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.
Jeff Crume and Patrick Fussell from IBM's X-Force team share a real-world ethical hacking war story, demonstrating an attack from an 'assume breach' perspective. They break down how vulnerabilities in Identity and Access Management (IAM) and legacy systems can lead to a full compromise, starting from an insider threat and escalating to domain administrator privileges through advanced C2 attacks and lateral movement.
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.
An in-depth look at building real-time, production-grade voice AI agents using the open-source Pipecat framework. This summary covers the core concepts of voice AI pipelines, the shift to speech-to-speech models like Gemini Live, and advanced techniques for managing latency, context, and turn-taking.
Chip Conley, the founder of Joie de Vivre hotels and former Head of Global Hospitality and Strategy at Airbnb, shares his insights on intergenerational collaboration, thriving in tech as an older professional, and how human wisdom will become more valuable in the age of AI. He discusses his experience working with Brian Chesky, tactics for navigating "founder mode," and the frameworks he developed for building culture and finding meaning, which led him to create the Modern Elder Academy.
Moving an AI PoC from 50% to 100% reliability requires a new development paradigm. This talk introduces a practical, evaluations-first approach, reverse-engineering tests from real-world user scenarios and business outcomes to build a robust benchmark, prevent regressions, and enable confident optimization.
A deep dive into "Vibe Coding," a development methodology that prioritizes outcomes over code-level details, using the advanced AI features of VS Code and GitHub Copilot. The talk explores three stages of this methodology—YOLO, Structured, and Spectrum—and demonstrates how to leverage agent modes, custom instructions, reusable prompts, and the Model Copilot Protocol (MCP) to enhance productivity from rapid prototyping to enterprise-scale development.
A deep dive into building and scaling production-ready AI agents, detailing a model-driven approach using the open-source 'Strands' SDK and a cloud-native architecture for deploying remote tools with MCP and AWS Lambda.
Sarah Goa from the AI-native venture fund Conviction discusses the state of AI, arguing that despite the hype, building valuable AI products is challenging. She covers the rapid advancement in AI capabilities like reasoning and multimodality, the increasingly competitive model market, and provides a playbook for building successful applications, using "Cursor for X" as a framework. The key takeaway is that defensibility in AI comes from superior execution and deep workflow integration, not just the underlying model.
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