{"podcast":{"title":"Machine Learning Street Talk (MLST)","slug":"machine-learning-street-talk","podcast_index_feed_id":781643,"rss_url":"https://anchor.fm/s/1e4a0eac/podcast/rss","website_url":"https://podcasters.spotify.com/pod/show/machinelearningstreettalk","image_url":"https://d3t3ozftmdmh3i.cloudfront.net/staging/podcast_uploaded_nologo/4981699/4981699-1757416025703-f026fa81b6d04.jpg","author":"Machine Learning Street Talk (MLST)","episode_count":250,"summary":"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/).","last_synced_at":null,"page_url":"https://stenobird.com/podcast/machine-learning-street-talk"},"episode":{"title":"Jürgen Schmidhuber - Neural and Non-Neural AI, Reasoning, Transformers, and LSTMs","slug":"j-rgen-schmidhuber-neural-and-non-neural-ai-reasoning-transformers-and-lstms","published_at":"2024-08-28T17:44:55+00:00","page_url":"https://stenobird.com/podcast/machine-learning-street-talk/j-rgen-schmidhuber-neural-and-non-neural-ai-reasoning-transformers-and-lstms","show_page_url":"https://stenobird.com/podcast/machine-learning-street-talk","url":"https://podcasters.spotify.com/pod/show/machinelearningstreettalk/episodes/Jrgen-Schmidhuber---Neural-and-Non-Neural-AI--Reasoning--Transformers--and-LSTMs-e2nnmjl","audio_url":"https://anchor.fm/s/1e4a0eac/podcast/play/91002933/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2024-7-28%2Fcf47b479-3c88-d4c3-62f1-009ef82e37c6.mp3","summary":"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 technology and the potential impact of AI on humanity and the universe. YT version: https://youtu.be/DP454c1K_vQ 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. Perfect for AI model training and retrieval augmentated generation. Try it now - get 2,000 free queries monthly at http://brave.com/api. TOC 00:00:00 Intro 00:03:38 Reasoning 00:13:09 Potential AI Breakthroughs Reducing Computation Needs 00:20:39 Memorization vs. Generalization in AI 00:25:19 Approach to the ARC Challenge 00:29:10 Perceptions of Chat GPT and AGI 00:58:45 Abstract Principles of Jurgen's Approach 01:04:17 Analogical Reasoning and Compression 01:05:48 Breakthroughs in 1991: the P, the G, and the T in ChatGPT and Generative AI 01:15:50 Use of LSTM in Language Models by Tech Giants 01:21:08 Neural Network Aspect Ratio Theory 01:26:53 Reinforcement Learning Without Explicit Teachers Refs: ★ "Annotated History of Modern AI and Deep Learning" (2022 survey by Schmidhuber): ★ Chain Rule For Backward Credit Assignment (Leibniz, 1676) ★ First Neural Net / Linear Regression / Shallow Learning (Gauss & Legendre, circa 1800) ★ First 20th Century Pioneer of Practical AI (Quevedo, 1914) ★ First Recurrent NN (RNN) Architecture (Lenz, Ising, 1920-1925) ★ AI Theory: Fundamental Limitations of Computation and Computation-Base…","meta_description":"Jürgen Schmidhuber, the father of generative AI shares his groundbreaking work in deep learning and artificial intelligence. In this exclusive interview,…","key_points":[],"chapters":[],"topics":[],"duration_seconds":5979,"processing_state":"processed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/machine-learning-street-talk/episodes/j-rgen-schmidhuber-neural-and-non-neural-ai-reasoning-transformers-and-lstms/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/machine-learning-street-talk/j-rgen-schmidhuber-neural-and-non-neural-ai-reasoning-transformers-and-lstms.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}