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Cloud AI Inference Workload Capacity Consumption to Surpass Training by 2033, Reaching 46 GW by 2035
Global technology intelligence firm ABI Research forecasts that AI inference workloads will grow at a 42% CAGR to surpass 46 Gigawatts of capacity consumption by 2035, overtaking training workloads by ...
A sign of the times? NVIDIA has introduced a major change to its financial reporting structure, removing gaming as a standalone business category and folding it into a broader “Edge Computing” ...
A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to ...
New AI compression technology targets always-on devices by significantly reducing memory and transmission overhead, helping ...
Frontier LLMs are evolving away from the dense and homogeneous AI workloads that originally favored GPU architectures.
Ubisoft executives offer a glimpse into the engineering behind its generative AI middleware, including the use of small ...
Not everybody has a datacenter that supports liquid cooling, and not every company, particularly those with datacenters ...
USC researchers built a memristor that works at 700C, surviving conditions that killed every Venus probe. TetraMem is commercialising the technology for AI inference.
Google has unveiled the eighth generation of its Tensor Processing Units (TPUs), consisting of two chips dedicated to AI training and inference workloads.
Recently, Cerebras went public with the largest IPO of the year, but it is still far away from the big names in the AI space.
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