Unsupervised Learning

Lin Qiao, the co-founder of Fireworks.ai, sits down for a deep dive into the future of AI. Lin ran the PyTorch team at Meta, which developed some of the most fundamental open-source AI software in use today. She’s got a riveting perspective on the AI landscape that is a must-listen. [0:00] Intro[1:06] Fireworks: Revolutionizing AI Inference[2:12] Challenges in AI Model Development[4:05] The Future of AI: Compound Systems[4:32] Designing Effective AI Tools[10:26] Customization and Fine-Tuning in AI[14:06] Human-in-the-Loop Automation[16:38] Evaluating AI Models[19:18] Building Complex AI Systems[21:18] Function Calling and AI Orchestration[26:52] AI Infrastructure and Hardware[31:08] Small Expert Models[31:27] Hyperscalers and Resource Management[32:14] Inference Systems and Scalability[33:08] Running Models Locally: Cost and Privacy[35:20] Open Source Models and Meta's Role[36:41] The Evolution of AI Training and Inference[38:04] Fireworks' Vision and Market Strategy[40:46] The Impact of Generative AI[45:18] AI Research and Future Trends[46:58] Building for a Rapidly Changing AI Landscape[49:36] Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint

Noam Brown, renowned AI researcher and key figure at OpenAI, joins us for a deep dive into the o1 release. Recorded just one day before o1’s full public debut, this episode explores the groundbreaking advancements and challenges behind this innovative test-time compute model.We discuss the technical breakthroughs that set o1 apart, its unique capabilities compared to previous models, and how it disrupts traditional paradigms in AI development. Noam also shares insights into OpenAI’s approach to innovation, the economic realities of scaling AI, and what the future holds for the field. [0:00] Intro[0:50] Scaling Model Capabilities and Economic Constraints[2:48] Excitement Around Test Time Compute[4:50] Challenges and Future Directions in AI Research[8:11] Noam Brown's Journey and OpenAI's Research Focus[16:08] The Role of Specialized Models and Tools[21:18] Unexpected Use Cases and Future Milestones[23:44] Proof of Concept: o1's Capabilities[24:48] The Bitter Lesson: Insights from Richard Sutton[25:59] Scaffolding Techniques and Their Future[27:56] Challenges in Academia and AI Research[30:30] Evaluating AI Models: Metrics and Trends[34:47] The Role of AI in Social Sciences[39:39] AI Agents and Emergent Communication[40:17] Future of AI Robotics[41:13] Advancing Scientific Research with AI[43:30] Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint

For this episode of Unsupervised Learning we spoke with Russ d'Sa, co-founder of LiveKit, a company at the forefront of voice AI technology. Russ thinks of LiveKit as a “nervous system,” powering the sensory interfaces humans use to interact with AI – including the Advanced Voice feature in ChatGPT as well as applications like Character.ai, Spotify and many more. Russ talked about when voice makes sense as an interface, the exciting new UX paradigms on the horizon, the intersection of voice and robotics and Anthropic's Computer Use API. [0:00] Intro[0:24] Using ChatGPT Voice in Daily Life[2:26] How LiveKit Works with ChatGPT Voice[5:16] LiveKit as the Nervous System for AI[8:11] Future of Work and AI Interfaces[18:31] Emerging Use Cases for Voice AI[22:29] AI Models in Customer Support[23:10] Latency Improvements in AI[24:37] Challenges in System Integration[26:01] Multimodal AI and Browser Integration[29:40] Telephony and AI in Healthcare[32:11] Humanoid Robotics and On-Device AI[33:50] Cloud vs. On-Device Inference[36:50] Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint

Jonathan Frankle is the Chief AI Scientist at Databricks ($43B), which he joined through the acquisition of MosaicML in July 2023. Databricks has over 12,000 customers on the cutting edge of AI; Jonathan works to anticipate their needs and offer solutions even as the tech is rapidly evolving. [0:00] Intro[0:52] Incentives and Team Motivation at Databricks[2:40] The Evolution of AI Models: Transformers vs. LSTMs[5:27] Mosaic and Databricks: A Strategic Merger[7:31] Guidance on AI Model Training and Fine-Tuning[11:11] Building Effective AI Evaluations[16:02] Domain-Specific AI Models and Their Importance[19:37] The Future of AI: Challenges and Opportunities[25:07] Ethical Considerations and Human-AI Interaction[29:13] Customer Collaboration and AI Implementation[30:45] Navigating AI Tools and Techniques[35:41] The Role of Open Source Models[36:46] AI Infrastructure and Partnerships[48:27] Academia's Role in AI Research[52:09] Ethics and Policy in AI[57:47] Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint