Apple’s MacBook Pro 14-inch (M5) features the latest chip from the Cupertino company, and it's just been super-charged with newer, more powerful, M5 Pro and M5 Max chips.

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Alibaba Qwen 3.5 Small models run offline on phones and laptops; 0.8B and 2B sizes, with mixed reliability on hard tasks.

These new models are specially trained to recognize when an LLM is potentially going off the rails. If they don’t like how an interaction is going, they have the power to stop it. Of course, every ...

Artificial intelligence (AI) is transforming the way scientists discover and design new materials. In a specially invited review published in Angewandte Chemie International Edition, Tohoku University ...

Mosaic Clinical Technologies™, a wholly-owned subsidiary of Radiology Partners, is pleased to announce that Cognita™, its AI ...

OpenAI Group PBC today launched a new large language model that it says is more adept at automating work tasks than its earlier algorithms. GPT-5.4 is available in ChatGPT, the Codex programming tool ...

B, an open-weight multimodal vision AI model designed to deliver strong math, science, document and UI reasoning with far ...

As large language models (LLMs) gain momentum worldwide, there’s a growing need for reliable ways to measure their performance. Benchmarks that evaluate LLM outputs allow developers to track ...

Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.

Abstract: Large Vision-Language Models have drawn much attention and become increasingly applicable in complicated multimodal tasks such as visual question answering, video grounding, etc. However, it ...

Classifying geospatial imagery remains a major bottleneck for applications such as disaster response and land-use monitoring-particularly in regions where annotated data is scarce or unavailable.