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AI Agents, Meet Test Driven Development
AI Engineer session on AI Agents, Meet Test Driven Development. It adds practical context for how teams are building and operating AI systems in production.
Research archive, page 18
Browse entries 409–432 of 1025. Return to the first page to search and filter the complete collection.
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How to Improve Your Agents: Academic Lit Review
AI Engineer session on How to Improve Your Agents: Academic Lit Review. It adds practical context for how teams are building and operating AI systems in production.
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Building and evaluating AI Agents — Sayash Kapoor, AI Snake Oil
AI Engineer session on Building and evaluating AI Agents, presented by Sayash Kapoor, AI Snake Oil. It adds practical context for how teams are building and operating AI systems in production.
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POC Prison: Why agentic systems never escape the lab and how to fix that in 90 days - Luise Freese
This talk was recorded at NDC Copenhagen in Copenhagen, Denmark. #ndccopenhagen #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndccopenhagen.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media!
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Code Mode: Let the Code do the Talking - Sunil Pai, Cloudflare
AI Engineer session on Code Mode: Let the Code do the Talking - Sunil Pai, Cloudflare. It adds practical context for how teams are building and operating AI systems in production.
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OpenRAG: An open-source stack for RAG — Phil Nash
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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Why, and how you need to sandbox AI-Generated Code? — Harshil Agrawal, Cloudflare
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.
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Defying Gravity - Kevin Hou, Google DeepMind
AI Engineer session on Defying Gravity - Kevin Hou, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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RL Environments at Scale — Will Brown, Prime Intellect
AI Engineer session on RL Environments at Scale, presented by Will Brown, Prime Intellect. It adds practical context for how teams are building and operating AI systems in production.
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Building in the Gemini Era — Kat Kampf & Ammaar Reshi, Google DeepMind
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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Minimax M2: Building the #1 Open Model — Olive Song, MiniMax
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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The Rise of Open Models in the Enterprise — Amir Haghighat, Baseten
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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Perceptual Evaluations: Evals for Aesthetics — Diego Rodriguez, Krea.ai
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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What Is a Humanoid Foundation Model? An Introduction to GR00T N1 - Annika & Aastha
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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Real-time Experiments with an AI Co-Scientist - Stefania Druga, fmr. Google Deepmind
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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How to build world-class AI products — Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)
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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RAG Evaluation Is Broken! Here's Why (And How to Fix It) - Yuval Belfer and Niv Granot
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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How to build the world's fastest voice bot: Kwindla Hultman Kramer
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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How Deep Research Works - Mukund Sridhar & Aarush Selvan, Google DeepMind
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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How to Construct Domain Specific LLM Evaluation Systems: Hamel Husain and Emil Sedgh
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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Customized, production ready inference with open source models: Dmytro (Dima) Dzhulgakov
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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Understanding AI Stakes to Break Production Code: Philip Rathle
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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How to evaluate a model for your use case: Emmanuel Turlay
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.
![[Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool video thumbnail](https://i.ytimg.com/vi/sKiTUuEV1rw/hqdefault.jpg)
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[Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool
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.