are a good thing and whether they cause perverse […]

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71

37:31

#48 Machine Learning Security – Andy Smith

First episode in a series we are doing on ML DevOps. Starting with the thing which nobody seems to be talking about enough, security! We chat with cyber security expert Andy Smith about threat modelling and trust boundaries for an ML DevOps system. Intro [00:00:00] ML DevOps – a security perspective [00:00:50] Threat Modelling [00:03:03] […]

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74

01:36:17

Sayak Paul

This week we spoke with Sayak Paul, who is extremely active in the machine learning community. We discussed the AI landscape in India, unsupervised representation learning, data augmentation and contrastive learning, explainability, abstract scene representations and finally pruning and the recent super positions paper. I really enjoyed this conversation and I hope you folks do […]

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75

01:27:00

Kaggle, ML Community / Engineering

Join Dr Tim Scarfe, Sayak Paul, Yannic Kilcher, and Alex Stenlake have a conversation with Mr. Chai Time Data Science; Sanyam Bhutani! 00:00:00 Introduction 00:03:42 Show kick off 00:06:34 How did Sanyam get started into ML 00:07:46 Being a content creator 00:09:01 Can you be self taught without a formal education in ML? 00:22:54 Kaggle […]

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88

02:56:04

#035 Christmas Community Edition!

Welcome to the Christmas special community edition of MLST! We discuss some recent and interesting papers from Pedro Domingos (are NNs kernel machines?), Deepmind (can NNs out-reason symbolic machines?), Anna Rodgers – When BERT Plays The Lottery, All Tickets Are Winning, Prof. Mark Bishop (even causal methods won’t deliver understanding), We also cover our favourite […]

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91

01:25:53

Explainability, Reasoning, Priors and GPT-3

This week Dr. Tim Scarfe and Dr. Keith Duggar discuss Explainability, Reasoning, Priors and GPT-3. We check out Christoph Molnar’s book on intepretability, talk about priors vs experience in NNs, whether NNs are reasoning and also cover articles by Gary Marcus and Walid Saba critiquing deep learning. We finish with a brief discussion of Chollet’s […]

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97

02:39:06

#034 Eray Özkural- AGI, Simulations & Safety

Dr. Eray Ozkural is an AGI researcher from Turkey, he is the founder of Celestial Intellect Cybernetics. Eray is extremely critical of Max Tegmark, Nick Bostrom and MIRI founder Elizier Yodokovsky and their views on AI safety. Eray thinks that these views represent a form of neoludditism and they are capturing valuable research budgets with […]

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98

01:12:57

Exploring Open-Ended Algorithms: POET

Three YouTubers; Tim Scarfe – Machine Learning Dojo (https://www.youtube.com/channel/UCXvHuBMbgJw67i5vrMBBobA), Connor Shorten – Henry AI Labs (https://www.youtube.com/channel/UCHB9VepY6kYvZjj0Bgxnpbw) and Yannic Kilcher (https://www.youtube.com/channel/UCZHmQk67mSJgfCCTn7xBfew). We made a new YouTube channel called Machine Learning Street Talk. Every week we will talk about the latest and greatest in AI. Subscribe now! Special guests this week; Dr. Mathew Salvaris (https://www.linkedin.com/in/drmathewsalvaris/), Eric Craeymeersch […]

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106

01:38:26

Harri Valpola: System 2 AI and Planning in Model-Based Reinforcement Learning

In this episode of Machine Learning Street Talk, Tim Scarfe, Yannic Kilcher and Connor Shorten interviewed Harri Valpola, CEO and Founder of Curious AI. We continued our discussion of System 1 and System 2 thinking in Deep Learning, as well as miscellaneous topics around Model-based Reinforcement Learning. Dr. Valpola describes some of the challenges of […]

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107

01:48:19

#030 Multi-Armed Bandits and Pure-Exploration

This week Dr. Tim Scarfe, Dr. Keith Duggar and Yannic Kilcher discuss multi-arm bandits and pure exploration with Dr. Wouter M. Koolen, Senior Researcher, Machine Learning group, Centrum Wiskunde & Informatica. Wouter specialises in machine learning theory, game theory, information theory, statistics and optimisation. Wouter is currently interested in pure exploration in multi-armed bandit models, […]

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96

01:14:43

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

According to Yann Le Cun, the next big thing in machine learning is unsupervised learning. Self-supervision has changed the entire game in the last few years in deep learning, first transforming the language world with word2vec and BERT — but now it’s turning computer vision upside down. This week Yannic, Connor and I spoke with […]

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102

01:30:36

Sara Hooker – The Hardware Lottery, Sparsity and Fairness

Dr. Tim Scarfe, Yannic Kilcher and Sayak Paul chat with Sara Hooker from the Google Brain team! We discuss her recent hardware lottery paper, pruning / sparsity, bias mitigation and intepretability. The hardware lottery — what causes inertia or friction in the marketplace of ideas? Is there a meritocracy of ideas or do the previous […]

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152

01:40:09

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

In this episode of Machine Learning Street Talk, we chat about Large-scale Transfer Learning in Natural Language Processing. The Text-to-Text Transfer Transformer (T5) model from Google AI does an exhaustive survey of what’s important for Transfer Learning in NLP and what’s not. In this conversation, we go through the key takeaways of the paper, text-to-text […]

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105

52:26

#044 – Data-efficient Image Transformers (Hugo Touvron)

Today we are going to talk about the Data-efficient image Transformers paper or (DeiT) which Hugo is the primary author of. One of the recipes of success for vision models since the DL revolution began has been the availability of large training sets. CNNs have been optimized for almost a decade now, including through extensive […]

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78

01:07:20

The Social Dilemma Part 1 – Andy Smith

In this first part of our three part series on the Social Dilemma Netflix film, Dr. Tim Scarfe, Yannic “Lightspeed” Kilcher and Zak Jost gang up with Cybersecurity expert Andy Smith. We give you our take on the film. We are super excited to get your feedback on this one! Hope you enjoy. 00:00:00 Introduction […]

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