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.
This session from Okta and Auth0 introduces a comprehensive framework for securing AI agents, covering identity establishment, delegated API access via Token Vault, user consent for risky operations using Asynchronous Authorization (CIBA), and integration with MCP servers.
A discussion on the evolving cybersecurity landscape, covering the persistent threat of ransomware gangs adapting with AI, the critical failures in identity security highlighted by the Zestix case, the emergence of AI agents as a new class of insider threats, and the physical-world risks demonstrated by hacking humanoid robots.
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.
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.
Craig Tavares, COO of Buzz HPC, provides an in-depth look at the complexities of building and scaling GPU cloud infrastructure for AI. He covers the critical role of renewable energy and strategic location, the evolution of data center design to handle extreme power densities, the importance of a strong partnership with NVIDIA, and the rise of sovereign mandates shaping the future of AI cloud services.
In the AI startup landscape, the traditional concept of a business "moat" is more critical than ever. This summary explores Hamilton Helmer’s Seven Powers framework, adapting its timeless business strategies for today's AI companies and emphasizing that while speed is the initial moat, long-term defensibility is built through strategic advantages in process, data, and business models.
Alex Rampell of a16z explains how software is evolving from digitizing records to performing labor, shifting the industry's focus from the $300 billion SaaS market to the $13 trillion labor market. This transition, accelerated by AI, is forcing a change in business models from seat-based pricing to outcome-based pricing, creating new opportunities and expanding the total addressable market.
A deep dive into the latest AI model releases, including IBM's hyper-efficient Granite 4.0, Anthropic's code-focused Claude 4.5, and OpenAI's consumer-centric Sora 2. The discussion covers the strategic differentiation between major AI labs, the future of open-source, the rise of AI e-commerce agents, and the emerging cybersecurity challenges of social engineering AI.
Experts from Anthropic discuss the evolution of the Claude Developer Platform, the philosophy of "unhobbling" models with tools rather than restrictive scaffolding, and the future of building sophisticated, autonomous AI agents with features like the Claude Agent SDK, advanced context management, and persistent memory.
Cybersecurity experts Jeff Crume and Patrick Fussell outline the essential skills, mindset, certifications, and career paths for aspiring ethical hackers, offering practical advice for breaking into the field of penetration testing and red teaming.
Get updates straight to your inbox. No spam, just useful content.