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Bloomberg: Local opposition disrupted 45 US data center projects worth $68B during Q2 That was below Q1’s record 75 projects and roughly $130B https://t.co/F6MLBs7KAt https://t.co/TsaqamFlkZ

Jensen Huaan: The data-center industry failed to engage communities early enough. "water consumption, that's a myth now. these data centers use less water evaporative. They don't use evaporation anymore. It uses less water than a swimming pool evaporating all year long." newer data centers recycle their cooling water, use much less evaporation. He says operators can also add power generation, make the grid stronger, lower electricity costs, and create the economic demand needed for solar, hydro, fission and fusion projects. ---- From "CBS Sunday Morning" YouTube channel, (full video link in comment)

wow, this is really something coming from Terence Tao. "We can afford to be slower than this. And seriously, where we are now is not right." Looks like AI entered the club of mathematical geniuses without asking permission. 🤔 “Okay, fine, they’re (AI) solving major conjectures and so forth left and right, but they’re not actually creating any value. Or whatever they have is much, much worse, much weaker than what it could have been if it was done in a leisurely, principled manner. And, you know, these problems, "Navier stroke" we don’t urgently need them next week. This is not something that we need to cram on. This is not a major world-crisis-type situation. We can afford to be slower than this. And seriously, where we are now is not right.” --- (Terence Tao's keynote at the Science x AI Summit at Caltech, from "SAIR" YouTube channel, (full video link in comment)

Full video https://t.co/zRj00PrsdQ

this will be a common statement from many elite specialists from almost all intellectual fields, once AI starts doing the field’s prestige work. "we have to slow down. This is insane, the pace and there's no reason to be this fast. There's no reason at all." - Terence Tao's keynote at the Science x AI Summit at Caltech: top experts welcome AI as a tool, then ask it to slow down the moment it starts producing results they used to own. ---- From "SAIR" YouTube channel, (full video link in comment)

JEV

Day-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24GB with CPU offload - 1024×1024 generation in 18.7s and image editing in 21.7s with 22.7 GiB peak GPU memory during requests. - On an RTX PRO 6000 96GB: 8.0s generation and 9.6s editing. 🎨 Text-to-image, multi-image editing, and transparent RGBA output—all with one checkpoint. ⚡ Native inference with TP/SP, LoRA, and OpenAI-compatible APIs. 40 denoising steps, one image per request, warmed HTTP latency including PNG output. No quantization. Cookbook and GPU-specific commands below 👇

Qwen Image 2.1 is here! 🖼️ A 7B params native image generation and editing model, with up to 10 image references The model comes with it's own prompt enhancement LLMs, integrated with diffusers 🧨 and ComfyUI ▶️ on Spaces https://huggingface.co/spaces/hugging-apps/qwen-image-2-1