Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .

Jan 10 (Reuters) - Elon Musk said on Saturday that social media platform X will open to the public its new algorithm, including all code for organic and advertising post recommendations, in seven days ...

While the creation of this new entity marks a big step toward avoiding a U.S. ban, as well as easing trade and tech-related tensions between Washington and Beijing, there is still uncertainty ...

Instagram is introducing a new tool that lets you see and control your algorithm, starting with Reels, the company announced on Wednesday. The new tool, called “Your Algorithm,” lets you view the ...

Social media companies and their respective algorithms have repeatedly been accused of fueling political polarization by promoting divisive content on their platforms. Now, two U.S. Senators have ...

Harrison Barnes used a visualization tool to help him improve. Illustration: Dan Goldfarb / The Athletic; Logan Riely / NBAE / Getty Images Editor’s note: This story is part of Peak, The Athletic’s ...

Service intelligence startup Neuron7 Inc. said today it has come up with a solution to solve the reliability challenges that prevent enterprises from adopting artificial intelligence agents. That ...

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...

A cycle-accurate alternative to speculation — unifying scalar, vector and matrix compute In dynamic execution, processors speculate about future instructions, dispatch work out of order and roll back ...

There’s been great interest in what Mira Murati’s Thinking Machines Lab is building with its $2 billion in seed funding and the all-star team of former OpenAI researchers who have joined the lab. In a ...

import torch @torch.compile(backend="inductor") def fn(src, index, base_tensor): src = src + 10 torch.use_deterministic_algorithms(True) base_tensor.scatter_(0, index ...