Beth's Blog: How Nonprofits Can Use Social Media

JANUARY 27, 2014

So, expect to see regular reflections on good instructional design and delivery for any topic, but especially digital technology and social media related. As someone who has been designing and delivering training for nonprofits over the past twenty years, the most exciting part is apply theory to your practice.

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Instructional Design Instructional Instruction Training 113

Beth's Blog: How Nonprofits Can Use Social Media

FEBRUARY 11, 2014

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.

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Learning Learning Theory Brain Nonprofit 139

The AI Alignment Forum

FEBRUARY 28, 2025

Concretely, this research agenda involves answering questions such as: What is the right method for expressing goals and instructions to AI systems? Some relevant criteria for evaluating a specification language include: How expressive is the language? Are there things it cannot express?

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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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The AI Alignment Forum

FEBRUARY 28, 2025

The third and final class of tasks I look at in this paper is a new category of objectives that I refer to as modal objectives, where the agent is given an instruction expressed not just in terms of what does happen along a given trajectory, but also in terms of what could happen. This paper is also discussed in this post (Paper 4).

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The AI Alignment Forum

FEBRUARY 7, 2025

In either of these settings, theres a chance that the LLMs will write messages that encode meaning beyond the natural language definitions of the words used. Externalizing reasoning: It could be safer to have much smaller language models which put more reasoning into natural language. Kumar et al. , OpenAI , Yuan et al.

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