This week during its re:Invent 2021 conference in Las Vegas, Amazon announced a slew of new AI and machine learning products and updates across its Amazon Web Services (AWS) portfolio. Touching on DevOps, big data, and analytics, among the highlights were a call summarization feature for Amazon Lex and a capability in CodeGuru that helps detect secrets in source code. Amazon's continued embrace of AI comes as enterprises express a willingness to pilot automation technologies in transitioning their businesses online. Fifty-two percent of companies accelerated their AI adoption plans because of the COVID pandemic, according to a PricewaterhouseCoopers study. Meanwhile, Harris Poll found that 55% of companies accelerated their AI strategy in 2020 and 67% expect to further accelerate their strategy in 2021.

Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. Software failures are expensive -- and on the rise. An estimated 19% to 23% of software development projects fail, and Standish Group found that "challenged" projects -- i.e., those that fail to meet scope, time, or budget expectations -- account for about 52% of software projects. According to a joint project by Undo and Cambridge Judge Business School, these bugs cost enterprises about $61 billion annually, and around 620 million developer hours are wasted on debugging.

We are pleased to announce the launch of Python support for Amazon CodeGuru, a service for automated code reviews and application performance recommendations. CodeGuru is powered by program analysis and machine learning, and trained on best practices and hard-learned lessons across millions of code reviews and thousands of applications profiled on open-source projects and internally at Amazon. The launch of Python support extends CodeGuru beyond its original Java support. Python is a widely used language for various use cases, including web app development and DevOps. Python's growth in data analysis and machine learning areas is driven by its rich frameworks and libraries.

This is a guest post co-written by Sergio Delgado from YoucanBook.me. In their own words, "YouCanBook.me is a small, independent and fully remote team, who love solving scheduling problems all over the world." At YoucanBook.me, we like to say that we're "a small company that does great things." Many aspects of our day-to-day culture are derived from such a simple motto, but especially a great emphasis on the efficiency of our operations. Although we're far from the first years in which our CTO programmed the entire first version of our SaaS tool, when I joined the company, we were only five developers, of which only three were in charge of backend services, and none were dedicated to it 100%.

Amazon Web Services Inc. said today its new Amazon CodeGuru service, which relies on machine learning to automatically check code for bugs and suggest fixes, is now generally available. Amazon announced the tool in preview at its AWS re:Invent event in December. "It's challenging to have enough experienced developers with enough free time to do code reviews, given the amount of code that gets written every day," the company said today. "And even the most experienced reviewers miss problems before they impact customer-facing applications, resulting in bugs and performance issues." AWS CodeGuru is actually made up of two separate tools, including a Reviewer and a Profiler, and they do pretty much what the names suggest.

Amazon today announced the general availability of CodeGuru, an AI-powered developer tool that provides recommendations for improving code quality. It was first revealed during the company's Amazon Web Services (AWS) re:Invent 2019 conference in Las Vegas, and starting today, it's available with usage-based pricing. Software teams perform code reviews to check the logic, syntax, and style before new code is added to an existing application codebase -- it's an industry-standard practice. But it's often challenging finding enough developers to perform reviews and monitor the apps post-deployment. Plus, there's no guarantee those developers won't miss problems, resulting in bugs and performance issues.

Amazon CodeGuru is a recently launched chargeable machine learning service, currently still in preview mode. It was first announced in Andy Jassy's keynote at Amazon's AWS re:Invent 2019 conference that took place on December 2–6, 2019. The service is comprised of two parts: Amazon CodeGuru Reviewer executes automated code reviews and provides code issue detection, whereas Amazon CodeGuru Profiler searches for ways to improve the application's performance. Amazon CodeGuru was trained on internal Amazon projects as well as more than 10,000 open source GitHub projects. Amazon CodeGuru Reviewer is designed to find issues in code via automatic detection and provide recommendations on resolving them.

Amazon is leveraging machine learning to fight fraud, audit code, transcribe calls, and index enterprise data. Today during a keynote at its Amazon Web Services (AWS) re:Invent 2019 conference in Las Vegas, the tech giant debuted Amazon Fraud Detector, a fully managed service that detects anomalies in transactions, and CodeGuru, which automates code review while identifying the most "expensive" lines of code. And those are just the tip of the iceberg. With Fraud Detector (in preview), AWS customers provide email addresses, IP addressees, and other historical transaction and account registration data, along with markers indicating which transactions are fraudulent and which are legitimate. Amazon takes that information and uses algorithms -- along with data detectors developed on the consumer business of Amazon's business -- to build bespoke models that recognize things like potentially malicious email domains and IP address formation.

Amazon Web Services (AWS) has packaged up another in-house Amazon capability and made it available to customers, having announced Contact Lens for Amazon Connect on Tuesday. CEO Andy Jassy has touted that Contact Lens for Amazon Connect -- the company's omnichannel cloud contact centre service -- will stitch together new abstractions for machine learning so AWS customers can have an easy to consume function. "Amazon Connect is one of the fastest growing services in the history of AWS … off to a blazing start," he said during the day one keynote of AWS re:Invent in Las Vegas. "Using the same customer service technology Amazon has used … it's really easy to use." According to Jassy, Connect is the first call centre in the cloud with machine learning in mind.

It's like having a distinguished engineer on call, 24x7 Amazon CodeGuru is a machine learning service for automated code reviews and application performance recommendations. It helps you find the most expensive lines of code that hurt application performance and keep you up all night troubleshooting, then gives you specific recommendations to fix or improve your code. CodeGuru is powered by machine learning, best practices, and hard-learned lessons across millions of code reviews and thousands of applications profiled on open source projects and internally at Amazon. With CodeGuru, you can find and fix code issues such as resource leaks, potential concurrency race conditions, and wasted CPU cycles. And with low, on-demand pricing, it is inexpensive enough to use for every code review and application you run.