• IEEE.org
  • IEEE CS Standards
  • Career Center
  • About Us
  • Subscribe to Newsletter

0

IEEE-CS_LogoTM-orange
  • MEMBERSHIP
  • CONFERENCES
  • PUBLICATIONS
  • EDUCATION & CAREER
  • VOLUNTEER
  • ABOUT
  • Join Us
IEEE-CS_LogoTM-orange

0

IEEE Computer Society Logo
Sign up for our newsletter
IEEE COMPUTER SOCIETY
About UsBoard of GovernorsNewslettersPress RoomIEEE Support CenterContact Us
COMPUTING RESOURCES
Career CenterCourses & CertificationsWebinarsPodcastsTech NewsMembership
BUSINESS SOLUTIONS
Corporate PartnershipsConference Sponsorships & ExhibitsAdvertisingRecruitingDigital Library Institutional Subscriptions
DIGITAL LIBRARY
MagazinesJournalsConference ProceedingsVideo LibraryLibrarian Resources
COMMUNITY RESOURCES
GovernanceConference OrganizersAuthorsChaptersCommunities
POLICIES
PrivacyAccessibility StatementIEEE Nondiscrimination PolicyIEEE Ethics ReportingXML Sitemap

Copyright 2026 IEEE - All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  • Home
  • /Publications
  • /Tech News
  • /Research
  • Home
  • / ...
  • /Tech News
  • /Research

Leveraging AI: Going Beyond Local Productivity Boosters at Meta

By IEEE Computer Society Team on
August 3, 2022

Leveraging machine learning to boost productivity of software engineers at MetaAI 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’s engineers accomplish this feat using three productivity tools: code search using natural language, code recommendation, and automatic bug fixing.


Want More Tech News? Subscribe to ComputingEdge Newsletter Today!


Code Search Using Natural Language


Instead of manually studying existing APIs that can do something similar to what they’re 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.

Code Recommendation


LATEST NEWS
Cloud-Driven Agentic AI: A New Era of Intelligent Automation
Cloud-Driven Agentic AI: A New Era of Intelligent Automation
Charting a Vision for the Future of Drone Computing
Charting a Vision for the Future of Drone Computing
Engineering the AI-Native Enterprise: Multi-Agent Systems, Multi-Model Strategy, and Spec-Driven Development
Engineering the AI-Native Enterprise: Multi-Agent Systems, Multi-Model Strategy, and Spec-Driven Development
Computing’s Top 30: Gabriele Serra
Computing’s Top 30: Gabriele Serra
Computing’s Top 30: Achyut Sarma Boggaram
Computing’s Top 30: Achyut Sarma Boggaram
Get the latest news and technology trends for computing professionals with ComputingEdge
Sign up for our newsletter
Read Next

Cloud-Driven Agentic AI: A New Era of Intelligent Automation

Charting a Vision for the Future of Drone Computing

Engineering the AI-Native Enterprise: Multi-Agent Systems, Multi-Model Strategy, and Spec-Driven Development

Computing’s Top 30: Gabriele Serra

Computing’s Top 30: Achyut Sarma Boggaram

Fueling Innovation: Highlights from the Astro Code 2026 Hackathon in Jordan

Episode 8 | How to Build a Career That Actually Matters to You

Computing’s Top 30: Vishnupriya S. Devarajulu