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As nonprofits attempt to tackle some of our communities' most difficult problems; funders, government agencies and the general public are actively calling for accountability, transparency and proof that a program is producing change. This call spurred the increasing demand for program evaluation. Guide to building evaluation capacity.
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 learningtheory. And, there is no shortage of learningtheories and research.
Finally, in the last post, I will also provide some resources for anyone who wants to contribute to this (or similar) research, in the form of both open problems and some thoughts on how these problems could be approached. Some relevant criteria for evaluating a specification language include: How expressive is the language?
This guide provides an opinionated overview of recent work and open problems across areas like adversarial testing, model transparency, and theoretical approaches to AI alignment. We think this adversarial style of evaluation and iteration is necessary to ensure an AI system has a low probability of catastrophic failure.
To me, the main takeaway from this paper is that we should be careful with the assumption that the basic RL setting really captures everything that we intuitively consider to be part of the problem domain of sequential decision-making.
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 learningtheory and other instructional approaches.
Derrick Xin , Behrooz Ghorbani , Ankush Garg , Orhan Firat , Justin Gilmer Associating Objects and Their Effects in Video Through Coordination Games Erika Lu , Forrester Cole , Weidi Xie, Tali Dekel , William Freeman , Andrew Zisserman , Michael Rubinstein Increasing Confidence in Adversarial Robustness Evaluations Roland S.
You could imagine saying, Oh, we figured out that the difficulties in finding It was still kind of hard and our lives would be easier if we solved sub-problems, X, Y and Z. Do you have thoughts on, are there sub-problems such that if we solved them we could do it? Or does it just seem kind of hopeless? Im like, its nice.
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