Screenshot from the new Inference Engine @AlpinDale is working on
LLMS
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Qwen 3.5 27B NVFP4 runs 5 agents full context under 20GB VRAM
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Qwen 3.5 27B in NVFP4 w/ full context taking less than 20GB VRAM You can basically run like 5 agents w/ full context on a single RTX PRO 6000 like this, and they'd be so fast Tell me I didn't tell you this was gonna happen
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Why Large Language Models Speak and Think Like Humans
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Why can large language models speak and think like humans? Link: https://
github.com/hangli-hl/AI-A
rticles/blob/main/.pdf
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Nature article warns against using AI as student ghostwriter
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Don’t let your students use #AI as a ghostwriter
by Yanjun Shen @Nature Learn more: https://
bit.ly/41QqUjd #MachineLearning #ArtificialIntelligence #EdTech -
India Builds Foundational AI for Indian Languages
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India is building its own foundational AI, trained on Indian languages, datasets, and contexts. Under the #IndiaAIMission, the IndiaAI Innovation Centre is developing multimodal models across text, speech, and vision, with deep support for Indian languages and domain-specific
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Grok 5 Model Ready: 1.5T Parameters, Public Release in Weeks
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SPEACEXAI : The next Grok model is expected to be ready for public release in 2-3 weeks. > 1.5T V9-Medium base model in comparison to 0.5T v8-Small, used for Grok 4.3
> Cursor data being used for supplementary training Grok 5? -
0.5T Model Open-Source Release Announced
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We will open source the 0.5T model towards the end of this year. It should still be quite useful.
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Local models’ progress from a year ago is amazing
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We've come so far from a year ago ngl People used to tell me it's impossible for local models to be where they're now They have no idea how good this thing will be
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EvalVerse: Expert-calibrated VLMs evaluate AI video quality
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Can AI-generated video ever match professional cinema? A team from HKUST, Tencent, and Stanford introduces EvalVerse. It treats video evaluation as a science—using expert-calibrated vision-language models to judge not just if the output follows the prompt, but also its
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DeepMind LLMs Lean Proof-Search Agents Solve Open Problems
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This new DeepMind research turns LLMs into Lean proof-search agents, so every step must compile and the final proof is mechanically verified. Under this setup, they solved 9 open Erdős problems, proved 44 OEIS conjectures, and helped advance actual research in optimization,