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Source channel @githubtrending · Post #14949 · Jul 12

#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7 YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments. https://github.com/WongKinYiu/yolov7

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AI & Law

@ai_and_law · Post #202 · 12/28/2023, 08:04 AM

USA: New Bill Proposes Transparency Rules for AI Training Data Hello everybody! In US a new AI Foundation Model Transparency Act have been introduced. The aim is to ensure transparency in the usage of copyrighted data in training AI models. Companies developing foundation models must reveal the sources of their training data. This move is geared towards informing copyright holders if their data has been utilized. The bill tasks the Federal Trade Commission (FTC) to collaborate with the National Institute of Standards and Technology (NIST) in establishing rules for reporting training data transparency. Companies must disclose the origin of training data, how it's retained during inference, model limitations or risks, alignment with NIST’s AI Risk Management Framework, and adherence to federal standards. AI developers are required to report efforts to "red team" the model, especially in areas like medical queries, cybersecurity, elections, and services impacting vulnerable populations. This bill complements the Biden administration’s AI executive order, reinforcing the push for standardized reporting in AI models. The bill is yet to go through committee discussions, and its fate before the election campaign season remains uncertain. #AIlaw#CopyrightData#Legislation#TechNews#AIRegulation