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.
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.
Jure Leskovec introduces Relational Foundation Models (RFMs), a new class of models based on graph neural networks that learn directly from raw, multi-table enterprise data. This approach bypasses manual feature engineering, leading to more accurate, faster-to-deploy, and easier-to-maintain predictive models for tasks like churn prediction, fraud detection, and recommendation systems.
a16z co-founders Marc Andreessen and Ben Horowitz discuss the shift to a decentralized media ecosystem, their investment thesis on supply-driven markets, and the transformative impact of AI. They detail the a16z model of leveraging reputation as a core asset to turn inventors into CEOs and explain why AI represents a fundamental reinvention of computing that will unlock unprecedented growth.
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.
Jacob Helberg, Under Secretary of State designate, discusses how AI will act as a productivity engine to reindustrialize America, the geopolitical race for AI dominance in the "superintelligence century," and the critical need for nuclear energy to power this transformation.
Sequoia Capital's Konstantine Buhler presents an investment thesis on the AI-driven "Cognitive Revolution," framing it as a transformation larger and faster than the Industrial Revolution. The core of the thesis is the $10 trillion opportunity in automating the US services market and the shift in work from certainty to high leverage. Buhler outlines five current investment trends, including real-world validation over academic benchmarks and compute as the new production function, and five future themes Sequoia is betting on, such as persistent memory, AI-to-AI communication, and AI security.
Nikolaos Vasiloglou, VP of Research ML at RelationalAI, shares his extensive analysis of the 2023 NeurIPS conference, distilling over 200 hours of content. Key themes include the dominance and evolution of agentic AI, the state of open-source vs. frontier LLMs, the first signs of deep learning models outperforming XGBoost on tabular data, and the critical rise of verification systems. He also explores the future of AI with data attribution for monetization and the concept of composable, LEGO-like language models.
In the fifth edition of the a16z Consumer AI 100, an analysis of the most-used AI-native products reveals a market that is beginning to stabilize after a period of chaotic growth. Key trends identified include the continued dominance of AI companionship and creative tools, the significant market entry of major players like Google and xAI's Grok, the rise of Chinese AI companies on the global stage, and the emergence of a powerful new category: "vibe coding." The data suggests a future of increased verticalization, prosumer tool adoption, and the development of more sophisticated network effects beyond simple data acquisition.
Daniel Terhorst-North explores the learnable traits of great programmers, challenging the notion of innate talent. He outlines a three-part framework focusing on effective execution, selecting appropriate tools, and fostering a psychologically safe team environment, emphasizing that greatness is achieved through deliberate practice and a focus on product and people over code.
Lak Lakshmanan presents a robust architecture for building production-quality, framework-agnostic agentic systems. He advocates for using simple, composable GenAI patterns, off-the-shelf tools for governance, and a strong emphasis on a human-in-the-loop design to create continuously learning systems that avoid vendor lock-in.
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