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PerthMLGroup

@PerthMLGroup

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In our paper arxiv.org/abs/2302.10360 on the arXiv today, we present results from a study investigating the energy-efficiency advantage that could be achieved in executing state-of-the-art Transformer models on optical hardware.


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🎉 We are thrilled to announce the release of the latest version of mlforecast a #Python library for Scalable #machinelearning 🤖 for #timeseries #forecasting 🚀 This version comes with exciting new features that are sure to make forecasting even more efficient and accurate 🧵

nixtlainc's tweet image. 🎉 We are thrilled to announce the release of the latest version of mlforecast a #Python library for Scalable #machinelearning  🤖 for #timeseries #forecasting

🚀 This version comes with exciting new features that are sure to make forecasting even more efficient and accurate

🧵

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Cyborgism Research Agenda -Does not try to make GPT an agent -Leverages GPT as a general simulator -LLMs reason from scratch about any situation -Advanced prompting interfaces -Branches GPT chains of thought -Injects variance into human thoughts Post alignmentforum.org/posts/bxt7uCiH…

johnjnay's tweet image. Cyborgism Research Agenda

-Does not try to make GPT an agent
-Leverages GPT as a general simulator
-LLMs reason from scratch about any situation

-Advanced prompting interfaces
-Branches GPT chains of thought
-Injects variance into human thoughts

Post alignmentforum.org/posts/bxt7uCiH…

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This quietly slipped out yesterday. Briefly, the UK is traditinally a strong source of clinical trials but patient recruitment has fallen by 44% (!) due to slow & unpredictable set-up of research sites. Independent review into UK clinical trials buff.ly/3lVWGtx

agapow's tweet image. This quietly slipped out yesterday. Briefly, the UK is traditinally a strong source of clinical trials but patient recruitment has fallen by 44% (!) due to slow & unpredictable set-up of research sites. 

Independent review into UK clinical trials buff.ly/3lVWGtx

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One exciting feature of our partnership with AWS is that we now have 1000+ GPUs to start training really large models at @huggingface 🔥🔥🔥! We’ll be working hard to make closed models open, starting with LLMs and friends 🤓 Which closed models would you like to be open?


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Recitation-Augmented LLMs -Usually: Retrieve relevant docs & give to LLM to answer -Instead: Recite relevant passages from LLMs' own memory via sampling, then produce final answer -State-of-the-art on closed-book Q&A Paper arxiv.org/abs/2210.01296 Code github.com/Edward-Sun/REC…

johnjnay's tweet image. Recitation-Augmented LLMs

-Usually: Retrieve relevant docs & give to LLM to answer

-Instead: Recite relevant passages from LLMs' own memory via sampling, 
then produce final answer
-State-of-the-art on closed-book Q&A

Paper arxiv.org/abs/2210.01296
Code github.com/Edward-Sun/REC…

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German AI startup @Aleph__Alpha claims it will have a 300-billion parameter Large Language Model "Luminous-World" trained this year for “highly complex and critical applications” (GPT-3 has 175 billion parameters)


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We're excited to welcome FuseMedML to the PyTorch ecosystem! FuseMedML is part of the BiomedSciAI organization which provides tools for AI-based accelerated discovery of biomarkers and molecules in the biomedical domain. See the latest here: hubs.la/Q01D6TZ70


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Robust Hybrid Learning With Expert Augmentation Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Joern-Henrik Jacobsen. Action editor: Jasper Snoek. openreview.net/forum?id=oe4dl… #expert #models #modelling


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We've officially passed 200K public datasets!!! 👏👏

kaggle's tweet image. We've officially passed 200K public datasets!!! 👏👏

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"MarioGPT: Open-Ended Text2Level Generation through Large Language Models" This looks like a pretty fun and creative project! The best part, it's based on a distilled GPT-3 model and can be trained on a single GPU.

rasbt's tweet image. "MarioGPT: Open-Ended Text2Level Generation through Large Language Models" 
This looks like a pretty fun and creative project!
The best part, it's based on a distilled GPT-3 model and can be trained on a single GPU.

