Unsupervised Learning x Latent Space Crossover Special
Latent Space: The AI Engineer Podcast
Intro
In this chapter, speakers discuss the rapid evolution of AI over the past year, highlighting key developments and strategic decisions in model releases. The conversation also addresses the adoption challenges of open-source models in enterprise contexts and the varied enthusiasm seen across different user communities.
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
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