OpenAI staff have told me that they didn’t specifically tune on these questions and I believe them. The improvements are seen even for newly made-up problems in the same style.
RESEARCH
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YOLOv5 Instance Segmentation: Elevate Your Object Detection Projects
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🚀Blog-tastic Tuesdays🚀
— Satya Mallick (@LearnOpenCV) 3 janvier 2023
Take your YOLOv5 object detection projects to the next level.📈 With the new instance segmentation architectures, YOLOv5 now supports both segmentation and detection of objects.
To learn more, head over to https://t.co/XPIV4nt5ur #yolov5 #opencv #ai pic.twitter.com/mU1lHrt7m7Blog-tastic Tuesdays Take your YOLOv5 object detection projects to the next level. With the new instance segmentation architectures, YOLOv5 now supports both segmentation and detection of objects. To learn more, head over to https://
learnopencv.com/yolov5-instanc
e-segmentation/
… #yolov5 #opencv #ai -
Submissions vs Papers: Research Collaboration and Student Impact
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To be clear, 14 submissions neq 14 papers, since some are resubmissions. I of course can't know absolutely everything about every paper, e.g., I don't read every line of code. It's hard to say whether great students or collaborators are more important, I'm blessed w both.
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TinyML Applications: Keyword Spotting, Wake Words, Gesture Recognition
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6. Applications of TinyML You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition. https://
pll.harvard.edu/course/applica
tions-tinyml?delta=0
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Reproducible Data Science: Statistical and Computational Tools
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4. Principles, Statistical and Computational Tools for Reproducible Data Science Learn skills to ensure you can trust your own research results, reproduce them yourself, and communicate them to others. https://
pll.harvard.edu/course/princip
les-statistical-and-computational-tools-reproducible-data-science?delta=3
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Harvard Probability Course: Essential Data Science Foundations
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3. Introduction to Probability Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty. https://
pll.harvard.edu/course/introdu
ction-probability-edx?delta=2
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Free Harvard Resources for Programming Data Science Machine Learning
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Don't pay ridiculous amounts of money to study Programming, Data Science, and Machine Learning. Learn these for FREE from the experts at Harvard university. (A thread)
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Artificial Intelligences Can Even Have Humor
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Les Intelligences Artificielles peuvent même avoir de l’humour ! https://
x.com/ribodanslasauc
/ribodanslasauce/status/1609991475429011458
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Difficulty without model release
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well its kinda hard to do that since they didnt even release the model
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AI Limitations: Humans Still Essential for Quality Output
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Here are some key points from the space: 1. AI can't completely replace humans in its current implementation. 2. AI can give you a skeleton to solve a problem but specifics need to filled by humans. 3. Quality of output for these tools totally depends on the quality of input.