Cohere For AI @forai_ml is celebrating six months of an incredible journey! Take a look back at everything that happened during this time
RESEARCH
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CALM: Dynamic Computational Effort for Language Models
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Presenting Confident Adaptive Language Modeling (CALM), a novel method that allows language models to dynamically modify computational effort when generating text. Learn how CALM can accelerate text generation while preserving output quality → https://t.co/Nm7yyT8sMA pic.twitter.com/MpuaPBzDMU
— Google AI (@GoogleAI) 16 décembre 2022Presenting Confident Adaptive Language Modeling (CALM), a novel method that allows language models to dynamically modify computational effort when generating text. Learn how CALM can accelerate text generation while preserving output quality → https://
goo.gle/3HJKzbM -
Stable Diffusion artifacts and training distribution drift analysis
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Yep, resembles the artifacts I had here. I get a lot of zig zags too.
— Gene Kogan (@genekogan) 16 décembre 2022
I think our working hypothesis was that the output image gradually careens out of the training distribution, so even after noising it, SD doesn't quite know what to do with it.https://t.co/r1YZNzonfUYep, resembles the artifacts I had here. I get a lot of zig zags too. I think our working hypothesis was that the output image gradually careens out of the training distribution, so even after noising it, SD doesn't quite know what to do with it.
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ROSCOE: New Metrics Suite for Evaluating Step-by-Step Reasoning
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ROSCOE is a first-of-its-kind suite of metrics for scoring step-by-step reasoning. By publishing this study we hope to provide a foundation that enables scalable systematic evaluation and benchmarking of new language models. See the paper on arXiv https://
arxiv.org/abs/2212.07919 -
Thanking researchers for advancing AI study and progress
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Thank you to @OlgaNLP
, @moyapchen
, @spencerpoff
, @LukeZettlemoyer
, @CMacota99
, Maryam F. and @real_asli for all of their work to move this space forward with this study! -
Ludwig AI Maintainer Discusses Declarative ML Approaches
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ICYMI: @ludwig_ai maintainer Justin Zhao joined @DataTalksClub to discuss all things declarative #ML. Topics covered:
• State of ML and #AutoML
• Overview of declarative approaches
• Live Ludwig demo
• Rapid config-driven iteration https://
pbase.ai/3HFNSAI #deeplearning -
Constitutional AI: Moving Beyond Researcher-Defined Constitutions
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In our paper we used an ad hoc constitution drafted purely for research purposes. Ultimately, we think constitutions shouldn’t be just defined by researchers in isolation, but by groups of experts from different disciplines working together.
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Constitutional AI: Making Implicit Principles Explicit in AI Systems
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While the name “Constitutional AI” may sound ambitious, we chose it to emphasize that powerful, general-purpose AI systems will always be operating according to *some* principles, even if they are left implicit, or encoded in privately held data.
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Hugging Face Reaches 100,000 Public AI Models Milestone
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We crossed 100,000 public AI models on the @huggingface hub available for free to all. Thank you to the whole community of contributors. Proud to make ML more open & collaborative!
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Sign Up for Semantic Search Hackathon Event
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Sign up and get hacking https://
lablab.ai/event/semantic
-search-hackathon
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