{"id":2530143,"date":"2023-03-28T20:15:26","date_gmt":"2023-03-29T00:15:26","guid":{"rendered":"https:\/\/platoai.gbaglobal.org\/platowire\/google-introduces-its-own-ai-code-suggestion-bot\/"},"modified":"2023-03-28T20:15:26","modified_gmt":"2023-03-29T00:15:26","slug":"google-introduces-its-own-ai-code-suggestion-bot","status":"publish","type":"platowire","link":"https:\/\/platoai.gbaglobal.org\/platowire\/google-introduces-its-own-ai-code-suggestion-bot\/","title":{"rendered":"Google introduces its own AI code-suggestion bot"},"content":{"rendered":"<p>Google, the tech giant, has introduced its own AI code-suggestion bot, which is designed to help developers write better code. The bot, called &#8216;CodeSearchNet Challenge&#8217;, is a machine learning model that can provide suggestions for code snippets based on the context of the code being written.<\/p>\n<p>The CodeSearchNet Challenge is built on top of the CodeSearchNet dataset, which contains over two million code snippets from open-source repositories. The dataset was created by Google&#8217;s AI team to help improve code search and code understanding. The team used natural language processing techniques to extract contextual information from the code snippets, such as function names, variable names, and comments.<\/p>\n<p>The CodeSearchNet Challenge uses this contextual information to provide suggestions for code snippets that are relevant to the code being written. For example, if a developer is writing code to sort an array, the bot might suggest a code snippet that sorts an array using a specific algorithm.<\/p>\n<p>The bot is designed to be integrated into existing code editors, such as Visual Studio Code and IntelliJ IDEA. Developers can use the bot by typing a keyword or phrase into the editor, and the bot will provide suggestions for code snippets based on the context of the code being written.<\/p>\n<p>The CodeSearchNet Challenge is part of Google&#8217;s ongoing efforts to improve the developer experience. By providing better code suggestions, Google hopes to help developers write better code more quickly and efficiently. The bot is also part of Google&#8217;s broader efforts to advance AI and machine learning technologies.<\/p>\n<p>Google is not the only company working on AI-powered code suggestions. Microsoft has also developed an AI-powered code suggestion tool called IntelliCode, which is integrated into Visual Studio Code. Other companies, such as Codota and Kite, are also working on similar tools.<\/p>\n<p>In conclusion, Google&#8217;s CodeSearchNet Challenge is an exciting development for developers who are looking for better ways to write code. By using AI and machine learning technologies, Google has created a tool that can provide relevant and useful code suggestions based on the context of the code being written. As AI and machine learning technologies continue to advance, we can expect to see more tools like this that help developers write better code more efficiently.<\/p>\n<ul class=\"plato-post-bottom-links\">\n<li class=\"plato-post-bottom-link-amplifi\">SEO Powered Content &amp; PR Distribution. <a href=\"https:\/\/www.amplifipr.com\" target=\"_blank\" rel=\"noopener\">Get Amplified Today.<\/a><\/li>\n<li class=\"plato-post-bottom-link-platoblockchain\">PlatoAiStream. Web3 Intelligence. Knowledge Amplified. <a href=\"https:\/\/platoaistream.com\" target=\"_blank\" rel=\"noopener\">Access Here.<\/a><\/li>\n<li class=\"plato-post-bottom-link-source\"><span>Source: Plato Data Intelligence:<\/span> <a rel=\"noopener\" target=\"_blank\" href=\"https:\/\/platodata.io\">PlatoData<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Google, the tech giant, has introduced its own AI code-suggestion bot, which is designed to help developers write better code. The bot, called &#8216;CodeSearchNet Challenge&#8217;, is a machine learning model that can provide suggestions for code snippets based on the context of the code being written. The CodeSearchNet Challenge is built on top of the [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":2527037,"menu_order":0,"template":"Default","format":"standard","meta":[],"aiwire-tag":[1974,562,2146,566,11,16,17,132,18,20,7982,21,315,23,140,369,24244,2449,28,29,218,219,796,2403,1772,727,222,2336,5103,2456,7315,37,1324,19330,38,157,4561,39,867,4075,25610,532,1198,1613,806,162,807,163,3234,50,1619,51,5762,2472,241,26104,245,11987,1798,169,605,3702,477,1234,13695,60,62,7119,1432,609,1053,252,293,611,612,3271,615,1658,1659,1063,69,1936,397,17099,17100,75,78,895,487,184,185,354,824,6211,5,10,7,8,4963,190,661,89,897,2429,496,5786,909,7501,3305,5007,1118,5333,103,2630,11468,104,1830,5020,203,108,109,111,557,1377,275,115,428,307,429,6075,211,430,10606,9315,310,9,311,124,341,3956,1144,1478,6],"aiwire":[27172],"_links":{"self":[{"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/platowire\/2530143"}],"collection":[{"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/platowire"}],"about":[{"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/types\/platowire"}],"author":[{"embeddable":true,"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/users\/2"}],"version-history":[{"count":0,"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/platowire\/2530143\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/media\/2527037"}],"wp:attachment":[{"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/media?parent=2530143"}],"wp:term":[{"taxonomy":"aiwire-tag","embeddable":true,"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/aiwire-tag?post=2530143"},{"taxonomy":"aiwire","embeddable":true,"href":"https:\/\/platoai.gbaglobal.org\/wp-json\/wp\/v2\/aiwire?post=2530143"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}