Unsupervised Learning x Latent Space Crossover Special

Unsupervised Learning is a podcast that interviews the sharpest minds in AI about what’s real today, what will be real in the future and what it means for businesses and the world - helping builders, researchers and founders deconstruct and understand the biggest breakthroughs. Top guests: Noam Shazeer, Bob McGrew, Noam Brown, Dylan Patel, Percy Liang, David Luan https://www.latent.space/p/unsupervised-learning Timestamps 00:00 Introduction and Excitement for Collaboration 00:27 Reflecting on Surprises in AI Over the Past Year 01:44 Open Source Models and Their Adoption 06:01 The Rise of GPT Wrappers 06:55 AI Builders and Low-Code Platforms 09:35 Overhyped and Underhyped AI Trends 22:17 Product Market Fit in AI 28:23 Google's Current Momentum 28:33 Customer Support and AI 29:54 AI's Impact on Cost and Growth 31:05 Voice AI and Scheduling 32:59 Emerging AI Applications 34:12 Education and AI 36:34 Defensibility in AI Applications 40:10 Infrastructure and AI 47:08 Challenges and Future of AI 52:15 Quick Fire Round and Closing Remarks Chapters 00:00:00 Introduction and Collab Excitement 00:00:58 Open Source and Model Adoption 00:01:58 Enterprise Use of Open Source Models 00:02:57 The Competitive Edge of Closed Source Models 00:03:56 DeepSea and Open Source Model Releases 00:04:54 Market Narrative and DeepSea Impact 00:05:53 AI Engineering and GPT Wrappers 00:06:53 AI Builders and Low-Code Platforms 00:07:50 Innovating Beyond Existing Paradigms 00:08:50 Apple and AI Product Development 00:09:48 Overhyped and Underhyped AI Trends 00:10:46 Frameworks and Protocols in AI Development 00:11:45 Emerging Opportunities in AI 00:12:44 Stateful AI and Memory Innovation 00:13:44 Challenges with Memory in AI Agents 00:14:44 The Future of Model Training Companies 00:15:44 Specialized Use Cases for AI Models 00:16:44 Vertical Models vs General Purpose Models 00:17:42 General Purpose vs Domain-Specific Models 00:18:42 Reflections on Model Companies 00:19:39 Model Companies Entering Product Space 00:20:38 Competition in AI Model and Product Sectors 00:21:35 Coding Agents and Market Dynamics 00:22:35 Defensibility in AI Applications 00:23:35 Investing in Underappreciated AI Ventures 00:24:32 Analyzing Market Fit in AI 00:25:31 AI Applications with Product Market Fit 00:26:31 OpenAI's Impact on the Market 00:27:31 Google and OpenAI Competition 00:28:31 Exploring Google's Advancements 00:29:29 Customer Support and AI Applications 00:30:27 The Future of AI in Customer Support 00:31:26 Cost-Cutting vs Growth in AI 00:32:23 Voice AI and Real-World Applications 00:33:23 Scaling AI Applications for Demand 00:34:22 Summarization and Conversational AI 00:35:20 Future AI Use Cases and Market Fit 00:36:20 AI Education and Model Capabilities 00:37:17 Reforming Education with AI 00:38:15 Defensibility in AI Apps 00:39:13 Network Effects and AI 00:40:12 AI Brand and Market Positioning 00:41:11 AI Application Defensibility 00:42:09 LLM OS and AI Infrastructure 00:43:06 Security and AI Application 00:44:06 OpenAI's Role in AI Infrastructure 00:45:02 The Balance of AI Applications and Infrastructure 00:46:02 Capital Efficiency in AI Infrastructure 00:47:01 Challenges in AI DevOps and Infrastructure 00:47:59 AI SRE and Monitoring 00:48:59 Scaling AI and Hardware Challenges 00:49:58 Reliability and Compute in AI 00:50:57 Nvidia's Dominance and AI Hardware 00:51:57 Emerging Competition in AI Silicon 00:52:54 Agent Authentication Challenges 00:53:53 Dream Podcast Guests 00:54:51 Favorite News Sources and Startups 00:55:50 The Value of In-Person Conversations 00:56:50 Private vs Public AI Discourse 00:57:48 Latent Space and Podcasting 00:58:46 Conclusion and Final Thoughts