Browse entries 913–936 of 1531. Return to the first page to search and filter the complete collection.
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AI Engineer session on Moondream: how does a tiny vision model slap so hard?, presented by Vikhyat Korrapati. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Fixing bugs in Gemma, Llama, & Phi 3: Daniel Han. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on State Space Models for Realtime Multimodal Intelligence: Karan Goel. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Unveiling the latest Gemma model advancements: Kathleen Kenealy. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Adversarial Path to the Personal Assistant: Sumit Agarwal. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Best Practices for Evaluating Large Language Model Applications with llmeval: Niklas Nielsen. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Breaking AI's 1-GHz Barrier: Sunny Madra (Groq). It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on System Design for Next-Gen Frontier Models, presented by Dylan Patel, SemiAnalysis. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Accelerate your AI journey with Azure AI model catalog: Sharmila Chokalingam. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Lessons from the Trenches: Building LLM Evals That Work IRL: Aparna Dhinkaran. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Evaluating Domain Specific LLMs for Real World Finance, presented by Waseem Alshikh, Writer. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Productionizing GenAI Models, presented by Lessons from the world's best AI teams: Lukas Biewald. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on WTF do people use Open Models for??. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Fine tune 20 Llama Models in 5 Minutes: Santosh Radha. It adds practical context for how teams are building and operating AI systems in production.
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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.
Two security teams have shown, in separate research published this week, that OpenClaw, the popular self-hosted AI agent, can be driven to run attacker-controlled code or hand over sensitive data through ordinary-looking inputs.
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AI Engineer session on The Age of the Agent: Flo Crivello. It adds practical context for how teams are building and operating AI systems in production.
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An insurance company does not train its risk model on your DNA. It trains on artifacts derived from your DNA. Under the moral code the user wrote, that is immoral and perfectly legal, and it is the kind of gap Loophole exists to surface.
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Where to start? A new era of cost-efficient AI on a day benchmark-makers got humbled, traders got excited, and AI safety researchers got unnerved.
![Sam Altman :‘AGI in 2026’, just as Models Start to [Mis]Train Themselves video thumbnail](https://i.ytimg.com/vi/KL9_1GbmCic/hqdefault.jpg)
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First, a Time Magazine spread has Sam Altman declaring AGI is imminent, at the same time as we get two bombshell reports, from OpenAI and METR which on first glance are detailing the AI swarm, but reveal a deeper story about how we are making AI in 2026.
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AI Engineer session on The End of Apps, presented by Kitze, Sizzy.co. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on It Ain't Broke: Why Software Fundamentals Matter More Than Ever, presented by Matt Pocock, AI Hero @mattpocockuk. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on How AI is changing Software Engineering: A Conversation with Gergely Orosz, @The Pragmatic Engineer. It adds practical context for how teams are building and operating AI systems in production.