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SOFTWARE
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PyTorch Compilation Strategy for Large-Scale Transformer Models
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1. there is no fork of pytorch fwiw. only a fork of nccl. clearly you overheard wrong.
2. torch.compile wasn't even considered because it doesnt have precompilation yet and that was deemed a requirement for large-scale xlformers runs. so the whole thing about graph breaks is -
iPad App for Creative Professionals Impresses Designer Community
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Yeah I feel like unreal or Maya ain’t going nowhere. But I do have an iPad and this app looks amazing – thank you!
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AI Studio GitHub Integration Launched
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BREAKING 🚨: Now you can connect AI Studio to GitHub and commit changes to your AI Apps without leaving a page.
— 🚨 AI News | TestingCatalog (@testingcatalog) 16 août 2025
Each AI Studio app will require a new repository to be created, and this feature seems to be already available.
Stealth rollout? 👀 pic.twitter.com/fNWpNwQrE9BREAKING : Now you can connect AI Studio to GitHub and commit changes to your AI Apps without leaving a page. Each AI Studio app will require a new repository to be created, and this feature seems to be already available. Stealth rollout?
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ScrapeCraft: AI-Powered Web Scraping with LangGraph
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ScrapeCraft: AI Web Scraping Editor Uses AI and LangGraph to power intelligent web scraping with automated code generation and real-time data streaming. Simplifies complex scraping workflows through bulk URL support. Check it out! https://
github.com/ScrapeGraphAI/
scrapecraft
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Apache Spark 4.0 transformWithState API for Operational Monitoring
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Learn to build operational monitoring pipelines using Apache Spark™ 4.0's new transformWithState API This blog walks through how to use the new transformWithState API to:
-Track, alert on, and analyze sensor data with ValueState, ListState, and MapState
-Set up time-based state -
Axolotl: YAML-based LLM fine-tuning and LoRA optimization framework
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4. Axolotl • Yaml-based setup for fine-tuning, LoRA/QLoRA, DPO, GRPO, and multimodal workflows
• Includes kernel optimizations for memory-efficient training GitHub repo: -
DeepSpeed: Distributed Fine-Tuning Framework for Large Language Models
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3. DeepSpeed • Built for large-scale distributed fine-tuning with ZeRO and FSDP
• Optimized for multi-GPU and multi-node training with advanced memory management
• Trusted in production environments for scalable LLM training GitHub repo: -
Unsloth AI: Fast LLM Fine-tuning with 70% Less VRAM
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1. Unsloth AI • Fine-tune models like Qwen3, Llama 4, and Gemma 3 up to 2× faster with 70% less VRAM
• Supports low-resource setups and runs on consumer GPUs or even Colab/Kaggle with ~3 GB VRAM GitHub repo: -
Jupyter Notebooks in Production: The AI Prehistory New Experts Ignore
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95% of the new "AI experts" on LinkedIn never experienced the good old days when some people wanted to put Jupyter Notebooks into production. That was the real prehistory of AI: explaining to managers that, well, no, we don't do that… Just because MNIST runs.