Ref: https://t.comms.acs.org.au/r/?id=h2bceda3,28cf8902,28cf8911


DeepMind’s new AI can write code

https://deepmind.com/

AlphaCode can understand abstract programming problems.

https://alphacode.deepmind.com/

By Casey Tonkin on Feb 14 2022 04:20 PM


A new programming AI system from DeepMind, Alphabet’s experimental AI research 
arm, can perform complex coding tasks better than the average programmer and 
could lead to the AI that can change itself.

AlphaCode was trained using open source code from GitHub and was put to the 
test solving abstract coding problems from the competitive programming platform 
Codeforces.  https://codeforces.com/

These are tests of programming nous that typically involve solving an esoteric 
programming problem from a qualitative description.

It’s a difficult thing for an AI to differentiate AlphaCode from OpenAI’s Codex 
which can interpret natural language requests into written code.

AlphaCode performed in the top 54 per cent of participants in coding 
competitions held on Codeforces late last year, which is quite a feat for a 
machine that first has to parse the complex description of the problem written 
in natural language before it begins coding.

“Going from ‘what the problem is’ to ‘how to solve the problem’ is a great leap 
that requires understanding and reasoning about the problem, as well as a deep 
comprehension of a wide range of algorithms and data structures,” the authors 
of a recent paper about AlphaCode wrote.

“This leap is a significant difference from previous works, which tend to 
explicitly specify what to implement.”

AlphaCode was trained on 715GB of code in most major languages like C++, C#, 
Go, Java, JavaScript, Python, Ruby, and PHP.

DeepMind’s researchers hinted what AlphaCode could lead to down the track 
including what the authors describe as “advanced AI risks” such as an AI system 
that is able to re-write its own underlying code.

“Coding capabilities could lead to systems that can recursively write and 
improve themselves, rapidly leaning to more and more advanced systems,” the 
researchers warn.

Yes, this coding bot could lead to the singularity – a hypothetical moment when 
an AI system quickly makes changes to itself in what philosopher Nick Bostrom 
has described as “an intelligence explosion” that could lead to a 
superintelligent, and not necessarily benign, AI.

Professor Scott Aaronson from the University of Texas’s computer science 
department described the paper as “absolutely astounding” but isn’t sold on the 
idea of AlphaCode leading to the singularity.

“Judged against where AI was 20-25 years ago, when I was a student, a dog is 
now holding meaningful conversations in English,” he said in a blog post.

“It’s not obvious how you go from solving programming contest problems to 
conquering the human race or whatever, but I feel pretty confident that we’ve 
now entered a world where ‘programming’ will look different.”

Other risks identified with AlphaCode include intellectual property concerns as 
the researchers note that there is debate around whether it is “fair use” to 
train an AI on publicly available code like GitHub, even if the data is 
filtered for certain licenses.

“There still remains the decision of how to credit and use people’s code, even 
with permissive licenses.”

Breakthroughs in automated coding could also lead to a glut of programmers, the 
researchers warn, although they said the effects of automation could be 
overstated since “writing code is only a portion of the job”.

They also note that other times when coding has been automated, such as through 
the development of integrated development environments (IDE), “have only moved 
programmers to higher levels of abstraction”.

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