Feature

Big updates to mlflow 3.0

Big updates to mlflow 3.0

Databricks’ Eric Peter and Corey Zumar introduce MLflow 3.0, focusing on its new "Agentic Insights" capabilities. They demonstrate how MLflow is evolving from providing tools for manual quality assurance in Generative AI to using intelligent agents to automatically find, diagnose, and prioritize issues, significantly speeding up the development lifecycle.

Amjad Masad & Adam D’Angelo: How Far Are We From AGI?

Amjad Masad & Adam D’Angelo: How Far Are We From AGI?

Adam D’Angelo (Quora/Poe) and Amjad Masad (Replit) debate the future of AI. They clash on whether LLMs are hitting limits, the timeline to AGI, and the societal impact of automating entry-level jobs while expert roles remain, potentially creating a "missing middle" in the workforce.

1X NEO humanoid robot enters the home

1X NEO humanoid robot enters the home

Experts analyze the 1X NEO humanoid robot's real-world viability and data challenges, delve into the complex copyright dispute between Japan's IP holders and OpenAI's Sora 2, and dissect the strategic implications of the new OpenAI and AWS partnership for AI infrastructure and multi-cloud strategies.

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.

Building Claude Code: Origin, Story, Product Iterations, & What's Next // Siddharth Bidasaria// #342

Building Claude Code: Origin, Story, Product Iterations, & What's Next // Siddharth Bidasaria// #342

Siddharth Bidasaria from Anthropic shares the origin story of Claude Code, from a simple internal terminal app to a powerful coding agent. He discusses the team's core philosophy of 'letting the model cook,' the evolution of agentic capabilities, the critical role of verification and testing, and the future of complex, multi-agent systems.

GenAI Grows Up: Building Production-Ready Agents on the JVM • Rod Johnson • GOTO 2025

GenAI Grows Up: Building Production-Ready Agents on the JVM • Rod Johnson • GOTO 2025

Rod Johnson explains the high failure rate of enterprise GenAI projects, attributing it to the misuse of the technology and a disconnect from established software engineering principles. He argues for a paradigm shift away from Python-centric approaches towards the JVM, introducing Embabel, a framework designed to build reliable, testable, and domain-integrated AI agents by tackling non-determinism and leveraging the strengths of the enterprise Java ecosystem.