Nvidia, which is being seen as the ‘undisputed king’ of the AI hardware boom (specifically Graphic Processing Units, or GPUs) ...
XDA Developers on MSN
Docker Model Runner makes running local LLMs easier than setting up a Minecraft server
On Docker Desktop, open Settings, go to AI, and enable Docker Model Runner. If you are on Windows with a supported NVIDIA GPU ...
CES used to be all about consumer electronics, TVs, smartphones, tablets, PCs, and – over the last few years – automobiles.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...
View post: Engagement Ring Drops 118 Feet, Ski Resort Employee Saves The Day Faction Skis has released a limited-edition graphic celebrating one of their most successful and loved skiers—Eileen Gu. Gu ...
Faction Skis has released a limited-edition graphic celebrating one of their most successful and loved skiers—Eileen Gu. Gu, who has been with the brand since she was just 16 years old, is no stranger ...
Microsoft (MSFT) said it has achieved a new AI inference record, with its Azure ND GB300 v6 virtual machines processing 1.1 million tokens per second on a single rack powered by Nvidia (NVDA) GB300 ...
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Researchers at DeepSeek on Monday released a new experimental model called V3.2-exp, designed to have dramatically lower inference costs when used in long-context operations. DeepSeek announced the ...
Amazon Web Services has initiated Global Cross-Region inference of Anthropic Claude Sonnet 4 in Amazon Bedrock, which makes it possible to direct the AI inference request to several AWS regions ...
This figure shows an overview of SPECTRA and compares its functionality with other training-free state-of-the-art approaches across a range of applications. SPECTRA comprises two main modules, namely ...
What if you could harness the power of advanced AI models at speeds that seem almost unreal—up to a staggering 1,200 tokens per second (tps)? Imagine running models with billions of parameters, ...
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