Google Unveils TurboQuant Compression Algorithm Recently, Google introduced a new compression algorithm known as TurboQuant.

Because video clips are made up of sequences of individual images, or “frames,” video compression algorithms share many concepts and techniques with still-image compression algorithms. Therefore, we ...

Video compression has become an essential technology to meet the burgeoning demand for high‐resolution content while maintaining manageable file sizes and transmission speeds. Recent advances in ...

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Google's new TurboQuant algorithm could slash AI working memory by 6x, but don't expect it to fix the broader RAM shortage ...

Suffix arrays serve as a fundamental tool in string processing by indexing all suffixes of a text in lexicographical order, thereby facilitating fast pattern searches, text retrieval, and genome ...

Large Language Models (LLMs), often recognized as AI systems trained on vast amounts of data to efficiently predict the next part of a word, are now being viewed from a different perspective. A recent ...

CompareAI is the first iOS app to enable experimentation with a library of state-of-the-art Deep Learning-based image compression algorithms on real world, resource-limited devices WILMINGTON, Del., ...

There are a thousand reasons to hate hopping on a video call every 10 minutes to chat with your co-workers, among them the ugly video compression artifacts that can occasionally make your face ...

In a nutshell: Stable Diffusion is a phenomenal example of how much a picture is worth more than a thousand words. In fact, by cutting the image-generation text prompt altogether, the visual AI could ...

The Apple acquisition of WaveOne gives the conglomerate similar capabilities, though the kind of services it builds on top of its AI-driven video compression remains unknown. Nevertheless, the move ...

Signal compression is an appealing technique to use in mixed-signal ATE (automated test equipment) systems because it can reduce the cost of test while improving tester performance. Unfortunately, ...