Jun 15, 2026

Cloud, Containers & Security • Adrian Mouat, Kief Morris & Sam Newman • GOTO 2025

In this panel discussion, experts Adrian Mouat, Kief Morris, and Sam Newman delve into the current landscape of cloud technology, container security, and infrastructure automation. They cover key topics such as supply chain security with Sigstore and SBOMs, the practical impact of AI on deterministic systems, the ongoing debate about cloud repatriation, and advanced Infrastructure as Code practices like TDD and managing configuration drift.

May 27, 2026

Power agents with full context of your experiments and traces with W&B MCP server

The W&B Model Context Protocol (MCP) is a hosted endpoint that enables AI agents to intelligently interact with all Weights & Biases data, including runs, traces, evaluations, and reports. It features discovery tools for smart queries, automated analysis for comparing experiments and identifying regressions, and seamless integration with IDEs, coding agents, and chat interfaces like Mistral AI for streamlined ML workflows and on-the-go reporting.

May 22, 2026

Reflections of AI: A Trilogy in 4 Parts • Rasmus Lystrøm • GOTO 2025

In a talk styled as "A Trilogy in Four Parts", Rasmus Lystrøm critically examines the real-world impact of Generative AI, debunking productivity myths and highlighting hidden costs like degraded code quality and environmental strain, while advocating for a return to solving real user problems with valuable, often simpler, technology.

May 20, 2026

What AI Agents Can Do Inside MATLAB and Simulink - Tianyi Zhu | Podcast #173

Tianyi Zhu from MathWorks explains the key differences between AI agents and chatbots, highlighting how agentic AI acts as a powerful amplifier for engineers. The discussion covers practical use cases in MATLAB and Simulink, measurable ROI in automotive workflows, and strategies for safely integrating non-deterministic AI into high-stakes engineering environments.

May 20, 2026

Any-to-Any: Building Native Multimodal Agents - Patrick Löber, Google DeepMind

Patrick Löber from Google DeepMind provides a technical walkthrough of the Gemini API's "any-to-any" capabilities. The session covers multimodal understanding of complex documents, video, and audio; an agentic loop using function calling to trigger native image and speech generation; and the real-time, audio-to-audio Live API.

May 19, 2026

Personalization in the Era of LLMs - Shivam Verma, Spotify

Spotify is personalizing open-weight LLMs without full fine-tuning by combining three key components: foundational user embeddings from streaming history, 'Semantic IDs' that tokenize its 100M+ item catalog, and a 'soft tokenization' layer that projects a user's embedding directly into the LLM's context. This allows the model to autoregressively generate the next song or podcast as the next token in a sequence.