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.
In a discussion with Astro Teller, Emily Ma from X (formerly Google X) delves into the multifaceted problem of food waste and the moonshot projects developed to tackle it. They explore Project Delta, an initiative that created an "air traffic control" system for surplus food, and Project Chorus, a broader supply chain moonshot designed to give every object a voice through advanced sensors and software.
Ben Horowitz of Andreessen Horowitz discusses how AI is reshaping venture capital, detailing the firm's strategy for managing partners, verticalizing teams, and evaluating investments in real-time. He breaks down the current AI cycle, arguing that application design and model orchestration are key, and explains why the current market's growth is driven by real demand, not just hype.
Ashwin Rajeeva, cofounder and CTO of Acceldata, details the architecture and philosophy behind their Agentic Data Management (ADM) platform. He explains how the Xlake reasoning engine provides crucial context for AI agents to operate across petabyte-scale enterprise data, enabling capabilities like self-healing data pipelines and automated data quality assurance, while also discussing strategies for leading technical teams in the age of AI.
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.
Garry, Harj, Jared, and Diana discuss why founders should pursue contrarian ideas in a crowded AI market. They analyze how companies like Uber, Coinbase, and Flock Safety found massive success by tackling non-obvious, legally ambiguous, or seemingly impossible problems that others ignored.
Kief Morris, author of 'Infrastructure as Code', and Abby Bangser discuss the evolution of IaC over the past decade. They explore the move from server configuration to complex cloud architectures, the limitations of current tooling, and the need for higher-level abstractions, while also looking ahead to the potential impact of AI and the critical role of platform engineering in connecting infrastructure to specific business needs.
The panel discusses the shifting AI hardware landscape as Oracle and OpenAI bet on AMD, challenging Nvidia's dominance. They also analyze a US government report on the risks of the DeepSeek model, debate the viability of Reflection AI's new $2B open-source venture, and dissect the story of a VC fund replacing analysts with AI agents.
A deep dive into the human side of cybersecurity, exploring the motivations of bad actors, the evolution of social engineering in the age of AI, and the defensive strategies being developed. The discussion covers the move beyond passwords with passkeys and risk-based authentication, and confronts the complex security and privacy challenges introduced by autonomous agents.
Mukhund and Madhav Jha, co-founders of Emergent, detail their journey of building an AI-powered app builder that reached $15M ARR in three months. They discuss their pivot from enterprise agents, the multi-agent architecture that enables production-ready apps, and their vision for a future with a 'billion builders'.
Keith Rabois predicts a new American economic boom driven by AI, forecasting 4-6% GDP growth without inflation. He discusses the rise of sovereign AI, OpenAI's dominance as a multi-trillion dollar company, Google's existential threat, and the strategic challenges facing Microsoft, Meta, and Apple in the new AI paradigm.
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