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.
Reddit’s r/opensource is banning AI-built projects, but its sweeping new rules are drawing criticism from developers over Linux kernel code and solo contributors.
Apollo data shows the Magnificent Seven widening their revenue-per-employee lead over the S&P 493 between 2019 and 2026, highlighting the growing productivity gap between Big Tech and the broader market.
OpenAI’s red-team agents passed hidden messages through the CPU cache, a covert trick already shown to move data between cloud VMs.
Premium Deepseek 4.1 Flash 1017 drives cost-per-task further down still — open-weight model is fit for agentic workloads and exceedingly cheap to run
Claude and Grok are among the AI agents that are being used to automate attacks on Latin American institutions, including banks and payment apps, by a group calling themselves CyberCartel.
Google’s TPUs now serve AI in production at Meta, through new open-source engines that run PyTorch models natively on the chips.
The U.S. Army is developing a program to deploy autonomous AI agents that can navigate digital and network infrastructures, identify targets, and “neutralize” them.
Google DeepMind researchers say four Gemini 4 Argon agents beat Minecraft in 27 hours, writing 2,783 programs with no human help.
A Chinese hacker reportedly used a fleet of AI agents to break into more than 100 company websites, including farm equipment maker Deers and appliance outfit SharkNinja.
Would this be enough to keep an AI model from going out of control?
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