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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.
Research archive, page 23
Browse entries 529–552 of 1346. Return to the first page to search and filter the complete collection.
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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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What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench
AI Engineer session on What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench. It adds practical context for how teams are building and operating AI systems in production.
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Building Generative Image & Video models at Scale - Sander Dieleman (Veo and Nano Banana)
AI Engineer session on Building Generative Image & Video models at Scale - Sander Dieleman (Veo and Nano Banana). It adds practical context for how teams are building and operating AI systems in production.
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Gemma, DeepMind's Family of Open Models — Omar Sanseviero, Google DeepMind
AI Engineer session on Gemma, DeepMind's Family of Open Models, presented by Omar Sanseviero, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Running LLMs on your iPhone: 40 tok/s Gemma 4 with MLX — Adrien Grondin, Locally AI
AI Engineer session on Running LLMs on your iPhone: 40 tok/s Gemma 4 with MLX, presented by Adrien Grondin, Locally AI. It adds practical context for how teams are building and operating AI systems in production.
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Frontier AI and the Future of Intelligence — Raia Hadsell, VP of Research, Google DeepMind
AI Engineer session on Frontier AI and the Future of Intelligence, presented by Raia Hadsell, VP of Research, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Building pi in a World of Slop — Mario Zechner
AI Engineer session on Building pi in a World of Slop, presented by Mario Zechner. It adds practical context for how teams are building and operating AI systems in production.
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Let LLMs Wander: Engineering RL Environments — Stefano Fiorucci
AI Engineer session on Let LLMs Wander: Engineering RL Environments, presented by Stefano Fiorucci. It adds practical context for how teams are building and operating AI systems in production.
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One Registry to Rule them All - Sonny Merla, Mauro Luchetti, & Mattia Redaelli, Quantyca
AI Engineer session on One Registry to Rule them All - Sonny Merla, Mauro Luchetti, & Mattia Redaelli, Quantyca. 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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Real World Development with GitHub Copilot and VS Code — Harald Kirschner, Christopher Harrison
AI Engineer session on Real World Development with GitHub Copilot and VS Code, presented by Harald Kirschner, Christopher Harrison. 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.
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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.