Episodit
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advanced RAG techniques like RAPTOR and using Clues
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Cursor, RepoAgent, Aider, and some more coding agents - overview and interesting architectural concepts
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Puuttuva jakso?
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Technical review of the new Realtime API introduced on the dev day
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How to migrate the llm provider in your AI app safely
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If you need to build an llm-app that uses an open-source llm, this episode is for you. Intermediate level
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end to end guide on how to get started and deploy to production your llm app
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Build LLM-app with legal documents that have many references and domain verbiage
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Getting started with LangGraph, the most popular multi agent framework
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Utilize no-code tools for fast POCs
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Review of why and how to build a multi-agent system. Assaf is Head of R&D @ Wix and GPT-researcher open source creator.
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everything about adopting open source code and models for your llm app
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build trust with users and stakeholders - transparency and explainability, reliability and consistency (how to fail safely), automation vs user control.
how to evaluate with uncertainty, prompt engineering, effective bug reports -
examples and practices of advanced agents, and use of LangGraph for effective tool usage by agents
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how to solve latency issues with minimal compromise on quality and cost
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The 12 most common challenges around building an effective RAG pipeline and the best practices for solutions
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exploring the reranker component in the 2 stage retrieval system
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how to define effective requirements for llm apps, and first steps after going to production
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What are transformers, why it is so expensive to train a Transformer-based model and what is the architecture of the future LLMs
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LCEL, LangGraph, LangSmith
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Indexing knowledgebases with KG for RAG applications
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