Tomorrow’s AI networks need to adapt to stay ahead of the inference curve

Tomorrow's AI services depend on networks built for massive inference growth.

OpenAI unveils first custom AI inference chip, Jalapeño, with Broadcom — and its development was sped-up with OpenAI's own models

The companies attributed this speed to a deep software-hardware co-development process that actively used OpenAI’s own models ...

Hot French startup ZML releases free product to speed inference across lots of AI chips

ZML, a hot French AI startup endorsed by Turing Award winner Yann LeCun, has now released ZML/LLMD, software that could make ...

How AI Inference Sends Decision Making To The Edge

The next phase of AI infrastructure will not be defined by a single destination called “the cloud” or “the edge.” ...
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DeepSeek lives up to market disruptor reputation with in-house chips talks

Chinese AI startup DeepSeek is designing an in-house chip to run its models, according to sources close to the matter. The ...

Crusoe Launches Serverless Fine-Tuning and Self-Serve Inference Deployments, Accelerating Open-Model Development From Experiment to Production

Purpose-Built AI Infrastructure Now Supports the Full Model Development Lifecycle—From Fine-Tuning to Production Inference—With No Cluster Provisioning, No Surprise Bills, and Full Weight ...

DeepSeek's Silicon Gambit: Chinese AI Star Begins Building Its Own Inference Chip

DeepSeek is developing its own AI inference chip, seeking to reduce reliance on Nvidia and Huawei amid rising demand and US ...

The AI Cost Crisis Isn’t About Models. It’s About Context.

After two years of maxxing out on AI tools, many organizations are confronting an uncomfortable reality: AI costs don't scale linearly with adoption.