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news.ycombinator.com• Jun 9, 2025• 1 min read

China Will Win at AI Because of ElsevierAI models don’t just need raw text—they need deep, structured, peer-reviewed knowledge to reason about science, medicine, engineering, and more. But most of that knowledge in the West is locked behind paywalls run by publishers like Elsevier.Elsevier doesn’t just sell access to human readers. It aggressively enforces licenses that prohibit text and data mining for machine learning. Even universities that pay for journal access often find their AI research groups barred from using that content to train models. The terms are clear: you can read the paper—but your model can’t.Meanwhile, China ignores these restrictions. Its researchers operate with centralized access to nearly every major Western journal. In many cases, they use institutional mirrors, semi-legal repositories, or just direct scraping. Tools like Sci-Hub are quietly tolerated or integrated into internal systems. Whether legal or not, the outcome is clear: China’s models are learning from the full scientific corpus.In the We

news.ycombinator.com• Dec 2, 2024• 1 min read

Ask HN: Is widespread use of non-commercial datasets an open secret in startups?I'm asking outside of language models. Aside from foundational models, I still see small companies with very specific goals, but even niche offshoots at bigger companies. One still needs data sets for performant, custom models. Collecting that data can be a hindrance, but some companies succeed anyway, with no appearance of data collection efforts. This is true for language, vision, etc.I suspect that many of these are bootstrapped with pretrained models, many of which surprisingly do have non-commercial licenses or were trained with non-commercially licensed data sets.So is it an open secret that companies just suck up whatever they can get their hands on anyway? Perhaps the legal landscape is still so grey?

bing.com• Sep 7, 2024• 1 min read

Texas game wardens seize red snappers well over bag limit on Brazos River, 50 citations issuedWith the beginning of the new Texas hunting and fishing season at the start of month, it’s important for residents who hunt and fish to renew their licenses and know the rules, because Texas game ...

news.ycombinator.com• Aug 18, 2024• 1 min read

Show HN: BI-LLM democratize data analysisHi HN! BI-LLM (https://github.com/amVizion/BI-LLM) automates data analysis workflows on semi-structured data. The assumption is that many decisions could be led by data, but instead are made by intuition because doing analysis would be too slow or expensive. The sweet-spot is decisions based on a few hundreds to a couple thousand items: too many to analyze manually, too few to dedicate an analyst to it. I believe that powerful insights are derived from a large number of data-driven decisions.There are 3 things special about BI-LLM:1. Web-native: the code is fully developed on TypeScript. A native integration with web, avoids the need for specialized software, or licenses. More importantly, I hope it contributes opening the field of AI to a wider group of developers.2. Runs-locally: BI-LLM uses a combination of statistical, machine-learning, and GenAI methods to automate the analysis. Embedding models run in TensorflowJS, and LLMs in Ollama. Running locally not only helps keeping costs

news.ycombinator.com• Mar 11, 2024• 1 min read

Ask HN: Should the US pass sweeping restrictions on AI development?https://time.com/6898967/ai-extinction-national-security-risks-report/According to this government-commissioned report, AI at its current SOTA frontier represents an unprecedented existential risk to humanity. The best course of action, according to its authors, is for the United States to restrict compute on training models and punish open-sourcing weights with jail time.> The new AI agency should require AI companies on the “frontier” of the industry to obtain government permission to train and deploy new models above a certain lower threshold, the report adds.> Authorities should also “urgently” consider outlawing the publication of the “weights,” or inner workings, of powerful AI models, for example under open-source licenses, with violations possibly punishable by jail time, the report says.> And the government should further tighten controls on the manufacture and export of AI chips, and channel federal funding toward “alignment” research that seeks to make advanced AI safer, it