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.
Itamar Friedman of Qodo argues that the future of AI in software development lies in moving beyond simple code generation to 'vibe coding with confidence.' This is achieved through multi-agent workflows, grounded in team standards and orchestrated via the Command Line Interface (CLI), enabling a holistic AI-driven approach across the entire SDLC.
Tanmai Gopal, CEO of Hasura, discusses a Gen AI-driven automation strategy that addresses the "Automation Paradox" by empowering non-technical users. This approach uses a domain-specific language (DSL) to translate natural language into deterministic, executable plans, aiming to drive over $100M in annual impact for a healthcare partner.
Leaders from VMware and Cisco share hard-won lessons on navigating disruption, fostering a founder's mindset at scale, and rebuilding for the AI era. They cover GTM strategies for new products, the importance of storytelling as strategy, and why AI represents a 100x shift for infrastructure.
Paul van der Boor and Bruce Martens from Prosus discuss the real bottlenecks in AI agent development, arguing that the primary challenges are not tools, but rather evaluation, data quality, and feedback loops. They detail their 'buy-first' philosophy, the practical reasons they often build in-house, and how new coding agents like Devon and Cursor are changing their development workflows.
A discussion on the promise and limitations of coding agents, covering key challenges like verification and debugging, and exploring how they can support developers through improved abstraction, collaboration, and handling long-term tasks.
![DeepMind's Secret AI Project That Will Change Everything [EXCLUSIVE]](https://img.youtube.com/vi/ekgvWeHidJs/maxresdefault.jpg)
Google DeepMind's Genie 3 is a new generative interactive environment that creates photorealistic, controllable 3D worlds from text prompts in real-time. This summary explores its architecture, the concept of emergent consistency, and its primary application as a powerful simulator for training embodied AI agents.
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