Google Colab Promises 'AI-Powered Coding, Free of Charge'

Google Colab hosts free cloud-based "executable documents" that, among other things, let you write and run code in your browser (in dozens of languages, including Python). Over 7 million people, including students, already use Colab, according to a recent post on Google's blog, "and now it's getting even better with advances in AI [with] features like code completions, natural language to code generation and even a code-assisting chatbot." Google says it will "dramatically increase programming speed, quality, and comprehension." Our first features will focus on code generation. Natural language to code generation helps you generate larger blocks of code, writing whole functions from comments or prompts. [For example: "import data.csv as a dataframe."] The goal here is to reduce the need for writing repetitive code, so you can focus on the more interesting parts of programming and data science. Eligible users in Colab will see a new "Generate" button in their notebooks, allowing them to enter any text prompt to generate code. For eligible paid users, as you type, you'll see autocomplete suggestions. We're also bringing the helpfulness of a chatbot directly into Colab. Soon, you'll be able to ask questions directly in Colab like, "How do I import data from Google Sheets?" or "How do I filter a Pandas DataFrame?" Anyone with an internet connection can access Colab, and use it free of charge... Access to these features will roll out gradually in the coming months, starting with our paid subscribers in the U.S. and then expanding into the free-of-charge tier. It's powered by Google's "next generation" machine-learning language model PaLM 2 (announced earlier this month), which "excels at popular programming languages like Python and JavaScript, but can also generate specialized code in languages like Prolog, Fortran and Verilog." Colab will use Codey, a family of code models built on PaLM 2... fine-tuned on a large dataset of high quality, permissively licensed code from external sources to improve performance on coding tasks. Plus, the versions of Codey being used to power Colab have been customized especially for Python and for Colab-specific uses.

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