Google’s Bard finally gets some coding skills and an important feature



Google has given its chatbot Bard an update that allows it to generate code in over 20 programming languages. The update also brings a feature that sets Bard apart from ChatGPT.

In addition to writers who string sentences together in natural language, one audience, in particular, has benefited from the progress of large language models: programmers. There are many reports of users who have been able to implement their own software ideas using ChatGPT or other language models without any real programming knowledge.

Often a basic understanding of the syntax is helpful, and it is not uncommon for the AI ​​to take several tries before it produces error-free code. Nevertheless, language models are a very helpful tool.

More than 20 programming languages, including Google Sheets syntax

Until now, however, Google’s ChatGPT alternative, Bard, lagged behind – the chatbot could not code. This is about to change, the search giant announced in a blog post: Bard now supports more than 20 programming languages, including C++, Go, Java, Javascript, Python, and Typescript.


Code written in Python, which plays a dominant role in machine learning, can be exported with a click to a Google Colab notebook (similar to a virtual machine for running Python in the browser). Conveniently, Google’s AI also masters Google’s own syntax for the spreadsheet program Sheets.

Video: Google

In addition to generating code, Bard can also explain a program line by line, debug it, or simply improve it, for example, to reduce runtime.

Bard shows open-source project sources

Paige Bailey, a product manager at Google Research, stresses that Bard’s coding capabilities are still in the early stages of development, so the AI ​​may spit out “inaccurate, misleading or false information while presenting it confidently.”

In this respect, Bard doesn’t really differ from ChatGPT and the like. Unlike OpenAI’s previous solutions, however, Bard does provide a source when it takes large chunks of code from an open-source project, according to Bailey.


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