Inference workloads are on course to consume a significant chunk of AI computing power in 2026. Intel is well positioned to capitalize on the growing demand for AI inference thanks to the efficiency ...

As AI continues to revolutionize industries, new workloads, like generative AI, inspire new use cases, the demand for efficient and scalable AI-based solutions has never been greater. While training ...

Overview: GPUs provide the flexibility and computing power needed to train large AI models, while TPUs optimize tensor-heavy ...

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use ...

Using the AIs will be way more valuable than AI training. AI training – feed large amounts of data into a learning algorithm to produce a model that can make predictions. AI Training is how we make ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

Named Jalapeño, the new processor was designed specifically for the unique needs of OpenAI's inference systems.