Llm

No Priors Ep. 139 | With Snowflake CEO Sridhar Ramaswamy

No Priors Ep. 139 | With Snowflake CEO Sridhar Ramaswamy

Snowflake CEO Sridhar Ramaswamy discusses the company's rapid transformation into an AI-first data platform. He introduces Snowflake Intelligence, an agentic system for enterprise data, and explores the strategic pivot, the ROI of AI for businesses, and the evolving roles of data platforms, partnerships, and search in the age of AI.

Intelligence as "Less is More" - Prof. David Krakauer [SFI]

Intelligence as "Less is More" - Prof. David Krakauer [SFI]

Prof. David Krakauer redefines intelligence not as possessing more knowledge, but as the ability to do more with less. He argues that LLMs are mere 'libraries' and proposes a universal theory where all life is intelligent, operating across strategic, inferential, and representational dimensions, with the latter being key to making hard problems easy.

How AI Agents and Decision Agents Combine Rules & ML in Automation

How AI Agents and Decision Agents Combine Rules & ML in Automation

A detailed breakdown of a multi-method Agentic AI architecture, combining Large Language Models (LLMs) with traditional automation like workflow and decision engines to solve complex, real-world problems like loan processing.

Marc Andreessen & Amjad Masad on “Good Enough” AI, AGI, and the End of Coding

Marc Andreessen & Amjad Masad on “Good Enough” AI, AGI, and the End of Coding

Amjad Masad, founder of Replit, joins a16z to discuss the rise of AI agents that can now plan, reason, and code for hours. He explains how reinforcement learning and verification loops unlocked long-horizon reasoning, why AI is advancing fastest in verifiable domains like code, and debates whether "good enough" AI might be a local maximum that blocks the path to AGI.

AI Agents + LLM Reasoning: Transforming Autonomous Workflows

AI Agents + LLM Reasoning: Transforming Autonomous Workflows

Explore the distinction between LLMs and AI agents, focusing on how agents leverage reasoning, tool calling, and the ReAct prompting framework for autonomous decision-making and task execution in complex business workflows.

Machine Learning Explained: A Guide to ML, AI, & Deep Learning

Machine Learning Explained: A Guide to ML, AI, & Deep Learning

A breakdown of Machine Learning (ML), its relationship with AI and Deep Learning, and its core paradigms: supervised, unsupervised, and reinforcement learning. The summary explores classic models and connects them to modern applications like Large Language Models (LLMs) and Reinforcement Learning with Human Feedback (RLHF).