Code like a Pro with DeepMind's AlphaCode – Analytics India Magazine

DeepMind’s AlphaCode has emerged as one of the hottest open-source code generators, besides OpenAI’s Codex, Tabnine, CodeWhisperer, and others. If you are new to programming, these tools will make you stand out from the crowd. 
In February this year, the developers at DeepMind examined the potential of AlphaCode by testing it in competitive programming websites where human developers are given programming problems and ranked on the basis of their results.
One of them was a competitive coding competition on Codeforces, a popular platform for hosting coding competitions. A selection of ten varied test problems from different stages of development was given to AlphaCode. The AI tool achieved an estimated rank within the top 54 percentile of participants that attended the contest, thus proving that AlphaCode’s code generation system has achieved results at a competitive level.
AlphaCode’s AI system is pre-trained in various programming languages that include C++, C#, Go, Java, JavaScript, Lua, PHP, TypeScript, Ruby, Scala, Rust and Python. This dataset consists of approximately 715 GB of codes along with their descriptions.
Through AlphaCode, DeepMind has been able to fill the gap that is lacking in AI models like Codex—problem-solving skills. AlphaCode has not only been trained to “understand” natural language but also to design complex programmes and algorithms and implement them in code. It has also been trained  to convert problem descriptions into code using thousands of problems from coding competitions. 
When presented with a fresh problem, AlphaCode generates candidate code solutions (in Python or C++) compared to GPT-3 algorithms, and filters out the bad ones. Whereas researchers had previously used models like Codex to generate tens or hundreds of candidates, DeepMind had AlphaCode generate up to more than 1 million.
OpenAI’s AI code suggestion tool GitHub Copilot runs on the natural language processing (NLP) model Codex, a boosted version of GPT-3. While it is built with the vision to achieve goals that are similar to that of AlphaCode, Copilot seems to have a difficult road ahead. Here are some of the differences between the two code generation tools:
Despite Alphacode performing well in coding competitions, these are usually focused on solving programming problems and giving solutions in the least time possible. Thus, this may not be a fair measure of real time usage.
Most real world problems need realistic and contextual solutions which need developers and programmers to think and solve complex problems, design systems, make design choices, provide different solutions and more. So, in essence, Alphacode might be able to implement coding for already known solutions reasonably well but will likely fail to perform when it comes to solving real world engineering problems.
So, it can implement but not invent! 
Recently, OpenAI’s ChatGPT has also been able to solve some programming puzzles. Robert Sweeney, a tech entrepreneur, shared in a LinkedIn post that the chatbot was able to get a working solution with an explanation for a Leetcode question in less than ten seconds!
However, Ritesh Menon, a tech expert, revealed in another post that ChatGPT’s responses are articulate but not always accurate. Menon pointed out that while the tool does correctly solve some easy programming puzzles, it falters when faced with more difficult problems. In addition, it gives bizarre answers with equally plausible explanations when one hits the ‘ try again’ option against its responses.
Besides these,  Salesforce’s Codegen is also another tool for coders. It is a 16-billion parameter, auto-regressive language model trained on a large corpus of natural and programming languages. Codegen can handle simple coding tasks but not so much when it comes to more complex problems.
In June 2022, Amazon also released CodeWhisperer, a machine learning-powered service that helps improve developer productivity by generating code recommendations based on developers’ comments in natural language and their code in the integrated development environment. Amazon claims that developers can speed up the development process with CodeWhisperer by simply writing a comment in their IDE’s code editor.
This month, Google Labs also unveiled Pitchfork, an AI that can convert old code to new code and rewrite itself. The list just goes on. 
While these systems attest to what is possible with AI today in the realm of computer programming, only a few of such systems are open source. In an effort to change this, AI startup Hugging Face and ServiceNow Research R&D division launched BigCode, a new project that aims to develop “state-of-the-art” AI systems for code in an “open and responsible” way. 
The BigCode team said that the goal is to eventually release a dataset large enough to train a code-generating system, which will then be used to create a prototype—a 15-billion-parameter model, larger in size than Codex (12 billion parameters) but smaller than AlphaCode (~41.4 billion parameters)—using ServiceNow’s in-house graphics card cluster.
It’s not always rainbows and butterflies for auto-code generating platforms. In November, Kite, an AI assisting tool that helps developers write code, announced that it would no longer be operational. The platform augments the coding environment with the internet’s programming knowledge and machine learning—similar to GitHub Copilot, which uses OpenAI CodeX, a version of GPT-3 language model. 

Workshop, Online
Linear Algebra with Python for Data Science
17th Dec 2022
Regular passes expiring on 30th Dec
Conference, in-person (Bangalore)
Machine Learning Developers Summit (MLDS) 2023
19-20th Jan, 2023
Conference, in-person (Bangalore)
Rising 2023 | Women in Tech Conference
16-17th Mar, 2023
Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
27-28th Apr, 2023
Conference, in-person (Bangalore)
MachineCon 2023
23rd Jun, 2023
Conference, in-person (Bangalore)
Cypher 2023
20-22nd Sep, 2023
Discover special offers, top stories, upcoming events, and more.
Stay Connected with a larger ecosystem of data science and ML Professionals
Stay up to date with our latest news, receive exclusive deals, and more.
© Analytics India Magazine Pvt Ltd 2022
Terms of use
Privacy Policy
Copyright

source

Note that any programming tips and code writing requires some knowledge of computer programming. Please, be careful if you do not know what you are doing…

Post expires at 7:04pm on Wednesday March 15th, 2023

Leave a Reply

Next Post

Australian Regulators Eye Cryptocurrency Regulations in 2023 By CoinEdition - Investing.com

Thu Dec 15 , 2022
Australian Regulators Eye Cryptocurrency Regulations in 2023 By CoinEdition  Investing.comsource Post expires at 7:04pm on Wednesday March 15th, 2023

You May Like

%d bloggers like this: