Gyrus

MARCH 15, 2024

Personalized learning experiences Personalized and adaptive learning is gaining traction in the L&D space, which is a welcome change from the traditional ‘one-size-fits-all’ approach. Video-based micro-learning Video learning has been one of the most impactful ways to deliver online training.

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Gyrus

MARCH 15, 2024

Personalized learning experiences Personalized and adaptive learning is gaining traction in the L&D space, which is a welcome change from the traditional ‘one-size-fits-all’ approach. Video-based micro-learning Video learning has been one of the most impactful ways to deliver online training.

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Google Research AI blog

APRIL 30, 2023

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. Mukund Varma T.

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Tech Soup

DECEMBER 8, 2014

The participants learn the foundations of choir singing, such as posture and breathing, vocal technique, and tone. They also learn theory, ear training, foreign language skills, and the study of music within a social context. It was founded in 1964 and has served hundreds of members over the years.

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The AI Alignment Forum

FEBRUARY 28, 2025

For example, suppose we have a metric d over the space of all reward functions, and that we have reason to believe that a given reward function R 2 is within a distance of to the ideal reward function R 1 (based on our learning algorithm and amount of training data, etc). If not, what errors and failure modes should we expect to see?

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Stanford AI Lab Blog

DECEMBER 6, 2021

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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Stanford AI Lab Blog

APRIL 25, 2022

Larsen, Stanislav Fort, Nic Becker, Surya Ganguli Contact : bwlarsen@stanford.edu Links: Paper Keywords : loss landscape, high-dimensional geometry, random hyperplanes, optimization How did the Model Change?

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The AI Alignment Forum

FEBRUARY 7, 2025

*Backdoors and other alignment stress tests: Past research has implanted backdoors in safety-trained LLMs and tested whether standard alignment techniques are capable of catching or removing them. Were interested in techniques like latent adversarial training and circuit breaking that might succeed where standard adversarial training falters.

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The AI Alignment Forum

FEBRUARY 28, 2025

The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret In this paper , we look at what happens when a learnt reward function is optimised. However, does this guarantee that we get a low regret relative to the underlying true reward function when that reward model is optimised?

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NonProfit Hub

OCTOBER 16, 2015

Beth has over 30 years working in the nonprofit sector in technology, training, capacity building, evaluation, fundraising and marketing. Beth is an expert in facilitating online and offline peer learning, curriculum development based on traditional adult learning theory and other instructional approaches.

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Beth's Blog: How Nonprofits Can Use Social Media

JUNE 29, 2016

Note from Beth: At this year’s Nonprofit Technology Conference, I was lucky to co-design and facilitate a session on technology training with colleagues John Kenyon, Cindy Leonard and Jeanne Allen. Cindy and Jeanne wrote this great reflection of what we learned and how we facilitated this very interactive session.

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DataRobot

APRIL 21, 2022

They are used for different applications, but nonetheless they suggest that the development in infrastructure (access to GPUs and TPUs for computing) and the development in deep learning theory has led to very large models. Furthermore, it costs somewhere between $1 and $3 million in a cloud environment to train.

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Google Research AI blog

NOVEMBER 28, 2022

Platt , Fernando Pereira , Dale Schuurmans Keynote Speakers The Data-Centric Era: How ML is Becoming an Experimental Science Isabelle Guyon The Forward-Forward Algorithm for Training Deep Neural Networks Geoffrey Hinton Outstanding Paper Award Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia , William Chan (..)

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The AI Alignment Forum

MARCH 28, 2025

And its a small transformer and theres not that much going on, and you train a transformer that in fact works at this, and I guess your job is: how can you prove that it actually works at this without just running it on all of the examples? This is to train the crosscoder? Jason Gross (00:10:33): So it works fine for max of four.

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