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.

Today, we're extremely happy to launch Amazon SageMaker Studio, the first fully integrated development environment (IDE) for machine learning (ML). We have come a long way since we launched Amazon SageMaker in 2017, and it is shown in the growing number of customers using the service. However, the ML development workflow is still very iterative, and is challenging for developers to manage due to the relative immaturity of ML tooling. Many of the tools which developers take for granted when building traditional software (debuggers, project management, collaboration, monitoring, and so forth) have yet been invented for ML. For example, when trying a new algorithm or tweaking hyper parameters, developers and data scientists typically run hundreds and thousands of experiments on Amazon SageMaker, and they need to manage all this manually.

Walmart (NYSE:WMT) has gone out of its way to promote its new in-store robots as tools that will free up its employees to do more tasks that involve interacting with customers, rather than as machines that will simply be taking people's jobs. It's a valid spin, to a point, but as the chain automates more functions, one has to wonder how long it will be before it decides it doesn't need quite so many people after all. For now, though, that's a question the retailer wants to sidestep; the most recent press release on the subject was focused on how useful robots can be to its employees. "Every hero needs a sidekick, and some of the best have been automated. Think R2D2, Optimus Prime, and Robot from Lost in Space. Just like Will Robinson and Luke Skywalker, having the right kind of support helps our associates succeed at their jobs," wrote Elizabeth Walker from Walmart Corporate Affairs.

According to a Global Market Insight study, the retail sector will increase its investment in AI to $8 billion by 2024. Since adoption of machine learning, deep learning and predictive analytics is required to succeed within the technological hemisphere in retail – which is growing at a rapid pace – it is absolutely necessary for retailers to adjust within the digital disruption. But the question is how and in which areas does AI help improve? As per AI experts on a global scale, this technology has so much to offer to any retail segment. GM Insights concluded that by 2020, a greater infusion of AI-based applications will be seen across the retail industry in everyday operations.

Silicon Valley is abuzz with Internet of Things (IoT), virtual reality (VR)/augmented reality (AR) and blockchain vendors seeking the Holy Grail of Retail: mass consumer markets where their technology can help fashion designers and retailers survive the "retail apocalypse." At the recent San Francisco Tech Fashion Week, retail experts provided invaluable insights that could save millions of designers, major retailers and small shops from bankruptcy. Here are key insights from three panels. In 2014, Macy's learned that "omnichannel marketing is the way to go." Instead of targeting customers with one channel, whether online or in-store, retailers must pursue multiple channels. For example, small retailers can also sell on Amazon to leverage its free shipping, which is a major competitive advantage.

Millennials are projected to soon overtake baby boomers as the largest adult population group, bringing demands for sustainability to the front of every grocery checkout aisle. Fresh retailers, or retailers in the business of providing highly perishable foods like fresh produce and meat to consumers, can strengthen sustainability efforts and combat the 1.3bn tonnes of food wasted annually with the support of artificial intelligence (AI) and machine learning (ML) solutions. AI and ML not only help fresh retailers reduce their environmental footprint through waste reduction, but the technologies allow them to respond to market conditions in real-time and offer more personalised assortments in line with the core values of their key consumers, resulting in more efficient and eco-friendly supply chains. So what does this look like in practice? Food waste is a worldwide issue.

Artificial intelligence can help businesses make more money from online shopping, Carrie Tharp, Google Cloud's head of retail, told CNBC on Monday. "We're helping retailers with Google A.I. to help drive their ability to do promotions, recommendations, improve their margins with dynamic pricing," Tharp said on "Squawk Alley." "So it's really helping that retail C-suite deliver on all of their financial goals." While it's not clear if Google is providing all these services to businesses whose websites are hosted on its cloud, Tharp said some of its partners include Home Depot and Kohl's. Tharp's comments on the retail landscape come on Cyber Monday, the annual e-commerce bonanza that is on pace to generate more than $9 billion in sales, according to Adobe Analytics.

Generative AI is one of the biggest recent advancements in artificial intelligence technology because of its ability to create something new. It opens the door to an entire world of possibilities for human and computer creativity, with practical applications emerging across industries, from turning sketches into images for accelerated product development, to improving computer-aided design of complex objects. Until now, developers interested in growing skills in this area haven't had an easy way to get started. Developers, regardless of their background in ML or music, can get started with Generative Adversarial Networks (GANs). This Generative AI technique pits two different neural networks against each other to produce new and original digital works based on sample inputs. With AWS DeepComposer, you can train and optimize GAN models to create original music.

I first wrote about AWS DeepRacer at this time last year, and described it as an opportunity for you to get some hands-on experience with Reinforcement Learning (RL). Along with the rest of the AWS team, I believe that you should always be improving your existing skills and building new ones. We launched the AWS DeepRacer car and the AWS DeepRacer League so that you could have the opportunity to get experience and new skills in a fun, competitive environment. In less than a year, tens of thousands of developers have participated in hands-on and virtual races located all over the world. Their enthusiasm and energy have been inspiring, as has been the creativity.

To stay ahead of the game and meet customer's needs, banks cannot afford to pay for costly and largely underused branches. Instead, the focus needs to shift to improving their online offerings. This past Friday was arguably the biggest day of the year for retailers, particularly online retailers. Throughout last week, you probably received emails about massive Black Friday discounts. Some of you might have put together wish lists to check out at the stroke of midnight while others used your phones, to scout whether a 30% discount was worth the still hefty price tags.