Are ChatGPT and AlphaCode going to replace programmers? – Nature.com
Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.
Advertisement
You can also search for this author in PubMed Google Scholar
You have full access to this article via your institution.
AIs are competing with humans to write code.Credit: Getty
Artificial intelligence (AI) researchers have been impressed by the skills of AlphaCode, an AI system that can often compete with humans at solving simple computer-science problems. Google sister company DeepMind, an AI powerhouse based in London, released the tool in February and has now published its results in Science1, showing that AlphaCode beat about half of humans at code competitions.
And in the past week or so, social-media users have been mesmerized by the ability of another chatbot, called ChatGPT, to produce occasionally meaningful-sounding (and sometimes sublimely ridiculous) mini-essays on request — including short computer programs. But these state-of-the-art AIs can perform only rather limited tasks, and researchers say they are far from being able to replace human programmers.
ChatGPT, the latest version of a natural-language system by software company OpenAI of San Francisco, California, was released on 30 November. Both ChatGPT and AlphaCode are ‘large language models’ — systems based on neural networks that learn to perform a task by digesting massive amounts of existing human-generated text. In fact, the two systems use “virtually the same architecture”, says Zico Kolter, a computer scientist at Carnegie Mellon University in Pittsburgh, Pennsylvania. “And while there are of course minor differences in the training and execution, the main difference, if there is any, is that they are simply trained upon different data sets, and thus for different tasks.”
Whereas ChatGPT is a general-purpose conversation engine, AlphaCode is more specialized: it was trained exclusively on how humans answered questions from software-writing contests. “AlphaCode was designed and trained specifically for competitive programming, not for software engineering,” David Choi, a research engineer at DeepMind and a co-author of the Science paper, told Nature in an e-mail.
Researchers have pointed out that much of the work that goes into a large software-engineering project — say, designing a web browser — involves understanding the needs of humans who are going to use it. These are difficult to describe with the simple, machine-readable specifications that an AI can use to produce code.
Kolter says that it’s unclear whether it will ever be possible for machines to generate large-scale software systems from scratch. But “my best guess is that tools like these that can generate portions of a program will likely become ‘second-nature’ kind of tools for programmers”, he says.
“We hope that further research will result in tools to enhance programmer productivity and bring us closer to a problem-solving AI,” Choi says.
Kolter adds that there are already some AI tools good enough to make programmers’ jobs easier, such as one called Copilot, a code autocompletion service introduced last year by code repository GitHub and based on OpenAI technology.
doi: https://doi.org/10.1038/d41586-022-04383-z
Li, Y. et al. Science 378, 1092–1097 (2022).
Article Google Scholar
Download references
Open-source language AI challenges big tech’s models
Robo-writers: the rise and risks of language-generating AI
Don’t ask if artificial intelligence is good or fair, ask how it shifts power
DeepMind AI topples experts at complex game Stratego
DeepMind AI topples experts at complex game Stratego
News
Food: use artificial intelligence to create new proteins
Correspondence
Spatial genomics maps the structure, nature and evolution of cancer clones
Article
AI bot ChatGPT writes smart essays — should academics worry?
News Explainer
Is China open to adopting a culture of innovation?
Nature Index
Driven quantum bits push computational limit
News & Views
Columbia University Medical Center (CUMC), CU
New York, NY, United States
University of California San Francisco (UCSF)
San Francisco, CA, United States
University of Hawai'i at Manoa (UH Mānoa)
Honolulu, United States
University of Kentucky (UK)
Lexington, KY, United States
You have full access to this article via your institution.
Open-source language AI challenges big tech’s models
Robo-writers: the rise and risks of language-generating AI
Don’t ask if artificial intelligence is good or fair, ask how it shifts power
DeepMind AI topples experts at complex game Stratego
An essential round-up of science news, opinion and analysis, delivered to your inbox every weekday.
Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.
© 2022 Springer Nature Limited