Deep TabNine System
A Deep TabNine System is a Code Auto-Completion System that is based on a Deep Learning Neural Network.
- Context:
- It can solve a Deep TabNine Autocompleter Task by implementing a Deep TabNine Autocompleter Algorithm.
- It is based on GPT-2 which uses the Transformer Network architecture.
- Example(s):
- Counter-Example(s):
- See: OpenAI, Misspelling Correction System, Parsing System, Text Wikification System, Wiki Markup Language, Text Error Detection System, Natural Language Processing System.
References
2019a
- (Tabnine, 2019) ⇒ "Autocompletion with deep learning". Published online on July 15, 2019.
- QUOTE: (...) TabNine is an autocompleter that helps you write code faster. We’re adding a deep learning model which significantly improves suggestion quality.(...)
Deep TabNine is trained on around 2 million files from GitHub.(...)
Deep TabNine is based on GPT-2, which uses the Transformer network architecture. This architecture was first developed to solve problems in natural language processing. Although modeling code and modeling natural language might appear to be unrelated tasks, modeling code requires understanding English in some unexpected ways.
- QUOTE: (...) TabNine is an autocompleter that helps you write code faster. We’re adding a deep learning model which significantly improves suggestion quality.(...)
2019b
- (Slashdot, 2019) ⇒ https://developers.slashdot.org/story/19/07/28/2034251/new-ai-assisted-coding-tool-called-amazing Retrieved: 2019-09-08.
- QUOTE: By scanning huge datasets of text, machine learning software can produce convincing samples of everything from short stories to song lyrics. Now, those same techniques are being applied to the world of coding with a new program called Deep TabNine, a “coding autocompleter”. Programmers can install it as an add-on in their editor of choice, and when they start writing, it'll suggest how to continue each line, offering small chunks at a time. Think of it as Gmail's Smart Compose feature but for code.
Jacob Jackson, the computer science undergrad at the University of Waterloo who created Deep TabNine, says this sort of software isn't new, but machine learning has hugely improved what it can offer... Earlier this month, he released an updated version that uses a deep learning text-generation algorithm called GPT-2, which was designed by the research lab OpenAI, to improve its abilities. The update has seriously impressed coders, who have called it "amazing," "insane," and "absolutely mind-blowing" on Twitter ...
Deep TabNine is trained on 2 million files from coding repository GitHub. It finds patterns in this data and uses them to suggest what's likely to appear next in any given line of code, whether that's a variable name or a function ... Most importantly, thanks to the analytical abilities of deep learning, the suggestions Deep TabNine makes are of a high overall quality. And because the software doesn't look at users' own code to make suggestions, it can start helping with projects right from the word go, rather than waiting to get some cues from the code the user writes.
- QUOTE: By scanning huge datasets of text, machine learning software can produce convincing samples of everything from short stories to song lyrics. Now, those same techniques are being applied to the world of coding with a new program called Deep TabNine, a “coding autocompleter”. Programmers can install it as an add-on in their editor of choice, and when they start writing, it'll suggest how to continue each line, offering small chunks at a time. Think of it as Gmail's Smart Compose feature but for code.
2019c
- (Caballer, 2019) ⇒ Rina Diane Caballar (August 26, 2019). "Q&A: This Autocompletion Tool Aims to Supercharge Your Coding". IEEE Spectrum.
- QUOTE: (...) Deep TabNine, a code autocompletion tool. Jackson, a computer science undergraduate student at the University of Waterloo, in Canada, and a previous intern at AI research company OpenAI, first launched TabNine as a code completion plug-in in November 2018, and then added deep-learning capabilities to create what’s now known as Deep TabNine.
Deep TabNine uses GPT-2—a natural-language-processing model designed by OpenAI—to generate relevant coding suggestions and predict the elements in each line of code. Similar to how OpenAI trained GPT-2 on a data set of 8 million web pages to “predict the next word given all of the previous words within some text,” Jackson used GPT-2 to train Deep TabNine on an estimated 2 million files from source-code-hosting and version-control platform GitHub to “predict each token given the tokens that come before it.”
Deep TabNine works with existing code editors and integrated-development environments (IDEs) and currently supports 22 programming languages, including C++, CSS, HTML, Java, JavaScript, PHP, Python, and SQL.
- QUOTE: (...) Deep TabNine, a code autocompletion tool. Jackson, a computer science undergraduate student at the University of Waterloo, in Canada, and a previous intern at AI research company OpenAI, first launched TabNine as a code completion plug-in in November 2018, and then added deep-learning capabilities to create what’s now known as Deep TabNine.