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Moving from Red AI to Green AI, Part 1: How to Save the Environment and Reduce Your Hardware Costs

DataRobot

This increase in accuracy is important to make AI applications good enough for production , but there has been an explosion in the size of these models. In the graph below, borrowed from the same article, you can see how some of the most cutting-edge algorithms in deep learning have increased in terms of model size over time.

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How To Think Like An Instructional Designer for Your Nonprofit Trainings

Beth's Blog: How Nonprofits Can Use Social Media

Designing and delivering a training to a nonprofit audience is not about extreme content delivery or putting together a PowerPoint and answering questions. If you want to get results, you need to think about instructional design and learning theory. And, there is no shortage of learning theories and research.

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Timaeus in 2024

The AI Alignment Forum

Published on February 20, 2025 11:54 PM GMT TLDR: We made substantial progress in 2024: We published a series of papers that verify key predictions of Singular Learning Theory (SLT) [ 1 , 2 , 3 , 4 , 5 , 6 ]. We are now pursuing direct impact in three main directions: Near-term Applications. Interpretability ("Reading").

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Google at ICLR 2023

Google Research AI blog

If you’re registered for ICLR 2023, we hope you’ll visit the Google booth to learn more about the exciting work we’re doing across topics spanning representation and reinforcement learning, theory and optimization, social impact, safety and privacy, and applications from generative AI to speech and robotics.

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Stanford AI Lab Papers and Talks at NeurIPS 2021

Stanford AI Lab Blog

Kochenderfer Contact : philhc@stanford.edu Links: Paper Keywords : deep learning or neural networks, sparsity and feature selection, variational inference, (application) natural language and text processing Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Authors : Jeff Z.

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Google at NeurIPS 2022

Google Research AI blog

A Workshop for Algorithmic Efficiency in Practical Neural Network Training Workshop Organizers include: Zachary Nado , George Dahl , Naman Agarwal , Aakanksha Chowdhery Invited Speakers include: Aakanksha Chowdhery , Priya Goyal Human in the Loop Learning (HiLL) Workshop Organizers include: Fisher Yu, Vittorio Ferrari Invited Speakers include: Dorsa (..)

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