Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten ...

“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 ...

Bayesian inference provides a robust framework for combining prior knowledge with new evidence to update beliefs about uncertain quantities. In the context of statistical inverse problems, this ...

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Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

Explore real-time threat detection in post-quantum AI inference environments. Learn how to protect against evolving threats and secure model context protocol (mcp) deployments with future-proof ...

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 ...

Within the first year of life, children can make transitive inferences about a social hierarchy of dominance. Human infants are capable of deductive problem solving as early as 10 months of age, a new ...