A tensor is a mathematical container for numbers arranged across one or more dimensions. A scalar can be treated as a zero-dimensional tensor, a list as one-dimensional, a table as two-dimensional, and images or batches of data as higher-dimensional tensors. Deep learning frameworks use tensors to store model inputs, parameters, activations, and gradients while performing efficient operations on CPUs, GPUs, or specialized accelerators. A tensor’s shape, data type, device, and memory layout determine which operations are valid and how much computation is required. In some mathematical contexts the word has a stricter meaning, but in everyday machine learning it usually refers to a multidimensional numerical array.
Elon Musk has unveiled Grokipedia – an AI-driven encyclopedia built on Grok that aims to offer factual, bias-free knowledge as an alternative to Wikipedia.
Andrew Tulloch, co-founder of the $12 billion AI startup Thinking Machines Lab, has joined Meta after previously rejecting what reports described as a $1.5 billion offer — a figure Meta has since called ‘inaccurate and ridiculous.’
OpenAI has announced a strategic partnership with Broadcom to design and deploy 10 gigawatts of custom AI accelerators, expanding its hardware ecosystem beyond Nvidia and AMD.
Google has unveiled Gemini Enterprise, a next-generation AI platform designed for business productivity and collaboration, positioning itself directly against Microsoft’s Copilot and OpenAI’s enterprise solutions in the race for workplace AI dominance.
Google Cloud and Figma have launched an expanded partnership to embed Google’s generative AI models – including Gemini 2.5 Flash and Imagen 4 – directly into Figma’s design tools, reducing latency and accelerating creative workflows.