Large language models like #GPT3 aren’t good enough for pharma and finance https://
thenextweb.com/news/large-lan
guage-models-like-gpt-3-arent-good-enough-for-pharma-finance
… @thenextweb #AI #MachineLearning #BigData #Analytics #Robots #DeepLearning #100DaysofCode #IoT #serverless #DEVCommunity #womenwhocode #DigitalTransformation #Python #DataScience
MACHINE LEARNING
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Large Language Models Insufficient for Pharma and Finance
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Machine Learning and Analytics in Professional Soccer Predictions
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When you think of soccer, do machine learning and analytics come to mind? They should! Learn how pros make their uncanny predictions. Sign up: http://
ow.ly/yCVt50Lv5HB #MachineLearning #analytics -
AI-Based Network Intrusion Detection for Telecommunications
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Learn how to implement multiple #AI-based approaches to solve a specific use case of identifying network intrusions for #telecommunications. Register now for the 11/16 workshop: https://
nvda.ws/3WxVN8b -
Machine Learning Optimizes Treasury Yield Curve Estimation
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Financial institutions can use a new #machinelearning method to optimize yield curve estimation from U.S. Treasury securities. Learn more from Stanford University and NVIDIA in a webinar on November 16: https://
nvda.ws/3zUhju1 -
Progress in Model Training: From Full Dataset Collection to Modern Approaches
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Definitely a limitation. I see some
progress, though. Back in the day, we had to collect an entire training dataset and train a new model! -
AI eases winter hospital pressures through pioneering technology
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Pioneering artificial intelligence could ease winter pressures on hospitals https://
news-medical.net/news/20221107/
Pioneering-artificial-intelligence-could-ease-winter-pressures-on-hospitals.aspx
… @NewsMedical #Healthcare #AI #DataScience #Python #Robots #BigData #Analytics #100DaysofCode #IoT #serverless #womenwhocode #DeepLearning #DigitalTransformation #MachineLearning -
NLLB-200 Achieves Lowest Content Deletion Rate Among Translation Services
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NLLB-200 sees only 0.13% of translated content deleted. That’s the lowest percentage across all machine translation services available on the platform, suggesting that the resulting translations are being understood & accepted. 3/5
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NLLB-200 Achieves Superior Translation Quality Across All Languages
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Across all languages, NLLB-200 is seeing the best results for translations modified <10% compared to all other MT services on the platform — a strong signal for the quality of translations that are being generated. 4/5
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NLLB-200 becomes third most-used translation engine in four months
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NLLB-200 now represents 3.8% of all machine translations on the platform. This makes it the third most-used machine translation engine across all published translations just four months after launch. 2/5
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Recommendation to Follow Le Hou’s Research on Large Language Models
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People interested in large LMs should follow Le Hou (
@Hou_Le
) at @GoogleAI
, who made a new twitter account recently Le has done great work such as Flan, and self-play for reasoning (
https://
arxiv.org/abs/2210.11610). I'm sure we'll see more great work from him 🙂