BrainWhisperer is Tether’s Brain-to-text project. Tether is earmarking resources to build technologies that push the borders of intracranial electrocortical decoding. The latest result is a variable ...

Healthcare is constantly being transformed by AI. With the advancement of GenAI, the healthcare and life science industries are enabling more intelligent decision-making through the latest ...

A mass of writhing maggots on a decomposing murder victim is not a sight for the squeamish, but for some, it is evidence. A maggot’s age and species can give essential information to forensic ...

Cambridge researchers map the convergence of biomarkers, digital phenotyping, and AI toward biologically grounded ...

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 ...

Sharplink, Inc. ( SBET) Q4 2025 Earnings Call March 9, 2026 8:30 AM EDT ...

The peer-reviewed invited review in Brain Medicine titled "New approaches to enhance the diagnosis of psychiatric disorders," is freely available via Open Access, starting on 10 March 2026 in Brain ...

It has strong reasoning, but it sometimes answers questions you didn't ask. Formatting and image generation lag behind the text quality. It's a new month, and a new AI version number. It's called ...

It’s a great, easy way to turn your handwriting into a font, but you can use it to create any typeface you can imagine as long as long as you have the adequate drawing skills. I tried it myself and it ...

Despite widespread industry recommendations, a new ETH Zurich paper concludes that AGENTS.md files may often hinder AI coding agents. The researchers recommend omitting LLM-generated context files ...

AI has designed candidate drugs for antibiotic-resistant infections and genetic diseases. But efforts to incorporate AI into the design of lipid nanoparticles (LNPs), the revolutionary delivery ...

To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...