Show HN: One-script installer for TRELLIS.2 on Nvidia Blackwell under WSL2
Article URL: https://github.com/Creepybits/trellis2-blackwell-wsl Comments URL: https://news.ycombinator.com/item?id=50403233 Points: 1 # Comments: 0
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待评分 · 分类列表推荐Article URL: https://github.com/Creepybits/trellis2-blackwell-wsl Comments URL: https://news.ycombinator.com/item?id=50403233 Points: 1 # Comments: 0
Hello everyone, I'm BIOcanse.Windows Task Manager has inaccurate readings and limited monitoring items. Various hardware adjustments are also very separated—CPU, GPU, and fans all require their own individual software. Their interfaces and interactions are primitive, and they often overwrite each other's configurations. Moreover, driver management of the CPU and GPU is too clumsy, and the memory usage issue on Windows is also very serious. So I made Resource Manager to view and manage all these resources in one place, making monitoring and scheduling work seamlessly together.Monitoring:This software integrates almost every possible monitoring item, letting you look at your computer from a God's-eye view!Scheduling:One of the core features. It uses algorithms I wrote to optimize memory usage and reasonably schedule processes across multiple CPU cores. It also supports GPU scheduling, which means it can switch the GPU a program uses while it is running. For example, after launching a game, if GPU usage is high or VRAM is about to overflow, it will move the remaining software to another GPU (for most personal computers, this is usually the integrated GPU).Reporting:Many times, computer performance problems are actually just caused by a single program or driver—the benefits of 100 programs optimizing themselves cannot make up for a memory leak in just one program. The reporting page reports abnormal resource usage (CPU, GPU, memory, VRAM, disk read/write, network traffic, and causing system interruptions).Hardware Adjustment:All the parameters you can think of for hardware like the CPU and GPU can be adjusted here. However, my own setup is an AMD CPU + NVIDIA GPU, so other setups still need to be verified. I do have several computers with Intel CPUs to verify Intel CPU support, but I really do not have a single AMD GPU. Although most of it uses mature open-source dependencies, there may still be risks, so please use it with caution. Comments URL: https://news.ycombinator.com/item?id=50380521 Points: 1 # Comments: 0
This repo provides an alternative to the ontology compiling capabilities of NVIDA Auto-Ontology.The main difference is that it builds the ontology from most of your existing data assets (transformation code, dashboards, docs), instead of building it from your warehouse and semantic layer only.It consists in skills and python scripts that ingest the metadata and docs your team already has, and compile them into YAML and Markdown files structured in a file tree that an agent can use as context to query your data.When your existing asset contradict, or reveal a gap in the business context around your data, it writes down questions for you and your team instead of guessing a plausible meaning.It runs locally in any coding agent. Comments URL: https://news.ycombinator.com/item?id=50363667 Points: 1 # Comments: 0
Cities generate enormous amounts of data from cameras, sensors and operational systems, but turning it into useful action — for planning, maintenance and public services — remains a challenge. Physical and agentic AI offer new ways to close that gap, from digital twins for infrastructure planning to vision and service agents, while keeping local governments […]
General Compute is betting on inference chips from outside the Nvidia ecosystem.
Jensen Huang is still struggling to prop up the Neocloud wall, while Musk has already predicted its collapse. The first domino in the AI bubble may well be among these companies. On October 25, Musk issued a warning on X: in recent weeks, the debt markets have virtually stopped extending financing to firms that lack substantial revenue streams beyond their AI data centers. He forecast that more than 200 Neocloud players will face “guppy‑level” deaths and consolidation, with only a handful ultimately surviving. Yet just three days earlier, NVIDIA CEO Jensen Huang offered a nearly opposite assessment. On October 22, during an interview with CNBC, Huang insisted that demand for Neocloud computing power remains extremely robust; the real bottleneck is insufficient working capital, and funding challenges will eventually be resolved. Both men remain optimistic about the demand for AI compute, but they differ sharply on how to manage the business of renting out computing power...
Issue 958 of “The Sequence Radar” examines inference software, modular AI factories, and enterprise AI investments side by side: cheaper per-inference does not necessarily mean lower overall industry spending. This article is compiled from the original publication and supplemented with technical scope and delivery terms based on DeepSeek and NVIDIA’s official materials.
The Verge published a satirical, fictional article claiming that SpaceX and Tesla have formed a special committee to discuss a merger, even jokingly mentioning speculative details such as SpaceX planning to borrow $40 billion to purchase NVIDIA chips. The piece contains no factual basis and is presented as humorous commentary on AI and tech culture.
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