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This call spurred the increasing demand for program evaluation. In your organization, this may look like negative attitudes toward evaluation, poor research designs and collecting data but not using the data. The root problem here is poor evaluation capacity. The root problem here is poor evaluation capacity.
If you want to get results, you need to think about instructional design and learningtheory. And, there is no shortage of learningtheories and research. 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.
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.
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.
We think this adversarial style of evaluation and iteration is necessary to ensure an AI system has a low probability of catastrophic failure. Wed like to support more such evaluations, especially on scalable oversight protocols like AI debate. and Which rules are LLM agents happy to break, and which are they more committed to? .
The first of these is the preference structures given by multi-objective RL, where the agent is given multiple reward functions R 1 , R 2 , R 3 , , and has to find a policy that achieves a good trade-off of those rewards according to some specified criterion.
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Daniel Filan (00:28:50): If people remember my singular learningtheory episodes , theyll get mad at you for saying that quadratics are all there is, but its a decent approximation. (00:28:56): Theres a little bit of structure but not very much. I think this looks a lot like what ARC theory is doing with heuristic arguments.
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