Browse entries 985–1008 of 1123. Return to the first page to search and filter the complete collection.
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AI Engineer session on Insights on Building AI Teams, presented by Heath Black, SignalFire. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Keynote: The AI developer experience doesn't have to suck, presented by why and how we built Modal. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Multimodal Future of Education: Stefania Druga. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The LLM Triangle: Engineering Principles for Robust AI Applications - Almog Baku:. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Accelerating Mixture of Experts Training With Rail Optimized InfiniBand Networking in Crusoe Cloud. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Cohere for VPs of AI: Vivek Muppalla. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Everything you need to know about Fine-tuning and Merging LLMs: Maxime Labonne. 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 the AI Software Engineer: Jesse Han. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Substrate Launch: the API for modular AI. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on AI Engineers: The Next Generation, presented by Stefania Druga, Google Gemini. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Your LLM Ran Out of Knowledge, presented by Now What?. It adds practical context for how teams are building and operating AI systems in production.
![[Full Workshop] Llama 3 at 1,000 tok/s on the SambaNova AI Platform video thumbnail](https://i.ytimg.com/vi/z_Xh2MzqKDM/hqdefault.jpg)
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AI Engineer session on [Full Workshop] Llama 3 at 1,000 tok/s on the SambaNova AI Platform. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Future of Knowledge Assistants: Jerry Liu. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on 10x Development: LLMs For the working Programmer - Manuel Odendahl. It adds practical context for how teams are building and operating AI systems in production.
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Fable 5 (newly re-released) vs GPT 5.6 Sol, what comparisons can we unearth? Plus, Sonnet 5, a 5% equity seizure by US Govt, the ‘largest heist’, Beetlejuice and more… Exclusive Vids in AI Insiders ($9!): https://www.patreon.com/AIExplained Chapters: 00:00 - Introduction 01:06 - Fable Timeline 02:59 - Sol Release?
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Claude Fable 5 banned, but what’s the bigger story. We go through 11 under-reported details, so you have the context to see what’s coming next for your use of AI. From whether the ban will last, what the possible motives are, what the model can actually do, and some wild over-extrapolations going on.
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The biggest Google AI push of the year, but what is the bigger story? Why is Google pursuing a different fork in the road than OpenAI or Anthropic? https://assemblyai.com/aiexplained What does Gemini 3.5 Flash mean for the near-term future of AI?
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A new class of small models is emerging with the ability to reliably follow instructions and call tools while running on-device under 1 GB of memory.
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An eval platform is not just a test runner. You are building shared definitions of "good," reliable data pipelines, labelling workflows, versioning, and trust in results across many teams and model changes.
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GitHub operates one of the most heavily-utilised MCP servers in the ecosystem, with over 4 million downloads of the stdio server alone. Discover the architectural decisions, technical challenges and lessons learned while building and scaling a remote MCP server on production infrastructure.
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MCPs are often flaky, face multiple security vulnerabilities, and are generally hard to scale. Most enterprises struggle to use more than single digit numbers of MCPs due to issues with security, observability, and access control.
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A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features.
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April 21, 2026 - all times in EST -- 9:00am - Welcome to Day 2 -- 9:10am - David House, G2i Transforming Programming Mindsets: Case Studies in Agentic Coding Adoption -- 9:35am - Sarah Chieng, Cerebras Help!
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AI Engineer session on Principles for Prompt Engineering - Karina Nguyen (Claude Instant @ Anthropic). It adds practical context for how teams are building and operating AI systems in production.