Microsoft’s E5 Text Embedding Model Tops the MTEB Benchmark With 40x Fewer Parameters https://
syncedreview.com/2022/12/13/mic
rosofts-e5-text-embedding-model-tops-the-mteb-benchmark-with-40x-fewer-parameters/
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MACHINE LEARNING
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Microsoft E5 Text Embedding Model Tops MTEB Benchmark
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Transformative Tech Advances: AI, Biotech, Rockets, and Fusion
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I feel so fortunate to live through some of the most transformative technological advances in history. AI, biotechnology, electric cars, landing rockets, the inception of fusion … amazing! Let’s put it to the benefit of human kind!
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AI Software Developers Pain Points Panel Discussion
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Join us this Thursday for a virtual panel session w/ @Imagimob
, @codeplaysoft
, @intel
, and @MLCommons at @eetimes
' AI Everywhere Forum! "AI Software: What are Developers' Biggest Pain Points and How Can We Resolve Them?" Dec. 15, 2022 – 9:15 AM PST https://
bit.ly/3PoaPtX -
Models Learning from Observed Data: Benefits and Ethical Considerations
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Well, that is objectively not what the models do, so they are just wrong. The question of the net social benefits of automating skilled craft is open for discussion. Generally, I think “Learn from all that you see” is virtuous behavior, and I would have a hard time condemning it.
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Stable Diffusion Hand Quality Limited by Training Resolution
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I still don't think you make sense lmfao but np The problem is not with training material, the problem is SD is trained on 512×512 mostly, now SD2 on 786×786, those are low resos and hard to see hands properly It'll be solved once reso of training pics goes up
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ChatGPT Will Kill Search and Open Path to Web3
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ChatGPT Will Kill Search and Open a Path to Web3
#AI #MachineLearning #digital #web3 #DataScience #python #Digital
Cc @Khulood_Almani @BetaMoroney @Analytics_699 @CurieuxExplorer @dr_gulsun @sallyeaves @amalmerzouk https://
coindesk.com/layer2/2022/12
/09/chatgpt-will-kill-search-and-open-a-path-to-web3/
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Ludwig v0.6 Simplifies ML Model Operationalization with Inference
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Operationalizing state-of-the-art #ML #models just got easier! With @ludwig_ai v0.6, you get an end-to-end #inference pipeline out of the box. Check out the blog to learn more. Sample code and #data included. https://
pbase.ai/3Hrdstf #machinelearning #deeplearning #pytorch -
Robotics Transformer 1: Multi-Task Robot Learning Model
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Introducing the Robotics Transformer 1, a multi-task model that tokenizes robot inputs and outputs actions to enable efficient inference at runtime. Learn how it improves zero-shot generalization to new tasks, environments and objects → https://t.co/hnsKvCJjmP pic.twitter.com/g9QFXzjs9T
— Google AI (@GoogleAI) 13 décembre 2022Introducing the Robotics Transformer 1, a multi-task model that tokenizes robot inputs and outputs actions to enable efficient inference at runtime. Learn how it improves zero-shot generalization to new tasks, environments and objects → https://
goo.gle/3Yxomnt -
Key AI Benchmarks for Language Model Evaluation
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Benchmarks:
– MMLU (massively multitask language understanding): https://
arxiv.org/abs/2009.03300
– BBH (Big-Bench Hard): https://
arxiv.org/abs/2210.09261
– TyDiQA (typographically diverse QA): https://
arxiv.org/abs/2003.05002
– MGSM (multilingual grade school math): https://
arxiv.org/abs/2210.03057 -
Code-Davinci-2 vs Text-Davinci-3: Instruction Tuning and PPO Performance
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– code-davinci-2 > text-davinci-3 means that their instruction finetuning overall hurts performance on academic benchmarks
– text-davinci-3 > text-davinci-2 means that PPO improves performance