Designing and deploying DSPs FPGAs aren’t the only programmable hardware option, or the only option challenged by AI. While AI makes it easier to design DSPs, there are rising complexities due to the ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has developed a surface code quantum simulator based on FPGA. This innovative technology marks a new ...

Neural Concept is helping launch products at 2X the speed. It does this by capturing past knowledge into AI-based ...

Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...

DIY Download launches engineered growth infrastructure for Etsy, KDP, and POD founders, providing high-velocity market ...

The EU is threatening to take action against the social media company. It could be the start of a global reckoning. Katie is a UK-based news reporter and features writer. Officially, she is CNET's ...

Efficient artificial intelligence (AI) hardware is crucial for resource-constrained applications such as healthcare and transportation, where it enhances performance, reduces costs, and supports ...

Wale says the modern music landscape is forcing artists like him into a nonstop battle with social media and streaming algorithms just to be heard. During his appearance on Million Dollaz Worth of ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Designing a complex electronic device like a delivery drone involves juggling many choices, such as selecting motors and batteries that minimize cost while maximizing the payload the drone can carry ...

For years, quantum computing sat at the far edge of most strategic roadmaps—important someday, but not urgent now. In 2025, that excuse is gone. Breakthroughs on four separate fronts—bigger and better ...

Abstract: The exploitation of fuzzy techniques in machine learning for modelling uncertainty is highly versatile and widespread. In addition to providing a suitable fuzzy algorithm, its hardware ...