Tabnine updates AI-based code writing assistant for developers


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tabninDeveloping an AI-powered assistant for software developers that can anticipate writing code for specific apps and fill in blanks with appropriate snippets, launched a new version of its time-saving application programming interface on June 15.

The company, which uses a freemium-plus-service provisioning business model, also said it will have eclipsed the 1 million user mark on its API by 2022.

Tel Aviv-based Tabnine’s software has a long memory for finding reusable code in 31 languages, including Python, JavaScript, Java, C#, TypeScript and other languages ​​available today in both Visual Studio Code and IntelliJ IDEs, CEO Dror said. Weiss to VentureBeat.

“The use case of our product is very simple,” Weiss said. “Your developer is writing code in her IDE and she has a topline installed as part of her editor. We look at the code being created in real time, and contextually we query the AI ​​engine in real time; we then suggest parts like the big next line or snippets or a block of code that the developer needs. The app very quickly assesses whether this is what they intended to do, and they accept the code. This happens most often with basically zero change in the process.”

Ninety percent of all code is already written

Ninety percent of all code is already written and doesn’t need to be created from scratch, Weiss said.

Developers are now seeing 30% to 40% of their code generated automatically using the Tabnine API without having to deviate, Weiss said. “No code has changed from the standard workflow of writing code in their favorite editor, and it works for all popular ideas or code editors and all popular programming languages,” he said.

Over the past year, Weiss said, Tabnine has refreshed both its AI models and its approach to integrating new models into its platform. Unlike a monolithic approach that mandates a single AI model, Tabnine is now able to support any compatible AI model to guide developers, Weiss said.

From infrastructure-as-code to continuous integration, companies that have implemented devops in recent years have seen productivity improvements in their software development and release processes. But those productivity benefits have mostly stopped at the developer’s keyboard, as an explosion of frameworks, tools, languages ​​and APIs has only made a developer’s job harder, Weiss said.

AI has great potential to help developer productivity

AI has the potential to do for developer productivity what CI has done for the release process, Weiss said.

“Every day we get great feedback from developers and teams that Tabnine’s AI is now part of their flow, giving them time to focus on higher-value activities,” Weiss said in a media advisory. “With longer and better code completions, our next-generation AI technology is a major step forward for developer productivity, further establishing Tabnine as the leader in AI-powered software development.”

The next-generation platform includes a dozen new AI models, each code-trained from the ground up (vs. models pre-trained on text and built-in to learn code afterwards). Each model is optimized for a specific language or domain, allowing Tabnine to contextually fill in entire lines and code snippets with unprecedented accuracy, Weiss said.

Founded in 2017, Tabnine also announced it has raised $15.5 million in funding from Qualcomm Ventures, OurCrowd and Samsung NEXT Ventures, with participation from existing investors including Khosla Ventures, Headline Ventures, Hetz Ventures and TPY Capital. With this latest capital injection, Tabnine has raised a total of $32 million so far.

Tabnine claims to be the only such AI-powered software development tool of its kind on the market, Weiss said.

The latter funding will be used to further accelerate development of Tabnine’s platform to add support for additional AI models and programming languages ​​later this year, Weiss said.

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