The implementation of #MLOps, #ModelOps, #DataOps and #AIOps can bring a number of benefits to organizations that are looking to leverage the power of #AI. Via @ingliguori #MachineLearning #DigitalTransformation #Innovation #DevOps #DataDriven #Data #BigData #RPA #Digital
MACHINE LEARNING
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Webcam accurately measures heart rate via AI
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Webcam accurately measures person's heart rate
— AI Breakfast (@AiBreakfast) 13 janvier 2023
The AI model detects subtle color changes in the face caused by blood flow to measure heart rate (BPM) and heart rate variability (HRV) pic.twitter.com/mmp2mCVxMhWebcam accurately measures person's heart rate The AI model detects subtle color changes in the face caused by blood flow to measure heart rate (BPM) and heart rate variability (HRV)
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KerasNLP APIs for Custom Tokenizers and Advanced NLP Use Cases
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At an even lower level, you can create your own custom tokenizer on a new vocabulary, or pretrain your own backbone. The KerasNLP APIs will be useful to you no matter how advanced you use case becomes. Be sure to check out the starter guide: https://
keras.io/guides/keras_n
lp/getting_started/
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Training Costs for Large Deep Learning Models Rising Significantly
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I also made this prediction, which I still think will soon kick in, as the cost of training modern very large deep models is getting pretty high…
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AI Models Approaching 100 Trillion Parameters Ahead of Schedule
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In my 2018 keynote at ICML I showed this curve and predicted that in 2025 we would have models with 100 trillion parameters. We might get there sooner…
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GPT-2 Development Finally Showing Results and Success
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Finally all that tinkering since GPT-2 is paying off
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TMLR Launches Expert Certification and Conference Partnerships for 2023
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For 2023:
– TMLR's Expert Certification reviewers will be selected
– An Outstanding Certification will be made
– Partnerships to present TMLR papers at specific conferences (AutoML, CoLLAs, and maybe even ICLR)
– Going beyond PDFs for papers! 7/7 -
Fast Conference Review Turnaround Accelerates AI Research Publication
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But I think the biggest news is just how *fast* the turnaround is. At ~75 days median, that's 2.5 months from submission to notification. The big conferences (NeurIPS, ICML, ICLR) are closer to 4 months. And much faster than JMLR, which takes > 200 days to first reviews. 5/n
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TMLR publishes 188 papers with 62% acceptance rate
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TMLR numbers:
– 651 submissions
– 188 accepted papers
– currently ~100 submissions/month
– 189 action editors
– 1846 reviewers
– acceptance rate: 62% (46% if you count desk rejections and withdrawls)
– median time to decision: 76 days (#NeurIPS2022: 118 days, JMLR: >200 days) 2/n -
AI and ML Demand Forecasting Solutions for Retailers
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How can #AI help retailers better forecast demand? Learn real-world examples of forecasting with #ML by downloading our white paper #NRF #NRF2023 https://
datarobot.com/resources/ai-h
elps-retailers-better-forecast-demand/
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