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Liquid AI's Ramin Hasani on liquid neural networks, AI advancement, the race to AGI & more! | E1928

E1928 • Apr 10, 2024 • 64 mins

Liquid AI’s Ramin Hasani joins Jason to discuss the mission and the concept of Liquid AI's liquid neural networks. They dive into liquid neural networks’ applications, transition from theory to execution, their efficiency on small devices, and more!

Key Points

Liquid AI is a company focused on creating efficient and scalable artificial intelligence systems that are rooted in biology and physics, drawing inspiration from the nervous system of the C. elegans worm to invent liquid neural networks which remain adaptable after training.
While current AI systems like GPT-4 are large, parameter-heavy, and fixed after training, Liquid AI's liquid neural networks are smaller, require significantly less computational power, and can continue to adapt and learn from incoming inputs.
Liquid AI's technology aims to understand and deploy AI systems efficiently in society, bridging the gap between statistical models and causal models to create more explainable and controllable AI, with applications across various industries like finance, healthcare, and autonomous driving.

Speakers

Ramin Hasani

Guest • 65%

Jason Calacanis

Host • 34%

Preroll

Guest • 1%

Partners

Chapters

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

Transcript

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