Amazon Lookout spots Defects and Anomalies in Visuals

Had not heard of this particular AWS service, could have been useful on our industrial manufacturing and supply chain areas.  Just as we use our vision to scan for anomalies in representations of systems or data. 

Amazon’s Lookout for Vision spots defects and anomalies in visual representations  By Duncan Riley in SiliconAngle

Amazon Web Services Inc. today announced the general availability of Amazon Lookout for Vision, a cloud service that uses machine learning to spot defects and anomalies in visual representation using computer vision.

Designed with manufacturing companies in mind, the service can identify differences in images of objects at large scale, delivering the ability to identify manufacturing and production defects such as cracks, dents, incorrect colors and irregular shapes. The technology uses a technique called “few-shot learning” so it can train a model for a customer using as few as 30 baseline images.

Amazon Lookout for Vision can process thousands of images an hour to spot defects and anomalies with no machine learning experience required. Customers send camera images to Amazon Lookout for Vision in real-time to identify anomalies, such as damage to a product’s surface, missing components and other irregularities in production lines. In addition to enabling the service to detect anomalies without large amounts of training data, this capability allows the service to adapt to a wide range of inspection tasks within industrial settings.

Upon analyzing data, Amazon Lookout for Vision reports images that differ from the baseline via the service dashboard or the “DetectAnomalies” real-time application programing interface so that appropriate action can be taken.  ...  ' 

Three Ways Visual AI Can Optimize Supply Chain

Visual interaction with data can strongly drive decisions, before and after.   Again had not heard it called that specifically,  But see the point  You can enhance intelligence by providing useful and efficient visualization.  Marketing since we pasted fancy labels on things has done that. 

Three Ways Visual AI Can Optimize Retail Supply Chains

January 14, 2021  Idan Pinto, SCB Contributor

Imagine you just bought a new robotic vacuum cleaner. After doing your research and purchasing the best available option, you can’t wait to bring your new gadget home and get effortlessly clean floors. To your amazement, it not only vacuums your floors, but it also does the laundry, washes your dishes and takes out the trash.

While the perfect house-cleaning robot may still be a few years into the future, the idea of a single piece of technology that can unlock a range of benefits is something we’re already seeing with visual AI and its applications for e-commerce and retail. 

As visual AI becomes more advanced, its value is often measured within the context of the sales and revenue it helps generate. Indeed, visual AI tools such as visual search have unlocked a host of sales-related advantages for e-commerce sites, including more accurate on-site search results, higher purchase volumes and greater average order value (AOV). But there’s another, often untapped asset of visual AI: data. Lots and lots of data. 

This data is your key to operational efficiency. Within it lives a wealth of information about your shoppers, which you can use to optimize your supply chain and transform your operations by boosting efficiency, better predicting customer trends, increasing sales and eliminating waste.

More than ever before — as supply chains face disruptions, unexpected shifts in demand and a new urgency to improve sustainability — visual AI has proven to be a wellspring of data that enables supply-chain optimization and the far-reaching business benefits that come with it. Let’s examine three key advantages.   ... "