{"id":367,"date":"2022-08-03T13:00:25","date_gmt":"2022-08-03T13:00:25","guid":{"rendered":"https:\/\/pc-keeper.tech\/index.php\/2022\/08\/03\/boosting-productivity-at-meta-ieee-computer-society\/"},"modified":"2022-08-03T13:00:25","modified_gmt":"2022-08-03T13:00:25","slug":"boosting-productivity-at-meta-ieee-computer-society","status":"publish","type":"post","link":"https:\/\/pc-keeper.tech\/index.php\/2022\/08\/03\/boosting-productivity-at-meta-ieee-computer-society\/","title":{"rendered":"Boosting Productivity at Meta | IEEE Computer Society"},"content":{"rendered":"

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\"LeveragingAI has become a ubiquitous element of daily life, playing a role in everything from self-driving cars to automated chatbots and enjoying phenomenal growth. The sector is expected to expand 47% between 2021 and 2022. Meta (formerly Facebook) is now using AI as an integral part of its app development process. A look at how the social media giant is leveraging this technology demonstrates its potential in the development sphere. Meta\u2019s engineers accomplish this feat using three productivity tools: code search using natural language, code recommendation, and automatic bug fixing.<\/p>\n

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Code Search Using Natural Language<\/h2>\n
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Instead of manually studying existing APIs that can do something similar to what they\u2019re trying to code, Meta programmers use natural language processing to search through existing code in GitHub. This way, they can identify the relevant code snippets they need to design and refine their solutions.<\/p>\n

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Code Recommendation<\/h2>\n
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