{"id":16160,"date":"2024-09-24T12:11:27","date_gmt":"2024-09-24T16:11:27","guid":{"rendered":"https:\/\/blogs.mathworks.com\/deep-learning\/?p=16160"},"modified":"2025-05-16T13:02:16","modified_gmt":"2025-05-16T17:02:16","slug":"apply-ai-with-new-r2024b-examples","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/deep-learning\/2024\/09\/24\/apply-ai-with-new-r2024b-examples\/","title":{"rendered":"Apply AI with New R2024b Examples"},"content":{"rendered":"
<\/h6>\r\nIn my last post<\/a>, I talked about new AI features introduced with MATLAB R2024b - the latest release, which is now available to you. In this blog post, I am going to present a few new and exciting examples on AI workflows, AI areas (computer vision and natural language processing), and AI applications.\r\n
<\/h6>\r\nTo find more new AI examples, see the Deep Learning Toolbox release notes for application examples<\/a>. Did you find the right example that helps you apply AI? Is there an example you would like to see but doesn't exist? Comment below!\r\n
<\/h6>\r\n \r\n
<\/h6>\r\n

AI Workflows<\/strong><\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Compression<\/strong><\/td>\r\nAI with Simulink<\/strong><\/td>\r\nPerformance<\/strong><\/td>\r\n<\/tr>\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
Reduce Memory Footprint of Deep Neural Networks<\/a><\/td>\r\nExport Quantized Networks to Simulink and Generate Code<\/a><\/td>\r\nProfile Your Deep Learning Code to Improve Performance<\/a><\/td>\r\n<\/tr>\r\n
End-to-End Workflow<\/strong><\/td>\r\n<\/tr>\r\n
\"\"<\/td>\r\n<\/tr>\r\n
Battery State Estimation Using Deep Learning<\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/h6>\r\n \r\n
<\/h6>\r\n

AI Branches<\/strong><\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
Computer Vision<\/strong><\/a><\/td>\r\nNatural Language Processing<\/strong><\/a><\/td>\r\n<\/tr>\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
Automatically Label Ground Truth Using Segment Anything Model (SAM)<\/a><\/td>\r\nOut-of-Distribution Detection for BERT Document Classifier<\/a><\/td>\r\n<\/tr>\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
Detect Small Objects Using Tiled Training of YOLOX Network<\/a><\/td>\r\nRetrieval Augmented Generation Using ChatGPT and MATLAB (GitHub)<\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/h6>\r\nFor natural language processing (NLP), check out the Large Language Models (LLMs) with MATLAB<\/a> repository, which also provides examples with LLMs. In a previous blog post<\/a>, we described some of the NLP tasks you can tackle by using the code in the repository. This blog post<\/a> focused on accessing local LLMs.\r\n
<\/h6>\r\n \r\n
<\/h6>\r\n

AI Applications<\/strong><\/p>\r\n \r\n\r\n\r\n\r\n\r\n\r\n\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
AI for Signal Processing<\/strong><\/a><\/td>\r\nAI for Wireless Communications<\/strong><\/a><\/td>\r\n<\/tr>\r\n
\"\"<\/td>\r\n\"\"<\/td>\r\n<\/tr>\r\n
Machine Learning and Deep Learning Classification Using Signal Feature Extraction Objects<\/a><\/td>\r\nCompare Residual Recurrent Neural Network Structures for Digital Predistortion Design<\/a><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/h6>","protected":false},"excerpt":{"rendered":"
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\r\nIn my last post, I talked about new AI features introduced with MATLAB R2024b - the latest release, which is now available to you. In this blog post, I am going to present a few new and exciting... read more >><\/a><\/p>","protected":false},"author":194,"featured_media":16172,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[36,9,5,12,59],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/posts\/16160"}],"collection":[{"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/users\/194"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/comments?post=16160"}],"version-history":[{"count":40,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/posts\/16160\/revisions"}],"predecessor-version":[{"id":17366,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/posts\/16160\/revisions\/17366"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/media\/16172"}],"wp:attachment":[{"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/media?parent=16160"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/categories?post=16160"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.mathworks.com\/deep-learning\/wp-json\/wp\/v2\/tags?post=16160"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}