This new @natBME review on #AI fairness in #healthcare, and how to mitigate it, is the best I've seen on the topic
by @richardjchen @AI4Pathology @tiffanyytchen @sharifa_sahai @ming_yu_lu @jana_lipkova @harvardmed https://
nature.com/articles/s4155
1-023-01056-8
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RESEARCH
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AI Fairness in Healthcare: Mitigation Strategies Review
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AI Reliability Issues and Performance Benchmarking Improvements
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Plenty of room for improvement here. Sometimes it behaves like an actual AI with ability to handle 20 follow ups, sometimes just like someone with schizophrenia. We are working on benchmarks and improvements.
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AI Is Running Circles Around Robotics
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AI Is Running Circles Around Robotics
#AI #AIio #BigData #ML #NLU #Futureofwork http://
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AI Is Running Circles Around Robotics Industry
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AI Is Running Circles Around Robotics#AI #AIio #BigData #ML #NLU #Futureofwork@briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova https://t.co/SEAPR3OOSf pic.twitter.com/HAKjwgxeti
— Terence Mills (@terence_mills) 28 juin 2023AI Is Running Circles Around Robotics
#AI #AIio #BigData #ML #NLU #Futureofwork @briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova http://
ow.ly/hbS330svSue -
SambaNovaAI DataScale SN30 Training Workshop at Argonne
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Register now for an exciting training workshop introducing users to the @SambaNovaAI DataScale SN30 deployed at the @argonne_lcf AI Testbed. This workshop is targeted at universities, national labs, and industries working on open science. https://
alcf.anl.gov/events/sambano
va-ai-training-workshop-0
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H100 Training Speed Triples A100 with FP8 Optimization
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As @MosaicML showcased in April, on GPT training H100 is ~3x the speed of A100, if you use FP8 training, which is both seriously impressive and grounds you in relative improvement versus the previous generation! https://
mosaicml.com/blog/coreweave
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Model Distillation Performance Trade-offs in Large Language Models
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But yeah, modeling performance-wise you'll probably take a hit. Same thing that happened when they distilled ChatGPT GPT-3.5 and later GPT-4
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CottonAce AI System Deployed for Pest Detection in Karnataka
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Accelerating the deployment of CottonAce, our AI-powered early pest warning and advisory system in Karnataka, we provided training to 350 farmers and provided them with pheromone traps in collaboration with @WeAreLDC and our on-ground partners, Kabini Organics. #MachineLearning
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OpenCV University Launch Recap at CVPR2023 Conference
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Here's a little recap of the Launch of OpenCV University at the #CVPR2023
— Satya Mallick (@LearnOpenCV) 28 juin 2023
It was awesome to see all the folks at our Booth!
See you guys in the next one! #CVPR2024 #AI #ComputerVisionhttps://t.co/p5t0Ha7DG0 pic.twitter.com/mvFJNVoCAhHere's a little recap of the Launch of OpenCV University at the #CVPR2023 It was awesome to see all the folks at our Booth!
See you guys in the next one! #CVPR2024 #AI #ComputerVision https://
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Standard Practice for Pruning Linear Layers in Neural Networks
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I haven't seen that yet. I think the standard is to prune all linear layers, this includes the QVK of the attention layers and the FC layers (except the embedding and output layers of course).