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As a trainer and facilitator who works with nonprofit organizations and staffers, you have to be obsessed with learningtheory to design and deliver effective instruction, have productive meetings, or embark on your own self-directed learning path.
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 learningtheory has led to very large models. The natural follow-up question is if this increase in computing requirements has led to an increase in accuracy.
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.
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.
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 LearningTheory (SLT) [ 1 , 2 , 3 , 4 , 5 , 6 ]. The S4 correspondence in small language models. Alignment).
The participants learn the foundations of choir singing, such as posture and breathing, vocal technique, and tone. They also learntheory, 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.
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.
Manning, Jure Leskovec Contact : xikunz2@cs.stanford.edu Award nominations: Spotlight Links: Paper | Website Keywords : knowledge graph, question answering, language model, commonsense reasoning, graph neural networks, biomedical qa Fast Model Editing at Scale Authors : Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D.
Some relevant criteria for evaluating a specification language include: How expressive is the language? What is the right way to quantify the differences and similarities between different goal specifications in a given specification language? Are there things it cannot express? How intuitive is it for humans to work with?
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. and Mathew et al. Roger and Greenblatt ).
Goodhart's Law in Reinforcement Learning As you probably know, "Goodhart's Law" is an informal principle which says that "if a proxy is used as a target, it will cease to be a good proxy". This paper is also discussed in this post (Paper 4). For details, see the full paper.
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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): Whereas in the crosscoder paper, language modeling doesnt seem like the kind of thing that is going to be very symmetric.
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