(بشير) bachir

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(بشير) bachir

(بشير) bachir

@bachiirc

Ph.D., Data and ML 🇩🇿

El Oued 가입일 Eylül 2007
261 팔로잉184 팔로워
(بشير) bachir
(بشير) bachir@bachiirc·
🚀 Gemini Headless is a game-changer for server-side AI automation at scale: 🔹 Built for headless server automation 🔹 Zero-deadlock background I/O piping 🔹 High-throughput parallel execution 🔹 Fully async & type-safe google-gemini.github.io/gemini-cli/doc…
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GitHub
GitHub@github·
If Copilot is: - creating unnecessary tests - writing messy legacy code - not following your instructions
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(بشير) bachir
(بشير) bachir@bachiirc·
AGENTS.md just dropped and it’s a big step for standardization: an open, clean format for coding agents! 🔥 With a community led by OpenAI, with teams from Factory, Cursor, Jules team from Google, Roo Code, and more. 🔗 agents.md #agentic #LLM
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(بشير) bachir
(بشير) bachir@bachiirc·
New lib for asynchronous and composable AI Pipelines ⛓️ Chaining (+) or Parallelizing (//) processors. 🔌 Integrates with Gemini and Gemini Live APIs. 🚀 Orchestrate concurrent tasks with asyncio. 🖼️ Diverse content: text, images, audio, and PDFs. developers.googleblog.com/en/genai-proce… #genai
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Lior Alexander
Lior Alexander@LiorOnAI·
The whole system prompt of Claude has been leaked on GitHub, 24,000 tokens long. It defines model behavior, tool use, and citation format.
Lior Alexander tweet media
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(بشير) bachir
(بشير) bachir@bachiirc·
Microsoft just released BitNet an inference framework for 1-bit #LLMs so you can run a 100bn BitNet b1.58 model on a single CPU 🤯It achieve speeds comparable to human reading (5-7 tokens per second) and it is perfect for local devices 👉 github.com/microsoft/BitN…
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(بشير) bachir
(بشير) bachir@bachiirc·
Google hard dataset for evaluating RAG applications: 🐇 evaluating a multi-hop rag application 🔖 benchmarking a language model on reasoning an factuality Baseline results range 41% for basic prompting up to 66% for multi-step retrieval & reasoning. huggingface.co/datasets/googl…
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(بشير) bachir
(بشير) bachir@bachiirc·
Practical RAG (i) Use semantic (aka vector database) and keyword search (ii) Situate the chunks of the doc in the greater context by summarizing the role they play (iii) More chunks are usually better (eg. 20 chunks) (iv) Rerank the chunks. anthropic.com/news/contextua…
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(بشير) bachir
(بشير) bachir@bachiirc·
OpenAI released an evaluation dataset 🌍 14 languages: Arabic, Spanish,…. 🧠 57 subjects: elementary to advanced professional 🎓 translated by professional translators 🔬 Evaluates general knowledge across diverse cultures, used in openai/simple-evals huggingface.co/datasets/opena…
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(بشير) bachir
(بشير) bachir@bachiirc·
The future is running your own AI cluster at home with your own everyday devices. Check how to run a Llama 3.1 405B model on MacBooks with exo 🤯 github.com/exo-explore/exo
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