Why Large Hadron Collider predictions can miss the mark, and a new way to fix it

Estimating things that exist is generally easy, but when it comes to estimating things that do not exist, it's more difficult. This is something physicists from Poland and the UK are well aware of. To ...
EurekAlert!

Better understanding of the unknown leads to more accurate collision simulations

Estimating things that exist is generally easy, but when it comes to estimating things that do not exist, it’s more difficult. This is something physicists from Poland and the UK are well aware of. To ...

Large genome model: Open source AI trained on trillions of bases

Late in 2025, we covered the development of an AI system called Evo that was trained on massive numbers of bacterial genomes. So many that, when prompted with sequences from a cluster of related genes ...

Letting atomic simulations learn from phase diagrams

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...

Mathematicians explain AI’s intelligence: It’s all about patterns, not thinking

Explore how core mathematical concepts like linear algebra, probability, and optimization drive AI, revealing its ...
Tech Xplore

AI energy use: New tools show which model consumes the most power, and why

AI users and developers can now measure the amount of electricity various AI models consume to complete tasks with an ...
Mashable

10 cool examples of Project Genie, the AI world model that sent video game stocks diving

Google rolled out a brand new experimental AI tool last Thursday called Project Genie. By Friday, video game stocks were tumbling as a result. Gaming industry giants like Unity Software, Roblox, ...
CNET

How Smart Do We Want AI to Be? World Models May Understand Things Better Than We Do

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world. Barbara is a tech writer specializing in AI and emerging technologies. With a ...
eLife

Generation of biophysical neuron model parameters from recorded electrophysiological responses

This study is a valuable contribution to the field of neuronal modeling by way of providing a method for rapidly obtaining neuronal physiology parameters from electrophysiological recordings. The ...
ascopubs.org

Development, External Validation, and Deployment of RFAN-ML: A Machine Learning Model to Estimate Renal Function After Nephrectomy

Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor ...
InfoWorld

Perplexity’s open-source tool to run trillion-parameter models without costly upgrades

TransferEngine enables GPU-to-GPU communication across AWS and Nvidia hardware, allowing trillion-parameter models to run on older systems. Perplexity AI has released an open-source software tool that ...