Microsoft presented the following slide as part of their Brainwave presentation at Hot Chips this summer: In existing inferencing solutions, high throughput (and high % utilization of the hardware) is ...

DigitalOcean (NYSE: DOCN) today announced the launch of its Inference Engine, a set of new production capabilities that give AI builders exceptional performance and unified control over how they run, ...

Batch size has a significant impact on both latency and cost in AI model training and inference. Estimating inference time ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

The DigitalOcean AI-Native Cloud is engineered for the four shifts redefining production AI: the rise of inference over training, reasoning models as the default, autonomous agents at scale, and ...

There’s huge interest in implementing neural-network inference at “the edge,” anything outside of data centers, in all sorts of devices from cars to cameras. However, so far, very little actual ...

DigitalOcean unveils a five-layer AI-Native Cloud at Deploy 2026, with a new Inference Engine, model router and managed ...

At HotChips 2018, Microsoft presented the attached slide in their Brainwave presentation: the ideal is to achieve high hardware utilization at low batch size. Existing architectures don’t do this: ...

The AI boom shows no signs of slowing, but while training gets most of the headlines, it’s inferencing where the real business impact happens. Every time a chatbot answers, a fraud alert triggers or a ...