Love is in the air for the vinegar fly. Drosophila melanogaster has long been a model for understanding how brains translate sensory information into courtship behavior. Male flies perform a multitude ...

Apple (AAPL) rated Sell: overvaluation, slowing innovation, iPhone dependence, a weak AI strategy, and Vision Pro flop. Read here for more analysis.

Computer Solutions East has earned Microsoft’s Solution Partner designation for Modern Work, recognizing expertise in ...

PHILADELPHIA, PA, UNITED STATES, February 4, 2026 /EINPresswire.com/ -- MBA Candidate at Wharton and Former Apple ...

The acquisition comes at a time when interest in computer vision is at an all-time high, and early experimentation has transitioned to full scale deployments with proven ROI. Standard AI has achieved ...

The Financial Times hit an Apple news home run over the holiday season with claims the company has scaled back its Vision Pro marketing and production efforts. It’s possible this could reflect Apple’s ...

Vision Pro 2 leaks suggest a late 2025 launch, positioning Apple at the forefront of Apple spatial computing. The new device is expected to feature M4 or M5 chips, doubling processing power to deliver ...

Apple has introduced two interesting ways to view photos across its platforms, Spatial Photos and Spatial Scenes, and each adds depth in its own way. Here are the differences and what you need to know ...

Apple is selling a new accessory for the Vision Pro headsets which happens to be the first spatial stylus for the device. Called the Logitech Muse spatial stylus, it offers exciting features for the ...

Muse is designed to make working, creating, and collaborating in visionOS more natural by blending precise motion tracking with tactile feedback. The stylus-like device supports six degrees of freedom ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Correlative imaging is a powerful analytical approach in bioimaging, as it offers ...

Spatial reasoning remains a fundamental challenge for Vision-Language Models (VLMs), with current approaches struggling to achieve robust performance despite recent advances. We identify that this ...