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.
Snowflake CEO Sridhar Ramaswamy discusses the company's rapid transformation into an AI-first data platform. He introduces Snowflake Intelligence, an agentic system for enterprise data, and explores the strategic pivot, the ROI of AI for businesses, and the evolving roles of data platforms, partnerships, and search in the age of AI.
![Intelligence as "Less is More" - Prof. David Krakauer [SFI]](https://img.youtube.com/vi/dY46YsGWMIc/maxresdefault.jpg)
Prof. David Krakauer redefines intelligence not as possessing more knowledge, but as the ability to do more with less. He argues that LLMs are mere 'libraries' and proposes a universal theory where all life is intelligent, operating across strategic, inferential, and representational dimensions, with the latter being key to making hard problems easy.
Siddharth Bidasaria from Anthropic shares the origin story of Claude Code, from a simple internal terminal app to a powerful coding agent. He discusses the team's core philosophy of 'letting the model cook,' the evolution of agentic capabilities, the critical role of verification and testing, and the future of complex, multi-agent systems.
Eugenia Kuyda, CEO of Wabi and founder of Replika, explains her vision for the future of personal software, where AI transitions from command-line interfaces to a creative, user-generated medium. She details how ephemeral, deeply personalized mini-apps will replace many traditional applications, fostering a new creator economy and transforming our interaction with technology.
Rod Johnson explains the high failure rate of enterprise GenAI projects, attributing it to the misuse of the technology and a disconnect from established software engineering principles. He argues for a paradigm shift away from Python-centric approaches towards the JVM, introducing Embabel, a framework designed to build reliable, testable, and domain-integrated AI agents by tackling non-determinism and leveraging the strengths of the enterprise Java ecosystem.
Thermal engineer and 2024 Thermy Award winner Wendy Luiten discusses the impending energy and water crisis driven by AI data centers. She explores how computational fluid dynamics (CFD) and a shift to sustainable liquid immersion cooling, particularly with plant-based oils, can mitigate the environmental impact while ensuring performance.
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