If you want a USB microphone for more than just streaming, Best Buy is the place to be today. The online retailer is selling the Blue Yeti X World of Warcraft edition for $95. That's about $45 cheaper than you'll play elsewhere. We took a look at Yeti X as part of our round-up of the best USB microphones for streaming. We deemed it an ideal mic for multi-purpose set-ups beyond just streaming. In terms of audio performance, we found that it was similar to the Elgato Wave:3, which was our top pick for the best USB microphones.

AWS BugBust is the first global bug-busting challenge for developers to eliminate 1 million software bugs and save $100 million in technical debt for their organizations. AWS BugBust allows you to create and manage private events that transform and gamify the process of finding and fixing bugs in your software. With automated code analysis, built-in leaderboards, custom challenges, and rewards, AWS BugBust helps foster team building and introduces some friendly competition into improving code quality and application performance. AWS BugBust utilizes the machine learning (ML)-powered developer tools in Amazon CodeGuru--CodeGuru Reviewer and CodeGuru Profiler--to automatically scan your code to weed out gnarly bugs, and gamifies fixing and eliminating them. Since launch in June 2021, thousands of Java and Python developers have participated in AWS BugBust events hosted internally by their organizations.

Today, we're pleased to announce Amazon SageMaker Inference Recommender -- a brand-new Amazon SageMaker Studio capability that automates load testing and optimizes model performance across machine learning (ML) instances. Ultimately, it reduces the time it takes to get ML models from development to production and optimizes the costs associated with their operation. Until now, no service has provided MLOps Engineers with a means to pick the optimal ML instances for their model. To optimize costs and maximize instance utilization, MLOps engineers would have to use their experience and intuition to select an ML instance type that would serve them and their model well, given the requirements to run them. Moreover, given the vast array of ML instances available, and the practically infinite nuances of each model, choosing the right instance type could take more than a few attempts to get it right.

For weeks, Jay Deitcher has been on the hunt for a specific Miles Morales: Spider-Man toy from Spidey and His Amazing Friends. "The thing that makes the toy special is Miles's mask flips up to show his face," Deitcher says. "My son is Black, and it would be great to have a Spider-Man figure that looks like him." But even though the father of two from Albany, New York, started shopping for Hanukkah earlier than usual, he has yet to track down the elusive toy, which is sold out at many retailers. "We were already expecting a shortage, so we got him most of his other presents," he says.

Creating efficiencies in your business is at the top of your list. You want your employees to be more productive, have them focus on high impact tasks, or find ways to implement better processes to improve the outcomes to your customers. There are various ways to solve this problem, and more companies are turning to artificial intelligence (AI) and machine learning (ML) to help. In the financial services sector, there is the creation of new accounts online, or in healthcare there are new digital platforms to schedule and manage appointments, which require users to fill out forms. These can be error prone, time consuming, and certainly improved upon.

Cresta Intelligence, a California-based AI startup, makes businesses radically more productive by using Expertise AI to help sales and service teams unlock their full potential. Cresta is bringing together world-renowned AI thought-leaders, engineers, and investors to create a real-time coaching and management solution that transforms sales and increases service productivity, weeks after application deployment. Cresta enables customers such as Intuit, Cox Communications, and Porsche to realize a 20% improvement in sales conversion rate, 25% greater average order value, and millions of dollars in additional annual revenue. This post discusses Cresta's journey as they moved from a multi-cloud environment to consolidating their machine learning (ML) workloads on AWS. It also gives a high-level view of their legacy and current training and inference architectures.

Today, we're pleased to announce Amazon SageMaker Training Compiler, a new Amazon SageMaker capability that can accelerate the training of deep learning (DL) models by up to 50%. As DL models grow in complexity, so too does the time it can take to optimize and train them. For example, it can take 25,000 GPU-hours to train popular natural language processing (NLP) model "RoBERTa". Although there are techniques and optimizations that customers can apply to reduce the time it can take to train a model, these also take time to implement and require a rare skillset. This can impede innovation and progress in the wider adoption of artificial intelligence (AI).

Residents can place orders through the 7Now app and an AV might bring the items to their location. They're available from 8AM until 9PM PT every day, and the companies say orders should arrive in around 30 minutes. When the AV arrives, customers collect their items from the rear. You won't be able to order age-restricted items -- such as alcohol, tobacco or lottery tickets -- for autonomous delivery. Nuro will initially use self-driving Priuses with a human operator monitoring the tech from the driver seat.

Amazon CloudWatch has recently launched Metrics Insights – a fast, flexible, SQL-based query engine that lets customers identify trends and patterns across millions of operational metrics in real time. Metrics Insights allows customers to easily query and analyze metrics to gain better visibility into the health and performance of their infrastructure and large-scale applications. Nobl9 and Amazon Web Services (AWS) have collaborated to extend the existing Nobl9 CloudWatch integration with CloudWatch Metrics Insights (Preview). This will help users to retrieve metrics even faster and gain added flexibility in querying raw service level indicator (SLI) data to use for your SLOs. Nobl9 launched the first version of its CloudWatch integration in September 2021, giving customers a versatile tool to monitor their products.

The outbreaks of the coronavirus pandemic and digital transformation have created ample opportunities for the retail and e-Commerce industry across the world. The ever-changing industry is allowing retailers, merchants, business people, and many more to enhance e-Commerce businesses to meet customer satisfaction by leveraging advanced AI innovations and technologies. Multiple retail and e-Commerce companies are harnessing smart functionalities of artificial intelligence with a diverse range of products and services including smart payments, seamless transactions, fast delivery, and many more through online mode. Virtual Trial Rooms: Virtual trial rooms are emerging as one of the top AI innovations in the retail and e-Commerce industry that digitally manage customer tastes and preferences of apparel. It is developed with the integration of artificial intelligence and augmented reality to increase customer engagement in this industry.