The world of artificial intelligence (AI) is growing at an exponential rate, with a broad range of topics spanning from the latest CPUs, GPUs, ASICs and FPGAs that run modern AI workloads, along with the different types of AI usages, such as the different types of large language models (LLM) and how they are trained and then used for inference workloads. Here you'll find Tom's Hardware's leading coverage of all things AI.
How realistic is it to run a local AI model and have it automate tasks for you using hardware that doesn’t cost the Earth? We gave it a shot with a Gorgon Point-powered Mini PC, with mixed results.
A million dollar "whoopsie"
Google eyes to build more TPU AI accelerators in 2028 than Nvidia, if a report by Fubon Research is correct.
AI and software research firm looking for a real-life pirate — extremely remote lob listing requires nautical and diving experience
Moonshot AI reportedly used Nvidia Blackwell chips for training Kimi K3 — potentially circumventing both U.S. export and Chinese import controls
OpenAI CEO Sam Altman recently declared on the Relentless podcast that artificial intelligence has entered the technological singularity.
New report reveals that AI companies are buying up physical books to train their LLMs and destroying them in the process.
OpenAI, Google, and Anthropic, companies behind proprietary, "closed" AI models are conspicuously absent from the alliance.
Moonshot AI has released the weights for its recent Kimi-K3 model, directly going against OpenAI and Anthropic.
Getting a local language model running on a sub-$10 microcontroller is impressive despite its obvious limitations.
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