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Why Movement Is the Killer Learning App for Nonprofits

Beth's Blog: How Nonprofits Can Use Social Media

As a trainer and facilitator who works with nonprofit organizations and staffers, you have to be obsessed with learning theory to design and deliver effective instruction, have productive meetings, or embark on your own self-directed learning path. Internal: These theories take into account our minds and bodies.

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Six Books About Skills You Need To Succeed in A Networked World

Beth's Blog: How Nonprofits Can Use Social Media

Paul Schoemaker, founder and executive chairman of Decision Strategies international and research director of Wharton’s Mack Center for technological innovation, shares critical insights on the benefits of making well-chosen mistakes. I’ve been curating resources on training techniques and capacity building over at scoop.it

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professionals

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How To Think Like An Instructional Designer for Your Nonprofit Trainings

Beth's Blog: How Nonprofits Can Use Social Media

In addition, I’m also doing a lot of training of other trainers and am now an Adjunct Professor at the Monterey Institute for International Studies (a graduate school of Middlebury College). So writing a lesson plan and using it for reflection is an invaluable process for improving your instructional techniques.

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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 scaled key SLT-derived techniques to models with billions of parameters, eliminating our main concerns around tractability.

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Research directions Open Phil wants to fund in technical AI safety

The AI Alignment Forum

Through these research directions, we aim to develop robust safety techniques that mitigate risks from AIs before those risks emerge in real-world deployments. Jailbreaks and unintentional misalignment : New techniques for finding inputs that elicit competent, goal-directed behavior in LLM agents that the developers clearly tried to prevent.

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AXRP Episode 40 - Jason Gross on Compact Proofs and Interpretability

The AI Alignment Forum

And for that, I think you need something like derandomization techniques, where the simplest example of this is that if you have a collection of random vectors in high dimensions, theyre almost always almost orthogonal. Weve said, Regardless of which output you read off of, it looks the same if you do this shuffling internal to the network.

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