This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...
“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 ...
Over the last couple of years, we have focused extensively on the hardware required for training deep neural networks and other machine learning algorithms. Focal points have included the use of ...
Paper: "Robust Nonparametric Bias-Corrected Inference in the Regression Discontinuity Design", (joint work with Sebastian Calonico and Rocio Titiunik).
Two distinct Bayesian methodologies are developed and compared for inference on gamma scale parameters in one and two population problems. Both approaches permit concomitant variables and censored ...
An archaeological dating problem is presented and analyzed. The analysis is based on a data-generating model, which takes careful account of the various kinds of uncertainty involved in relating ...
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 ...
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