An expert overview of post-training techniques for language models, covering the entire workflow from data generation and curation to advanced algorithms like Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Learning (RL), along with practical advice on evaluation and iteration.
This talk introduces Anaximander, a system designed to bridge the gap between traditional, GUI-driven Geographic Information System (GIS) workflows and modern, code-heavy machine learning practices. Anaximander integrates geospatial foundation models directly into QGIS, allowing experts to interactively orchestrate, run, and evaluate models for tasks like semantic segmentation and object detection on satellite imagery.
At Applied Compute, efficient Reinforcement Learning is critical for delivering business value. This talk explores the transition from inefficient synchronous RL to a high-throughput asynchronous 'Pipeline RL' system. The core challenge is managing 'staleness'—a side effect of in-flight weight updates that can destabilize training. The speakers detail their first-principles systems model, based on the Roofline model, used to simulate and find the optimal allocation of GPU resources between sampling and training, balancing throughput with algorithmic stability and achieving significant speedups.
A panel of university students from LSE, Princeton, Berkeley, and ASU discuss the real-world impact of AI on campus life. They cover how AI is used as both a powerful learning tool and a crutch, the innovative projects students are building, how universities are adapting, and the challenges of navigating cheating, job applications, and 'AI slop' in a rapidly changing educational landscape.
Explore how Temporal, a durable execution framework, brings resilience and scalability to AI agents built with the OpenAI Agents SDK. This summary covers Temporal's core concepts of Workflows and Activities, the official integration that makes OpenAI agents durable, and patterns for orchestrating multiple micro-agents.
This talk introduces 'structured dissent,' a multi-agent orchestration pattern where believer, skeptic, and neutral agents debate decisions to overcome the 'confidently wrong' failure mode of single-agent LLM systems, improving reliability for high-stakes tasks like cybersecurity analysis.
Nikesh Arora, CEO of Palo Alto Networks, shares his unconventional journey and leadership philosophy. He provides a masterclass in building a multi-platform company through strategic M&A, explains why founders should sometimes ignore customers, and reveals how to lead with conviction while managing imposter syndrome.
Stewart Butterfield, co-founder of Slack and Flickr, shares the product frameworks and leadership principles that guided his success. He delves into concepts like "utility curves" for feature investment, the "owner's delusion" in product design, and why focusing on "comprehension" is often more important than reducing friction. He also introduces powerful mental models for organizational effectiveness, such as combating "hyper-realistic work-like activities" and applying Parkinson's Law to team growth.
Intuit CEO Sasan Goodarzi discusses the operational playbook for reinventing a 40-year-old company, from its slow transition to SaaS to its early adoption of AI. He shares insights on winning the SMB market by treating small businesses like consumers, building effective channel partnerships, and developing a platform strategy. Goodarzi also details his leadership philosophy, emphasizing that grit and curiosity are more critical than raw talent.
A recap of key conversations from the No Priors podcast in 2025, featuring insights from leaders at OpenAI, Harvey, and the Center for AI Safety on topics ranging from reasoning models and spatial intelligence to the geopolitical risks of superintelligence and the human impact of AI in healthcare.
The Mixture of Experts panel discusses Anthropic's major investment in Google's TPUs for inference, debates the feasibility of insuring superintelligence, critiques OpenAI's approach to handling sensitive user conversations, and explores the futuristic concept of data centers in outer space.
A viral MIT report claimed 95% of enterprise AI projects fail. This isn't because AI doesn't work, but because large companies are ill-equipped to build it. This creates a massive opportunity for startups that can deliver functional, integrated AI solutions where enterprises and established vendors fall short.
Gavin Baker, CIO of Atreides Management, and David George, General Partner at a16z, provide a macro view of the AI landscape. They discuss the trillion-dollar data center buildout, compare the current AI boom to the 2000 telecom bubble, analyze the competitive dynamics in AI infrastructure between Nvidia and Google, and explore the evolving business models for AI applications and the future of SaaS.
IBM's Granite 4.0 models introduce a groundbreaking hybrid architecture combining Mamba-2 and Transformer blocks with a Mixture of Experts (MoE) design. This approach enables smaller models to achieve superior performance, speed, and memory efficiency, even outperforming much larger models on key enterprise tasks while running on consumer-grade hardware.
Nick Schrock, CTO of Dagster, introduces Compass, a Slack-native tool for collaborative, exploratory data analysis, and discusses the rising importance of 'context engineering' as the new data pipeline in the AI era.
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