"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
Liquid AI co-founder and CEO Ramin Hasani joins Nathan to make a technically grounded case against the idea that scale alone defines the future of AI. Drawing on Liquid’s path from MIT CSAIL work on liquid time-constant networks to Automated Foundation Model Design, he explains why efficient, hardware-aware architectures can look very different from frontier-scale attention models. The conversation centers on device-native foundation models for phones, laptops, cars, and wearables, including Liquid’s open-weight LFM family and production deployments at Shopify and Mercedes-Benz. The stakes are whether useful intelligence can move beyond the data center into local, privacy-sensitive, low-latency applications—and which model and chip companies will own that on-device intelligence layer. For full show notes, links, and references, read the episode page: https://www.cognitiverevolution.ai/intelligence-on-the-edge-liquid-ai-s-ramin-hasani-on-the-search-for-device-native-foundation-models/ [https://www.cognitiverevolution.ai/intelligence-on-the-edge-liquid-ai-s-ramin-hasani-on-the-search-for-device-native-foundation-models/] Mercury: Command is Mercury’s new conversational interface, giving you natural-language access to your finances and helping you take actions within your existing permissions and approval policies. Visit https://mercury.com [https://mercury.com/?utm_source=cognitive_rev&utm_medium=sponsored_podcast&utm_campaign=26q2_brand_campaign] to learn more and apply online in minutes. Sponsor: Claude: Claude by Anthropic is an AI collaborator that understands your workflow and helps you tackle research, writing, coding, and organization with deep context. Get started with Claude and explore Claude Pro at https://claude.ai/tcr [https://claude.ai/tcr] CHAPTERS: (00:00) About the Episode (03:53) Special Sponsor (05:41) Liquid AI origins (22:35) Neurons versus parameters (Part 1) (22:40) Sponsor: Claude (24:32) Neurons versus parameters (Part 2) (30:51) Scaling liquid networks (40:09) Automated model design (52:04) Gating and input dependence (01:01:16) Architecture bias spectrum (01:09:17) Device foundation models (01:18:16) Hardware intelligence layer (01:30:01) Local agent setup (01:36:20) Miniaturizing intelligence limits (01:40:40) Curiosity driven AI future (01:43:45) Episode Outro (01:46:46) Outro PRODUCED BY: https://aipodcast.ing [https://aipodcast.ing] SOCIAL LINKS: Website: https://www.cognitiverevolution.ai [https://www.cognitiverevolution.ai] Twitter (Podcast): https://x.com/cogrev_podcast [https://x.com/cogrev_podcast] Twitter (Nathan): https://x.com/labenz [https://x.com/labenz] LinkedIn: https://linkedin.com/in/nathanlabenz/ [https://linkedin.com/in/nathanlabenz/] Youtube: https://youtube.com/@CognitiveRevolutionPodcast [https://youtube.com/@CognitiveRevolutionPodcast] Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 [https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431] Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk [https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk]
359 episodes
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