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.
Thomas Wolf, co-founder of Hugging Face, discusses his journey from physics to AI, the power of open-source models to accelerate innovation, the practical challenges of productionalizing AI demos, and why the biggest opportunities for founders now lie in the application layer on top of powerful foundation models.
Daren Fields, Co-Founder & CEO of Virtual Select, discusses the future of manufacturing, emphasizing the role of AI as a tool for human augmentation, not replacement. He explores how to modernize manufacturing by combining a carbon-based workforce with silicon-based systems to prevent defects, reduce costs, and de-risk execution.
The panel discusses Anthropic's Claude Cowork and the challenge of user trust in AI agents for everyday tasks. They then analyze the Apple-Google partnership to integrate Gemini into Siri, debating its implications for edge AI, privacy, and hardware limitations. Finally, they explore Linus Torvalds' use of AI for "vibe coding," considering its impact on hobbyist programming and entrepreneurship versus the current limitations in producing production-ready software.
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.
Raiza Martin, co-founder of Huxe and former leader of Google’s NotebookLM team, discusses the move from the text-based, source-grounded world of NotebookLM to building Huxe, an audio-first, mobile-first personal AI companion designed to create delightful and useful experiences in the interstitial moments of a user's day.
SemiAnalysis CEO Dylan Patel discusses the shifting AI landscape, covering OpenAI's strategic open-source release, the fierce competition to challenge Nvidia's dominance, the consolidation of neoclouds, and the geopolitical implications of the global AI infrastructure buildout.
Partners Olivia and Justine Moore discuss the latest in consumer AI, including Grok's uniquely social and fast image generation, Google's interactive world model Genie 3, the user backlash to GPT-5's personality changes, ElevenLabs' licensed AI music model, and the emerging fragmentation of "vibecoding" platforms for technical and non-technical users.
GPT-5 introduces five key improvements to address core limitations of large language models, including a new routing system for model selection, targeted training to reduce hallucinations, post-training penalties for sycophancy, a nuanced "safe completions" approach for sensitive topics, and chain-of-thought monitoring to prevent deception.
Drawing from conversations with top AI builders, Dex argues that production-grade AI agents are not magical loops but well-architected software. This talk introduces "12-Factor Agents," a methodology centered on "Context Engineering" to build reliable, high-performance LLM-powered applications by applying rigorous software engineering principles.
This talk introduces Eval-Driven Development (EDD) as a scientific alternative to 'vibe-based' iteration for improving AI agents. It covers quantitative evaluation (choosing strong end-to-end metrics, aligning LLM judges) and qualitative evaluation (using error and attribution analysis to debug failures), providing a structured framework for consistent agent improvement.
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