Following the Antwerp Summit, CEO Cameron Price argues for keeping technical complexity under the hood while enabling business teams to build with governed data As AI changes how organizations make and automate decisions, Data Tiles Founder & CEO Cameron Price says the starting point for creating data products needs to change. Speaking at the 3rd

Northeastern University professor Raymond Fu has a knack for transforming fundamental research into successful commercial ventures.  He’s almost got it down to a science.  Since joining the university in 2012, he has spun out more than four technology startups out of Northeastern University’s Synergetic Media Learning Lab, which focuses on big data, artificial intelligence and

OpenAI recently announced that it tapped AI to solve the regularity problem of the Navier-Stokes equations, which describe the movement of liquids and gases. The news sparked controversy within the mathematical community, raising questions about the role of humans and AI tools in math research, as well as academic conduct, priorities and attribution. Navier-Stokes is

Silicon Valley's next big AI idea is probably already sitting in a 1991 paper by Sakana AI's new chief advisor. The Tokyo-based startup has hired Jürgen Schmidhuber, whom it calls the "father of modern AI," as Chief Scientific Advisor. Sakana credits him with early work on world models in 1990 and with the 1991 deep

Breast cancer screening must balance diagnostic accuracy with workflow throughput. DM remains the traditional cornerstone, but its two-dimensional projection creates tissue-overlap noise, particularly in dense breasts, leading to false positives and obscured lesions. Ultrasound (US) is widely used as an adjunct because it is sensitive to soft-tissue masses in dense parenchyma, yet it is operator-dependent

Brain gives people and AI agents a shared, persistent company memory, alongside tools for deploying agents and controlling what each person and agent can see and do. Businesses have no shortage of AI tools to choose from. The harder problem is getting those tools to understand the business they are supposed to work for. A

New York University (NYU) researchers have trained an AI model to learn chemical patterns associated with stability in drug-like molecules and accurately predict where their hydrogen atoms should be positioned. The team’s research, headed by Yingkai Zhang, PhD, professor of chemistry at NYU, addresses a longstanding challenge in molecular design and drug discovery, which is

A digital twin used to mean a detailed 3D replica that updated slowly and told you what had already happened. That definition no longer holds. From 2025 into 2026, digital twins have shifted from passive visualization tools to systems that predict, reason, and, in some cases, act on behalf of the physical assets they represent.