GenAI Use Cases A comprehensive RAG pipeline repository for internal documentation processing, featuring multiple LLM support, ChromaDB integration, and both notebook/production implementations using LangChain. Check out this practical guide https://
github.com/rguthaa/genai-
usecases/tree/main
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LLMS
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RAG Pipeline Repository for Internal Documentation Processing with LangChain
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Dario Amodei on 100 Million Word Context Windows and In-Context Learning
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"Une fenêtre de contexte de 100 millions de mots est tout à fait possible.
— VISION IA (@vision_ia) 2 août 2025
Les modèles apprennent effectivement pendant la fenêtre de contexte, sans que leurs poids ne soient modifiés."
– Dario Amodei, PDG d’Anthropic
(Sur le deuxième point, un excellent article de Google… pic.twitter.com/1HkiyIGkXC"Une fenêtre de contexte de 100 millions de mots est tout à fait possible. Les modèles apprennent effectivement pendant la fenêtre de contexte, sans que leurs poids ne soient modifiés." – Dario Amodei, PDG d’Anthropic (Sur le deuxième point, un excellent article de Google
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100+ Free Step-by-Step AI Agent Tutorials with Code
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100+ free step-by-step tutorials with code covering: AI Agents RAG Systems Voice AI Agents MCP AI Agents Multi-agent Teams Autonomous Game Playing Agents P.S: Don't forget to subscribe for FREE to access future tutorials.
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DeepSeek Scientific Model Reaches 40.44% on HLE Benchmark
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And here we go again: a finetuned DeepSeek scientific model allegedly achieved 40,44% on HLE
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Google Launches Gemini Deep Think: Advanced Reasoning AI
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Google just dropped a major upgrade: Gemini Deep Think It doesn’t just give answers—it reasons, tests multiple ideas in parallel, and picks the best one. Think chess grandmaster meets creative strategist.
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Deep Think Outperforms Gemini 2.5 Pro on Major Benchmarks
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Deep Think beats Gemini 2.5 Pro across key benchmarks: Coding (LiveCodeBench) Multimodal tasks (MMMU) Advanced math (USAMO) It’s already live for AI Ultra users in the Gemini app—$250/month if you want early access.
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Build Full-Stack LLM Web Apps Entirely in Python with Reflex
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Build full‑stack LLM web apps in pure Python! Reflex is a Python framework that lets you build web apps with both frontend and backend entirely in Python. It’s 100% open source.
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China’s XBAI-o4 Medium Achieves Impressive Benchmark Results
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China is doing it again: holy moly! XBAI-o4 Medium: •Parameter: 32,8 B
•Training: Long‑CoT RL + Process Reward Learning (SPRM)
•Benchmarks (High‑Modus):
•AIME24: 86,5
•AIME25: 77,9
•LiveCodeBench v5: 67,2
•C‑EVAL: 89,7 -
AI Assistants Need Structure: JSON for Predictable, Fast Results
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1/ AI is a picky assistant. Give it a vague prompt, and it might give you:
• A list
• A paragraph
• A random poem But give it structure with JSON?
You get predictable results. Fast. -
Why JSON Works: Speak AI’s Native Language
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2/ Why JSON works:
AIs are trained on millions of JSON examples.
It’s like speaking their native language. Instead of this:
"Summarize this email" Try this:
{ "task": "summarize", "email": "[INPUT FULL EMAIL]", "format": "list"
}