Goto

Collaborating Authors

IBM's Project CodeNet will test how far you can push AI to write software

#artificialintelligence

IBM's AI research division has released a 14-million-sample dataset to develop machine learning models that can help in programming tasks. Called Project CodeNet, the dataset takes its name after ImageNet, the famous repository of labeled photos that triggered a revolution in computer vision and deep learning. While there's a scant chance that machine learning models built on the CodeNet dataset will make human programmers redundant, there's reason to be hopeful that they will make developers more productive. In the early 2010s, impressive advances in machine learning triggered excitement (and fear) about artificial intelligence soon automating many tasks, including programming. But AI's penetration in software development has been extremely limited.


IBM's Project CodeNet will test how far you can push AI to write software

#artificialintelligence

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. IBM's AI research division has released a 14-million-sample dataset to develop machine learning models that can help in programming tasks. Called Project CodeNet, the dataset takes its name after ImageNet, the famous repository of labeled photos that triggered a revolution in computer vision and deep learning. While there's a scant chance that machine learning models built on the CodeNet dataset will make human programmers redundant, there's reason to be hopeful that they will make developers more productive. In the early 2010s, impressive advances in machine learning triggered excitement (and fear) about artificial intelligence soon automating many tasks, including programming.


IBM CodeNet: Artificial Intelligence That Can Program Computers And Solve A $100 Billion Legacy Code Problem

#artificialintelligence

Computer scientists have long toyed with the idea of creating computers that could write programs for other computers. Artificial intelligence is an obvious technology for the task. It has been previously used for programming on a small scale but unfortunately the results have been limited. Artificial intelligence is one of our most powerful and versatile technologies in use today. It can understand and generate speech, analyze documents, recognize images and characters, drive cars, pilot war planes, write papers, and perform thousands of other valuable operations.


Can we teach AI how to code? Welcome to IBM's Project CodeNet

#artificialintelligence

IBM's AI research division has released a 14-million-sample dataset to develop machine learning models that can help in programming tasks. Called Project CodeNet, the dataset takes its name after ImageNet, the famous repository of labeled photos that triggered a revolution in computer vision and deep learning. While there's a scant chance that machine learning models built on the CodeNet dataset will make human programmers redundant, there's reason to be hopeful that they will make developers more productive. In the early 2010s, impressive advances in machine learning triggered excitement (and fear) about artificial intelligence soon automating many tasks, including programming. But AI's penetration in software development has been extremely limited.


What is IBM's Project CodeNet?

#artificialintelligence

At its recently concluded Think 2021 conference, IBM introduced Project CodeNet to develop machine learning models that can help in programming. The large dataset consists of 14 million code samples and 500 million lines of code in over 55 different languages, including C, Java, Go, Python, COBOL, Pascal, and Fortran. Modern computer programs have millions of lines of code and are hard to debug, maintain, update, and document. The use of artificial intelligence to write codes has been an important area of research for many years. However, it is easier said than done.