Intelligence on the Edge: Liquid AI's Ramin Hasani on the Search for Device-Native Foundation Models
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/
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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
SOCIAL LINKS:
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How a worm could save humanity from bad AI | Ramin Hasani
What if AI could think and adapt like a real brain? TED Fellow and AI scientist Ramin Hasani shares how liquid neural networks — a new, more flexible AI technology inspired by physics and living brains — could transform how we solve complex problems.
Hosted on Acast. See acast.com/privacy for more information.
Liquid AI's Ramin Hasani on liquid neural networks, AI advancement, the race to AGI & more! | E1928
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Todays show:
Liquid AI’s Ramin Hasani joins Jason to discuss the mission and the concept of Liquid AI's liquid neural networks (1:09). They dive into liquid neural networks’ applications (16:07), transition from theory to execution (21:37), their efficiency on small devices (27:30), and more!
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Timestamps:
(0:00) Liquid AI CEO and co-founder Ramin Hasani joins Jason
(1:09) Liquid AI's mission and concept of liquid neural networks
(7:06) LinkedIn Jobs - Post your first job for free at https://linkedin.com/twist
(8:34) Demo of Liquid AI: traditional vs. Liquid neural networks in autonomous driving
(16:07) Practical applications of Liquid AI
(20:07) Eppo. Accelerate your experimentation velocity with Eppo. Visit https://geteppo.com/twist
(21:37) Commercializing worm-inspired AI systems, building a team, and solving problems across various sectors
(27:30) Efficiency of liquid neural networks in compact devices like the Raspberry Pi and the transformative potential of AI modeled after worms.
(34:15) Attio - Head to https://attio.com/twist to get 15% off for your first year.
(35:24) Data ownership in AI and incentivizing data providers
(41:18) Role of AI in real-world applications
(43:57) Societal impact of AI, job displacement, and the optimistic view on AI's potential
(50:25) Explanation of physical models vs statistical models in AI and the challenge of understanding black box AI systems
(57:01) Speculations about AGI's market cap, who might achieve AGI first, and the potential of using AI systems to build various applications
(1:00:12) Comparison between open-source and closed-source models in AI and the trend of open-source moves in the AI industry
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Mentioned on the show:
https://www.raspberrypi.com/products/raspberry-pi-5
https://www.capgemini.com/us-en
https://www.ctc-g.co.jp/en
https://www.accenture.com
https://www.ey.com/en_gl
https://www.cnn.com/videos/media/2024/04/02/the-daily-show-jon-stewart-ai-work-force-jobs-orig.cnn
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Source of C. elegans worm footage:
https://www.youtube.com/watch?v=zjqLwPgLnV0&t=1s
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Follow Ramin:
X: https://twitter.com/ramin_m_h
LinkedIn: https://www.linkedin.com/in/raminhasani
Check out Liquid AI: https://www.liquid.ai
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X: https://twitter.com/Jason
LinkedIn: https://www.linkedin.com/in/jasoncalacanis
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Great 2023 interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland
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