Amazon Web Services (AWS) has released a series of products aimed at helping other companies develop their own chatbots and image-generation services, backed by artificial intelligence (AI). The move comes as part of a wider AI race following the popularity of ChatGPT, and Google’s move into generative AI Bard.
These products include a generative AI service called Bedrock and Amazon CodeWhisperer, a real-time AI coding companion.
Bedrock gives customers access to foundation models, large machine learning models generative AIs need to work, from AI startup model providers including AI21, Anthropic, and Stability AI, and access to the Titan family of foundation models developed by AWS.
Amazon’s entry into the generative AI space via Bedrock is set to compete with the likes of Microsoft’s generative AI suite, Azure OpenAI Service, which had over 1,000 users as of March this year.
Amazon CEO, Andy Jassy, told CNBC: “Most companies want to use these large language models, but the really good ones take billions of dollars to train and many years and most companies don’t want to go through that. So what they want to do is they want to work off of a foundational model that’s big and great already and then have the ability to customise it for their own purposes. And that’s what Bedrock is.”
Amazon CodeWhisperer, which was originally launched for preview last year, is now generally available and includes a CodeWhisperer individual tier which is free to use for developers. The companion allows developers to stay in their integrated development environments (IDEs) when they need to research something.
Amazon CodeWhisperer generates code suggestions for popular scripts like Python, Java, JavaScript, TypeScript, and C#. However, it also supports Go, Rust, PHP, Ruby, Kotlin, C, C++, Shell scripting, SQL, and Scala. CodeWhisperer is available to developers working in Visual Studio Code, IntelliJ IDEA, CLion, GoLand, WebStorm, Rider, PhpStorm, PyCharm, RubyMine, and DataGrip IDEs (when the appropriate AWS extensions for those IDEs are installed), or natively in AWS Cloud9 or AWS Lambda console.