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.
David Sacks details the Trump administration's strategy for AI and crypto, focusing on unleashing permissionless innovation, combating regulatory capture, and winning the global AI race through infrastructure and open source, while warning against the rise of "Orwellian AI."
Michael Nygard, author of 'Release It!', discusses his experiences at Sabre and Nubank, offering deep insights into balancing autonomy and centralization, the practical implications of Conway's Law, and how architectural boundaries can reduce organizational friction and the need for constant alignment.
![Why Humans Are Still Powering AI [Sponsored]](https://img.youtube.com/vi/R11ESdfVX64/maxresdefault.jpg)
AI's "dirty secret" is its deep reliance on human intelligence. Phelim Bradley, CEO of Prolific, explains how his platform provides the critical human data infrastructure for training and evaluating frontier models, emphasizing the shift from commoditized labor to a sophisticated marketplace of verified expertise.
Melanie Perkins, co-founder and CEO of Canva, shares the core philosophies that propelled the company to a $42 billion valuation. She details her 'Column B' thinking—building towards a dream future rather than from existing constraints—and explains how setting 'crazy big goals' and systematically learning from over 100 investor rejections were crucial. Perkins also discusses surviving a two-year technical rewrite without shipping features and Canva's foundational 'two-step plan' to build a valuable company and use its wealth to do the most good possible.
In a reflective and forward-looking conversation, Daniel Terhorst-North and Kevlin Henney explore the evolution of software development over the past 20 years and predict the key challenges and innovations for the next 20. They delve into the philosophy of programming language design, the critical need for hardware-sympathetic programming, the untapped potential of concurrency models like CSP and the Actor Model, and the future of user interfaces and decentralized technology.
A discussion with Marc Andreessen and Ben Horowitz on the true nature of AI creativity, the limitations of intelligence in leadership, why the current AI boom is not a bubble, and the coming platform shifts and geopolitical race in robotics.
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