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
