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AI Engineer session on Building in the Gemini Era, presented by Kat Kampf & Ammaar Reshi, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Minimax M2: Building the #1 Open Model, presented by Olive Song, MiniMax. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Rise of Open Models in the Enterprise, presented by Amir Haghighat, Baseten. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Perceptual Evaluations: Evals for Aesthetics, presented by Diego Rodriguez, Krea.ai. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on What Is a Humanoid Foundation Model? An Introduction to GR00T N1 - Annika & Aastha. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Real-time Experiments with an AI Co-Scientist - Stefania Druga, fmr. Google Deepmind. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How to build world-class AI products, presented by Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust). It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on RAG Evaluation Is Broken! Here's Why (And How to Fix It) - Yuval Belfer and Niv Granot. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How to build the world's fastest voice bot: Kwindla Hultman Kramer. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How Deep Research Works - Mukund Sridhar & Aarush Selvan, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How to Construct Domain Specific LLM Evaluation Systems: Hamel Husain and Emil Sedgh. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Customized, production ready inference with open source models: Dmytro (Dima) Dzhulgakov. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Understanding AI Stakes to Break Production Code: Philip Rathle. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How to evaluate a model for your use case: Emmanuel Turlay. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on [Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on GitHub Copilot: The World's Most Widely Adopted AI Developer Tool. It adds practical context for how teams are building and operating AI systems in production.
Earlier this month, I spoke at the Gartner Security & Risk Management Summit about a blind spot most security programs are still not accounting for - how attackers are circumventing AI security programs by using legacy infrastructure to hijack AI agents.
AI could help defenders of critical infrastructure identify the vulnerabilities that attackers might exploit—and close them before they are exploited.
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An AI skill is a piece of code you hand a model to extend what it can do, and once engineers start sharing skills with each other, each one becomes a supply chain risk, more so inside a regulated bank.
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AI Engineer session on OpenRAG: An open-source stack for RAG, presented by Phil Nash. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Why, and how you need to sandbox AI-Generated Code?, presented by Harshil Agrawal, Cloudflare. It adds practical context for how teams are building and operating AI systems in production.
The rapid development and deployment of emerging technologies such as artificial intelligence, blockchain, and the internet of things is driving an increased need for standards that can keep pace with the accelerating rate of technological change.
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AI Engineer session on Jack Morris: Stuffing Context is not Memory, Updating Weights is. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How Claude Code Works - Jared Zoneraich, PromptLayer. It adds practical context for how teams are building and operating AI systems in production.