Ai

Claude Cowork analysis & Apple picks Gemini

Claude Cowork analysis & Apple picks Gemini

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.

Graph Neural Networks Just Solved Enterprise AI?

Graph Neural Networks Just Solved Enterprise AI?

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.

Ben & Marc: Why Everything Is About to Get 10x Bigger

Ben & Marc: Why Everything Is About to Get 10x Bigger

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.

How to Make AI Forget

How to Make AI Forget

Ben Luria, CEO of Hirundo, discusses the critical need for machine unlearning, framing it as a form of "AI neuro-surgery" for enterprise AI. He explains how this technique directly modifies model weights to remove unwanted data and behaviors, addressing core risks that superficial solutions like guardrails cannot solve.

What are State Space Models? Redefining AI & Machine Learning with Data

What are State Space Models? Redefining AI & Machine Learning with Data

State Space Models (SSMs) are emerging as a powerful and efficient alternative to Transformers for handling sequential data. Aaron Baughman explains the core concepts of SSMs, their mathematical foundations, and how architectures like S4 and Mamba address the memory and scalability challenges inherent in Transformers, leading to a new generation of faster, more intelligent hybrid AI models.

AI and the Future of Warfare with US Under Secretary of War Emil Michael

AI and the Future of Warfare with US Under Secretary of War Emil Michael

Emil Michael, the Under Secretary of War for Research and Engineering, details the radical technological transformation of the US military. He discusses the architecture and rapid launch of GenAI.mil, an internal AI platform powered by Gemini that reached over one million users in 30 days. He also outlines critical technology priorities, including scaled hypersonics and autonomous drone swarms, and the urgent need to rebuild the American defense industrial base for a new era of global competition.