As organizations enter the next phase of AI maturity, IT leaders must step up to help turn promising pilots into scalable, ...

The major cloud builders and their hyperscaler brethren – in many cases, one company acts like both a cloud and a hyperscaler – have made their technology choices when it comes to deploying AI ...

Sponsored Feature: Training an AI model takes an enormous amount of compute capacity coupled with high bandwidth memory. Because the model training can be parallelized, with data chopped up into ...

The global collaboration expands to Asia-Pacific, enabling Philippine organizations to meet compliance and low-latency ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More California-based MosaicML, a provider of generative AI infrastructure, ...

South Korean startup FriendliAI has raised $20 million in a seed extension round to support its efforts to accelerate AI inferencing. FriendliAI offers an inference platform designed to accelerate AI ...

Nvidia is aiming to dramatically accelerate and optimize the deployment of generative AI large language models (LLMs) with a new approach to delivering models for rapid inference. At Nvidia GTC today, ...

Intel on Tuesday formally introduced its next-generation Data Center GPU explicitly designed to run inference workloads, wedding 160 GB of LPDDR5X onboard memory with relatively low power consumption.

An analog in-memory compute chip claims to solve the power/performance conundrum facing artificial intelligence (AI) inference applications by facilitating energy efficiency and cost reductions ...

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