Liquid AI Releases LFM2.5-VL-3B: A 3B Vision-Language Model That Reads Screens, Grounds Objects, and Calls Tools On-Device

Yesterday, Liquid AI released LFM2.5-VL-3B. It is a 3.1B-parameter vision-language model built for on-device deployment. The model reads digital screens across mobile, web, and desktop. It grounds objects to coordinates, parses documents and charts, and calls tools from text or image input. Liquid AI reports an average of 69.4 across 28 vision benchmarks. That matches…

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CDA moves to unlock Islamabad’s property revenue

The Capital Development Authority (CDA), as the principal planning, development and municipal authority of Islamabad, has a substantial opportunity to strengthen its financial position without relying primarily on the disposal of additional prime land. A potentially significant source of revenue lies within Islamabad’s existing built environment: commercial and residential properties with unresolved construction, completion certification,…

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Ford authorities mum on whether or not it’s going to provide replace on its 1.5M properties aim

Ford authorities mum on whether or not it’s going to provide replace on its 1.5M properties aim

The Ford authorities is mum on whether or not it’s going to proceed to replace a once-signature housing tracker lower than three years after first introducing it as an try to encourage municipal governments to construct properties sooner. In August 2023, the Ford authorities started setting targets for the variety of new properties in cities…

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From In-Silico to Wet-Lab: Evaluating AI Protein Design Performance

In this tutorial, we use Anthropic’s claude-protein-binder-design dataset, which contains 1,440 AI-designed miniprotein binders tested against 16 targets. Because the release includes both computational predictions and real wet-lab results from two independent labs, we can go beyond simply studying the designs. We evaluate how well structure predictors identify successful binders, whether combining predictions improves performance,…

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