Saishruthi is an active ethical AI practitioner and advocate based out of California. She has been a one of the top contributors to the field of Ethical AI.
Cloud robotics deals with low powered robots that can offload their compute to centralized servers if they are uncertain locally or want to run more accurate, compute-intensive models.
Neural network subspaces contain diverse solutions that can be ensembled, approaching the ensemble performance of independently trained networks without the training cost.
Sanmay has worked with the US Treasury department on machine learning approaches to credit risk analysis, and occasionally consults in the areas of technology and finance.
Is it time to bid farewell to bias-variance tradeoff when it comes to machine learning?
We are celebrating three pioneers from different ages whose work laid the foundations for modern day AI.
Matrix multiplication is among the most fundamental and compute-intensive operations in machine learning.
I’m a senior Technical Program Manager(PM) with the Cloud AI services team. I lead teams to build products/solutions for our customers.
Snippet: With increasing size of the language models, the computation complexity increases and Transformers, too, struggle while dealing with long contexts.
Researchers from Mila AI Institute, Quebec, in their survey, have departed from the traditional categorisation of RL exploration methods and given a treatise into RL exploration methods.
VICReg combines the variance term with a decorrelation mechanism based on redundancy reduction and covariance regularisation.
Last month, Apple announced that it will be introducing new child safety features in three areas, developed in collaboration with child safety experts. After backlash
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