Unsupervised Learning

In this discussion, Simon Eskildsen, the co-founder and CEO of TurboPuffer, shares his insights on the challenges and advancements in AI infrastructure. Drawing from his decade at Shopify, he highlights the limitations of traditional databases for AI applications. Simon introduces the SCRAP framework, emphasizing scale, cost, recall, and performance. He delves into the rise of object storage and the complexities of vector search technology, advocating for smarter retrieval systems to enhance data efficiency and performance.

In this insightful discussion, Karol Hausman, Co-founder and CEO of Physical Intelligence, and Danny Driess, Research Scientist, dive into the evolving realm of AI robotics. They share the transition from traditional coding to machine learning models capable of multitasking. Topics include robots folding laundry and the importance of effective data collection. They dissect the future potential of generalist robots and the challenges of integrating advanced models. Their conversation highlights the transformative impact of robotics on daily life and the importance of open-source collaboration.

Ion Stoica, co-founder of Databricks and Anyscale, and founder of LMArena, dives into the intricacies of AI model evaluation. He reveals the shortcomings of traditional metrics and discusses new dynamic systems for assessing AI models. Stoica highlights the competitive edge China has in open-source AI, urging the need for collaboration in the tech landscape. The conversation also touches on the importance of human involvement in evaluations and the ongoing challenges in AI infrastructure and optimization, reflecting on the future of data and AI in enterprises.

Brendan Foody, the co-founder and CEO of Mercor, leads a pioneering company at the forefront of AI-native labor markets. He discusses the evolving landscape of AI in talent evaluation, emphasizing how AI can enhance hiring practices through improved candidate assessments. Brendan also shares insights on the future of data labeling and the skills needed to thrive in an AI-driven job market. Addressing the demand for software engineers and navigating the complexities of fundraising in tech, he provides a fascinating look at integrating AI into recruitment.

Max Junestrand, Founder and CEO of Legora, shares insights from his journey building an innovative AI platform for the legal industry. He discusses how AI is revolutionizing legal processes, making them more efficient and accurate. Key topics include strategies for scaling in global markets and the challenges of pricing AI applications. Max also reflects on essential lessons learned about adapting product strategies and fostering a fast-paced work culture, while emphasizing the need for law firms to embrace AI to stay competitive.

Sholto Douglas, a Member of Technical Staff at Anthropic, dives into the advancements of Claude 4 and its impressive coding capabilities. He discusses how AI agents are starting to transform research in fields like biology and robotics, emphasizing their role in automating white-collar jobs. Predictions include the timeline for original scientific contributions from AI. A fascinating look into the trust needed between AI models and human developers showcases the economic implications of integrating these agents into everyday workflows.

In this engaging discussion, Daniel Kokotajlo, a former OpenAI researcher and AI alignment advocate, teams up with Thomas Larsen, co-author of the AI 2027 report. They dive into the urgent need for safe AI development, exploring the timeline of AI advancements, the growing tensions between the U.S. and China, and the critical risks of misaligned AI. The duo offers compelling predictions for 2027, emphasizes the importance of public awareness, and lays out essential policy recommendations to ensure a safer AI future.

Michelle Pokrass, a key player in launching GPT-4.1 at OpenAI, delves into the intricacies of AI model development and evaluation. She discusses how user feedback fuels improvements and the evolving challenges in AI training. The conversation highlights the shift towards Reinforcement Fine-Tuning for personalized applications and the importance of balancing conversational abilities with problem-solving as we look towards future models. Her insights reflect a deep understanding of AI's potential and the organizational growth at OpenAI.

When Khan Academy launched Khanmigo, Salman Khan thought they might reach 100k users by 2025. Today, they’re at 1.4 million. 🎧 Sal joined us on Unsupervised Learning to talk about AI's role in education— from the vantage point of someone deploying it at scale. As founder of Khan Academy, he’s overseen the rollout of AI tools to over a million teachers and students, giving him a front-row seat to what’s actually working in classrooms. (0:00) Intro(1:17) The Vision for Future Classrooms(4:28) Khan Academy's AI Initiatives(7:06) Proactive AI and Engagement(10:33) Teacher and Student Experiences(18:24) District-Level Adoption and Policy(25:56) Gamification and Engagement(27:36) Evaluating AI Models(31:03) Global Impact and Future Prospects(37:43) Challenges and Innovations in AI Education(44:19) 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

Aidan Gomez, CEO of Cohere and co-author of the Transformers paper, shares insights on scaling AI for real-world applications. He discusses the importance of reasoning in custom AI models and how tailored solutions can outperform general models in enterprise settings. Aidan also highlights challenges in data integration and the significance of privacy in AI use-cases across sectors like finance and healthcare. He emphasizes the need for global collaboration and the evolving landscape of AI technologies, all while maintaining an optimistic view on AI's societal impacts.