The edge inference conversation has been dominated by latency. Read any survey paper, attend any infrastructure conference, and the opening argument is nearly always the same: cloud inference ...
AWS partnered with Cerebras. Microsoft licensed Fireworks. Google built Ironwood. One week of announcements reveals who ...
“The rapid release cycle in the AI industry has accelerated to the point where barely a day goes past without a new LLM being announced. But the same cannot be said for the underlying data,” notes ...
As AI workloads shift from centralized training to distributed inference, the network faces new demands around latency requirements, data sovereignty boundaries, model preferences, and power ...
Paper: "Robust Nonparametric Bias-Corrected Inference in the Regression Discontinuity Design", (joint work with Sebastian Calonico and Rocio Titiunik).
How to improve the performance of CNN architectures for inference tasks. How to reduce computing, memory, and bandwidth requirements of next-generation inferencing applications. This article presents ...
Inference protection is a preventive approach to LLM privacy that stops sensitive data from ever reaching AI models. Learn how de-identification enables secure, compliant AI workflows with ...
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