Artificial intelligence can write itself

As soon as Tom Smith was able to get in touch with Codex – a new technology for artificial intelligence who writes his own computer programs — he interviewed him for a job.

He asked if he could solve the “code challenges” that programmers often face when interviewing them for jobs that could make a lot of money at software companies. Silicon Valley What Google and Facebook.

Could you write a program that hyphens to replace all spaces in a sentence?

Tom Smith in his studio in Lafayette, California. Photo Jason Henry / The New York Times.

Even better, could you write one that identifies invalid zip codes?

He did both in an instant, before completing various tasks.

“These are difficult problems for many humans to solve, myself included, and he wrote the answer in two seconds,” said Smith, a seasoned programmer who oversees an artificial intelligence startup called Gado Images.

“It was creepy to see.”

Codex it seemed like a technology that was soon to replace human workers.

As Smith continued to test the system, he found that his abilities extended well beyond a gimmick to answering prepared interview questions.

He could even ttranslate from one programming language to another.

However, after several weeks working with this new technology, Smith believes that it poses no threat to professional programmers.

In fact, like many other experts, he considers it ato tool that will end up boosting human productivity.

You could even help a whole new generation of people learn the art of computers, by showing them how to write little bits of code, almost like a personal tutor.

“This tool can make a programmer’s life a lot easier,” Smith said.

Codex, a product of OpenAI, one of the most ambitious research laboratories in the world, reveals information about the state of artificial intelligence.

Although a wide range of artificial intelligence technologies have improved rapidly during the most recent decade, even the most impressive systems have ended by complementary to human workers instead of replacing them.

Thanks to the rapid rise of a mathematical system called red neuronal, now machines can learn certain skills analyzing huge amounts of data.

For example, after analyzing thousands of photos of cats, they can learn to recognize a cat.

This is the technology that recognizes the orders you give your iPhone, translate between languages ​​in services like Skype and identifies pedestrians and street signs when autonomous vehicles are speeding down the street.

About four years ago, researchers in labs like OpenAI began designing neural networks to analyze huge amounts of prose, including thousands of digital books, articles of Wikipedia and all types of other texts published on the internet.

By locating the patterns in all those texts, the networks learned to predict the next word in a sequence.

When someone typed a few words into these “universal language patterns,” they could complete the idea with entire paragraphs.

In this way, one system – an OpenAI creation called GPT-3 – was able to write its own publications of Twitter, speeches, poetry and news articles.

To the surprise even of the researchers who built the system, he could type your own computer programs, although they were short and simple.

Apparently, he had learned from an untold number of programs posted on the Internet.

So OpenAI went one step further and trained a new system – Codex – in a huge variety of prose and code.

The result is a system that understands both prose and code … up to a point.

Plain and simple, you can ask it to fall snow with a black background and it will give you the code that creates a virtual snowstorm.

If you ask him for a blue ball that is bouncing, he will also give it to you.

“You can tell it to do something and it will do it,” said Ania Kubow, another programmer who has used the technology.

Codex can generate programs in twelve computer languages ​​and even translate between them.

However, he often makes mistakes, and although his abilities are impressive, he cannot reason like a human.

You can recognize or imitate what you have seen in the past, but you are not agile enough to think for yourself.

Sometimes the programs that Codex generates do not work.

Or they contain security flaws.

Or they don’t even come close to what you want them to do.

OpenAI estimates that Codex produces the correct code 37 percent of the time.

This summer, when Smith used the system as part of a beta testing program, the code he produced was impressive.

However, sometimes it worked only if he made a tiny change, such as altering a command to fit his particular software configuration or adding a digital code necessary to access the internet service he was trying to query.

In other words, Codex was actually only useful for a experienced programmer.

However, it could help programmers get through their daily work much faster.

It could help them find basic building blocks they needed or show them the way to new ideas.

Through technology, GitHub, a popular online service for programmers, now offers Co-pilot, a tool that suggests the next line of code to you, in much the same way as “autocomplete” tools suggest the next word when you type text messages or emails. .

“It’s a mechanism to have code written without having to write a lot of code,” said Jeremy Howard, who founded the artificial intelligence laboratory. and helped create the language technology on which OpenAI’s work is based.

“It is not always correct, but it is quite close.”

Howard and others believe that Codex could also help beginners learn to code.

He is particularly good at generating simple programs from short descriptions in English.

Furthermore, it also works in the other direction, by explaining complex code in English.

Some people, like Joel Hellermark, an entrepreneur from Sweden, are already trying to transform the system into a teaching tool.

“We believed that these tools would completely eliminate the need for humans, but after many years we learned that in reality this was not possible; yet it takes a human trained to review the result, “said Smith.

“Technology is wrong.

And it can be biased.

You still need a person whoand reviewe what you have done and decide what is good and what is not ”.

Codex expands on what a machine can do, but it’s another indication that technology works best with humans at the helm.

“Artificial intelligence is not developing as anyone expected,” said Greg Brockman, CTO at OpenAI.

“It seemed like I was going to do this and that job, and everyone wanted to find out which one was going to come first.

Instead, it is not replacing any work. P

But it is eliminating the part of everyone’s tedious work at the same time.

c.2021 The New York Times Company


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Artificial intelligence can write itself