{"podcast":{"title":"Gradient Dissent: Conversations on AI","slug":"gradient-dissent","podcast_index_feed_id":1020509,"rss_url":"https://feeds.captivate.fm/gradient-dissent/","website_url":"https://wandb.ai/site/resources/podcast","image_url":"https://artwork.captivate.fm/25fd1181-b46e-459b-85a5-d397eec4cdcf/JDLDW81K-wlJoAWL7ZnxLdTp.jpg","author":"Lukas Biewald","episode_count":136,"summary":"Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.","last_synced_at":null,"page_url":"https://stenobird.com/podcast/gradient-dissent"},"episode":{"title":"Phil Brown — How IPUs are Advancing Machine Intelligence","slug":"phil-brown-how-ipus-are-advancing-machine-intelligence","published_at":"2021-05-27T19:00:00+00:00","page_url":"https://stenobird.com/podcast/gradient-dissent/phil-brown-how-ipus-are-advancing-machine-intelligence","show_page_url":"https://stenobird.com/podcast/gradient-dissent","url":"https://wandb.ai/site/resources/podcast","audio_url":"https://podcasts.captivate.fm/media/c70e87db-0917-4e43-b75e-d51be76ba1b9/1022858641-wandb-gd-phil-brown.mp3","summary":"Phil shares some of the approaches, like sparsity and low precision, behind the breakthrough performance of Graphcore's Intelligence Processing Units (IPUs). --- Phil Brown leads the Applications team at Graphcore, where they're building high-performance machine learning applications for their Intelligence Processing Units (IPUs), new processors specifically designed for AI compute. Connect with Phil: LinkedIn: https://www.linkedin.com/in/philipsbrown/ Twitter: https://twitter.com/phil_s_brown --- 0:00 Sneak peek, intro 1:44 From computational chemistry to Graphcore 5:16 The simulations behind weather prediction 10:54 Measuring improvement in weather prediction systems 15:35 How high performance computing and ML have different needs 19:00 The potential of sparse training 31:08 IPUs and computer architecture for machine learning 39:10 On performance improvements 44:43 The impacts of increasing computing capability 50:24 The ML chicken and egg problem 52:00 The challenges of converging at scale and bringing hardware to market Links Discussed: Rigging the Lottery: Making All Tickets Winners (Evci et al., 2019): https://arxiv.org/abs/1911.11134 Graphcore MK2 Benchmarks: https://www.graphcore.ai/mk2-benchmarks Check out the transcription and discover more awesome ML projects: http://wandb.me/gd-phil-brown --- Get our podcast on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts​​​ Spotify: http://wandb.me/spotify​​ Google Podcasts: http://wandb.me/google-podcasts​​​ YouTube: http://wandb.me/youtube​​​ Soundcloud: http://wandb.me/soundcloud​​ Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack​​​ Check out our Gallery, which features curated machine learni…","meta_description":"Phil shares some of the approaches, like sparsity and low precision, behind the breakthrough performance of Graphcore's Intelligence Processing Units (IPU…","key_points":[],"chapters":[],"topics":[],"duration_seconds":3430,"processing_state":"failed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/gradient-dissent/episodes/phil-brown-how-ipus-are-advancing-machine-intelligence/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/gradient-dissent/phil-brown-how-ipus-are-advancing-machine-intelligence.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}