Tensorflow(@CVision)

AI researcher Jim Fan has had a charmed career. He was OpenAI’s first intern before he did his PhD at Stanford with “godmother of AI,” Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI “GEAR” group. The lab’s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a “foundation agent” that can generalize across skills, embodiments and realities—both physical and virtual. He also supports Jensen Huang’s idea that “Everything that moves will eventually be autonomous.” Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital 00:00 Introduction 01:35 Jim’s journey to embodied intelligence 04:53 The GEAR Group 07:32 Three kinds of data for robotics 10:32 A GPT-3 moment for robotics 16:05 Choosing the humanoid robot form factor 19:37 Specialized generalists 21:59 GR00T gets its own chip 23:35 Eureka and Issac Sim 25:23 Why now for robotics? 28:53 Exploring virtual worlds 36:28 Implications for games 39:13 Is the virtual world in service of the physical world? 42:10 Alternative architectures to Transformers 44:15 Lightning round

Andrew Ng, founder of DeepLearning.AI and AI Fund, speaks at Sequoia Capital's AI Ascent about what's next for AI agentic workflows and their potential to significantly propel AI advancements—perhaps even surpassing the impact of the forthcoming generation of foundational models. #AI #AIAscent #Sequoia #Startup #Founder #entrepreneur

پیوستن به دوره جامع یادگیری عمیق و هوش مصنوعی، که به 'الکتریسیته جدید' شهرت یافته، شما را قادر می‌سازد تا در دنیای داده‌های بزرگ با استفاده از TensorFlow و Keras به اکتشاف بپردازید. این دوره مهارت‌های تحلیلی شما را تقویت می‌کند و شما را برای پیشروی در صنعت تکنولوژی آماده می‌سازد، تا در مسیر حرفه‌ای خود به موفقیت‌های بزرگ دست یابید.