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On a Welsh island, a seagull swallows a rabbit whole.


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Supercontinuum in 100m of 50 micron Fiber youtube.com/watch?v=l6uH0O…

LesLaboratory's tweet image. Supercontinuum in 100m of 50 micron Fiber

youtube.com/watch?v=l6uH0O…
LesLaboratory's tweet image. Supercontinuum in 100m of 50 micron Fiber

youtube.com/watch?v=l6uH0O…

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In the last week, three people on reddit/r/statistics have asked about testing whether a sample came from a Gaussian distribution. The answer is that you should never test for normality. The result is a non-answer to the wrong question. allendowney.com/blog/2023/01/2…


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.@TalarianHQ's `GPT for Sheets™` is the gift that keeps on giving! 🔥 Look at how easy it is to create personalized content with it, thanks to #GPT3's seamless integration! 🤯👇 Get the add-on here: 🔗workspace.google.com/marketplace/ap…

Now it's even easier to use #GPT3 in @googlesheets with @TalarianHQ's `GPT for Sheets™` extension! 🔥 Check out their new `GPT_FILL()` function! 👇 🔗 workspace.google.com/marketplace/ap…



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I think this link will be useful: google-research.github.io/seanet/musiclm… the paper: arxiv.org/abs/2301.11325 also they released a dataset: kaggle.com/datasets/googl… it's a shame the actual library is not available but the research article is pretty good


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Batch normalisation appears to be falling out of favour (probably for the best IMO, so many bugs end up being batchnorm bugs😬). One area where it persists is GAN discriminators (e.g. in StyleGAN-T and VQGAN). Are there any other settings where batchnorm is still hard to avoid?


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The first text line detection model for historical documents available on @huggingface : paper+code+models, all open-source huggingface.co/Teklia/doc-ufc… teklia.com/research/publi… #digitalhumanities @LitisLab

_Teklia_'s tweet image. The first text line detection model for historical documents available on @huggingface : paper+code+models, all open-source   huggingface.co/Teklia/doc-ufc…  teklia.com/research/publi… #digitalhumanities @LitisLab

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[CV] Learning Good Features to Transfer Across Tasks and Domains P Z Ramirez, A Cardace, L D Luigi, A Tonioni, S Salti, L D Stefano [University of Bologna & Google] (2023) arxiv.org/abs/2301.11310 #MachineLearning #ML #AI #CV [1/2]

fly51fly's tweet image. [CV] Learning Good Features to Transfer Across Tasks and Domains
P Z Ramirez, A Cardace, L D Luigi, A Tonioni, S Salti, L D Stefano [University of Bologna & Google] (2023)
arxiv.org/abs/2301.11310
#MachineLearning #ML #AI #CV 
[1/2]
fly51fly's tweet image. [CV] Learning Good Features to Transfer Across Tasks and Domains
P Z Ramirez, A Cardace, L D Luigi, A Tonioni, S Salti, L D Stefano [University of Bologna & Google] (2023)
arxiv.org/abs/2301.11310
#MachineLearning #ML #AI #CV 
[1/2]
fly51fly's tweet image. [CV] Learning Good Features to Transfer Across Tasks and Domains
P Z Ramirez, A Cardace, L D Luigi, A Tonioni, S Salti, L D Stefano [University of Bologna & Google] (2023)
arxiv.org/abs/2301.11310
#MachineLearning #ML #AI #CV 
[1/2]
fly51fly's tweet image. [CV] Learning Good Features to Transfer Across Tasks and Domains
P Z Ramirez, A Cardace, L D Luigi, A Tonioni, S Salti, L D Stefano [University of Bologna & Google] (2023)
arxiv.org/abs/2301.11310
#MachineLearning #ML #AI #CV 
[1/2]

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Just published a literature review on scaling laws @EpochAIResearch! I collected a database of scaling laws for different tasks and architectures and reviewed dozens of papers in the scaling law literature. Check out the database! docs.google.com/spreadsheets/d… 🧵


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