Broad availability:
IBM http://
watsonx.ai + partners including Dell, Docker Hub, Hugging Face, Kaggle, NVIDIA NIM, LM Studio, Ollama, Replicate & more. Azure AI Foundry and AWS SageMaker support coming soon.
Huggingface: https://
shorturl.at/yaopH
Ollama:
SOFTWARE
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IBM watsonx.ai expands availability across major cloud platforms
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Granite-4.0-H Model Lineup: 32B Small to 3B Micro
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3/ Models in the lineup: Granite-4.0-H Small → 32B params (9B active), ideal for agents & support automation
Granite-4.0-H Tiny → 7B (1B active), low-latency + edge use
Granite-4.0-H Micro → 3B dense hybrid
Plus a 3B transformer-only Micro -
Granite 4.0 Hybrid Mamba Transformer Cuts GPU Memory 70%
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Granite 4.0 introduces a hybrid Mamba + transformer architecture. Cuts GPU memory needs by up to 70% Runs on cheaper hardware Faster inference, even with long contexts or multiple sessions
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IBM Granite 4.0: Hybrid LLM for Enterprise Efficiency
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🚨 IBM just dropped Granite 4.0 — hybrid Mamba/transformer LLMs built for enterprise efficiency.
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 3 octobre 2025
✅ Up to 70% less RAM
✅ ISO 42001 certified & cryptographically signed
✅ Open-sourced + cheaper GPUs
Here’s why it matters 👇🧵 pic.twitter.com/4jtcWHzOwRIBM just dropped Granite 4.0 — hybrid Mamba/transformer LLMs built for enterprise efficiency. Up to 70% less RAM ISO 42001 certified & cryptographically signed Open-sourced + cheaper GPUs Here’s why it matters
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Platform Consolidation: Enterprise AI Operations Across All Functions
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We've refined the process and the platform. We now basically live in the platform—we do all our sysadmin work in it, host production apps in it, develop most of our software in it, our legal team does contract drafting in it, we iterate on GUIs in it, etc.
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Turning Chat Discussions Into Scalable Deployment Plans
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E.g before we built the scalable server farm for expanding the solveit platform, I chatted to my team about approaches we could take. You can see here a snippet of the dialog I used to turn that chat into a deployment plan—the transcript and style guide coming from variables.
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Iterative Code Learning Trial Generates Overwhelming Interest
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A year ago we ran a small trial titled "How To Solve It With Code". The response was so overwhelming that we closed signups after one day. We explored using our approach for very small iterations with constant feedback for web development, AI, business (with @ericries
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React Interactive Components Streaming Challenges Explained
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Another thing to add here, which makes it more complex, is that it has interactive components with states and props. I wish I showed in that video.
Which makes it much harder to do vs just stream a React component that wraps an HTML element. -
MagicPath Adds reui_io Design Library for Product Development
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We just added @reui_io, another beautiful library inside of MagicPath to get you started designing and building your next product. pic.twitter.com/uUbcOBIF4K
— Pietro Schirano (@skirano) 2 octobre 2025We just added @reui_io
, another beautiful library inside of MagicPath to get you started designing and building your next product. -
Snorkel AI scales ML workflows 20x faster with Prefect
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Snorkel AI’s ML Foundations team runs tens of thousands of workflows daily with @PrefectIO OSS—20x faster throughput, less tech debt, and tools engineers love using. Read more from our Principal Engineer Smit Shah!