It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in ...

This brute-force scaling approach is slowly fading and giving way to innovations in inference engines rooted in core computer ...

Smaller models, lightweight frameworks, specialized hardware, and other innovations are bringing AI out of the cloud and into ...

Today, we’re proud to introduce Maia 200, a breakthrough inference accelerator engineered to dramatically improve the ...

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" that solves the latency bottleneck of long-document analysis.

AI inference at the edge refers to running trained machine learning (ML) models closer to end users when compared to traditional cloud AI inference. Edge inference accelerates the response time of ML ...

Red Hat Inc. today announced a series of updates aimed at making generative artificial intelligence more accessible and manageable in enterprises. They include the debut of the Red Hat AI Inference ...