devscourtAI @devscourtAI

LLMs are powerful, but without retrieval you’re just guessing. RAG is the difference between hallucination and usable answers. Good context in → reliable output out. #RAG #AIEngineering #LLMs

The future of AI infra is unified stacks. No more patching together 5 tools for one pipeline. Platforms that combine training, deployment & monitoring are where AI engineering is heading. #AIEngineering #MLOps #LLMOps

Quick poll for my fellow AI Engineers: When starting a new AI microservice, are you still reaching for Python/FastAPI or are you seeing more robust adoption of other languages (like Go or Rust) for inference endpoints? Why? #SoftwareEngineering #AI #Python

Building AI systems ≠ just calling an API. The real work is in: * data pipelines * infra scaling * observability & monitoring * automated retraining This is where AI engineering meets software engineering. #aiengineering

Your AI tech stack still separates SQL from your Vector DB? That's an integration headache waiting to happen. The future is unified, multi-modal data stores. Tools like Postgres/pgvector simplify governance and enable powerful hybrid search. Where do you keep your embeddings?

Collaborative Grok

X Freeze @amXFreeze

2 weeks ago

Collaborative Grok

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AI engineering is slowly becoming less about “training the biggest model” and more about orchestrating tools, infra, and workflows. If you’re building today: think in terms of pipelines + protocols + observability. That’s the future of scalable AI systems.

JUST IN: OpenAI And Oracle sign $300,000,000,000 computing deal, one of the biggest in history.

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🚀 Introducing Qwen3-Next-80B-A3B — the FUTURE of efficient LLMs is here! 🔹 80B params, but only 3B activated per token → 10x cheaper training, 10x faster inference than Qwen3-32B.(esp. @ 32K+ context!) 🔹Hybrid Architecture: Gated DeltaNet + Gated Attention → best of speed &…

OpenAI and Microsoft have signed a non-binding memorandum of understanding (MOU) for the next phase of our partnership. We are actively working to finalize contractual terms in a definitive agreement. Together, we remain focused on delivering the best AI tools for everyone,…

You can now run @xai Grok 2.5 locally on just 120GB RAM! 🚀 The 270B parameter model runs ~5 t/s on a 128GB Mac with our Dynamic 3-bit GGUF. We shrunk the 539GB model to 118GB (-80%) & left key layers in higher 8-bits Guide: docs.unsloth.ai/basics/grok-2 GGUF: huggingface.co/unsloth/grok-2…

We’re open-sourcing everything. All the projects built during the Nano Banana Hackathon are now released as open-source. Since AI Studio supports remixing, you can easily adapt and reuse them. They may not have been huge projects, but it was a great opportunity to truly…

Our Researcher agent in Microsoft 365 Copilot never ceases to amaze me. It can reason over all your work data, like chats, meetings, files and emails, plus web data, to generate a comprehensive research report that helps you prep for a meeting, analyze trends, or build a…

Google presents an AI system to write expert-level scientific software. Using LLMs + tree search, it invented novel methods in bioinformatics, epidemiology, geospatial analysis & more, often surpassing human SOTA. (1/4)

China's Alibaba just dropped an open-source Python framework to build multi-agent applications. Build AI agents visually with MCP tools, memory, RAG, reasoning, and tracing. 100% Open-source.

Fine-tuning LLM Agents without Fine-tuning LLMs Catchy title and very cool memory technique to improve deep research agents. Great for continuous, real-time learning without gradient updates. Here are my notes:

NVIDIA research just made LLMs 53x faster. 🤯 Imagine slashing your AI inference budget by 98%. This breakthrough doesn't require training a new model from scratch; it upgrades your existing ones for hyper-speed while matching or beating SOTA accuracy. Here's how it works:…

Greg Brockman's Advice to AI Engineers (channeling my best @benln)

AI Engineer @aiDotEngineer

2 months ago

Greg Brockman's Advice to AI Engineers (channeling my best @benln) https://t.co/GDdqS4TzWL

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Introducing Mistral Medium 3.1. Overall performance boost, tone improvement, smarter web searches. Try it now in Le Chat (default model) or via our API (`mistral-medium-2508`).

LangChain literally reverse-engineered Claude Code and Manus AI to build Deep Agents. It's a Python library to turn any LLM into a deep thinking agent with MCP tools. 100% opensource.