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.
Ivan Nardini from Google Cloud demonstrates how to build, enhance, and productionalize AI agents using Google Cloud's agent stack. The session covers the challenges of deploying agents and introduces the Agent Development Kit (ADK) for building, the Vertex AI Agent Engine for managed deployment, and protocols like MCP and Agent-to-Agent for tool integration and inter-agent communication, using Claude on Vertex AI as the core LLM.
Brooke Hopkins, founder of Coval, discusses how evaluation methodologies from the autonomous vehicle industry, particularly from her experience at Waymo, can be adapted to build reliable, scalable, and trustworthy voice and conversational AI systems.
Founders from Function Health and Slingshot AI discuss building consumer health products by shifting from digital-only context to a 'Human Experience' that brings biological and psychological data online. They explore new engagement paradigms beyond DAU, the role of AI in augmenting rather than replacing doctors, and the ethical imperative of preserving user autonomy.
Sean DuBois (OpenAI, Pion) and Kwindla Hultman Kramer (Daily, Pipecat) argue that to build successful real-time AI applications, developers must start from the network layer up, prioritizing WebRTC over WebSockets to manage latency effectively and enable advanced features like interruption and state management.
An in-depth look at Gabber's experience deploying the Orpheus text-to-speech model to production, covering latency optimization, high-fidelity LoRa-based voice cloning, and a cost-effective inference stack using vLLM and a consistent hash ring for load balancing.
Bryan Kim from a16z, Jonathan Swerdlin from Function Health, and Daniel Cahn from Slingshot AI / Ash discuss how AI is revolutionizing healthcare and mental health by focusing on deep human context rather than just digital behavior. They explore building consumer trust, augmenting rather than replacing professionals, and creating new engagement models like "hourly active use" for a more accessible, continuous, and personalized future of care.
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