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NVIDIA has released the Jetson Orin Nano Super Developer Kit for $249, targeting generative AI applications at the edge. It offers 1.7 times more generative AI performance, reaching 67 INT8 TOPS, making it suitable for robotics and other edge AI tasks. This kit is aimed at developers and hobbyists looking for a cost-effective yet powerful platform for AI development. The product is designed to disrupt the market with high performance at a lower price, targeting the generative AI at the edge market.

GitHub has launched a free tier for its Copilot AI code completion tool, offering developers up to 2,000 code completions and 50 chat messages per month. This new free tier includes access to both GPT-4o and Claude 3.5 Sonnet models, making advanced AI-assisted coding accessible to a broader audience. This initiative aims to expand the reach of AI capabilities to more developers and further encourage adoption of AI in software development workflows.

Microsoft has released .NET 9, a major upgrade to its open-source software development platform. This release features significant performance enhancements and new capabilities for building AI-enabled applications. It includes over 1,000 performance-related changes across runtime, workloads, and languages, along with more efficient algorithms for code generation. Microsoft has made integrating AI into .NET apps easier by building out a smart components ecosystem. The release also includes new features in the C# and F# programming languages, making it easier and safer for developers to write code.

Researchers at Protect AI plan to release a free, open-source tool that can find zero-day vulnerabilities in Python codebases with the help of Anthropic’s Claude AI model. This tool leverages the power of LLMs to analyze code and identify potential security issues, potentially improving the speed and efficiency of vulnerability detection. The tool is designed to help developers identify and mitigate vulnerabilities early in the development cycle, improving the overall security of Python applications. This highlights the potential of AI to be used for proactive security measures and to enhance the security posture of software applications.