Machine Learning (ML) has been widely used in Natural Language Processing (NLP) applications. A fundamental assumption in ML is that training data and real-world data should follow a similar distribution. However, a deployed ML model may suffer from out-of-distribution (OOD) issues due to distribution shifts in the real-world data. Though many algorithms have been proposed to detect OOD data from text corpora, there is still a lack of interactive tool support for ML developers. In this work, we propose DeepLens, an interactive system that helps users detect and explore OOD issues in massive text corpora. Users can efficiently explore different OOD types in DeepLens with the help of a text clustering method. Users can also dig into a specific text by inspecting salient words highlighted through neuron activation analysis. In a within-subjects user study with 24 participants, participants using DeepLens were able to find nearly twice more types of OOD issues accurately with 22% more confidence compared with a variant of DeepLens that has no interaction or visualization support.

These days, companies are using cloud services to receive and process the data they gather from sensors, cameras, and services. However, the amount of data is getting so massive that sending them and managing them is becoming increasingly expansive. This is where Edge AI comes in, a combination of Edge Computing and Artificial Intelligence. Edge AI is a system of AI-equipped chips that are on board multiple devices. These devices can be installed and set up much closer to the sources of data. Although these chips process with less processing power and maybe slower action, they can provide invaluable services in terms of receiving and processing the data.

As companies welcome more autonomous robots and other heavy equipment into the workplace, we need to ensure equipment can operate safely around human teammates. In this post, we will show you how to build a virtual boundary with computer vision and AWS DeepLens, the AWS deep learning-enabled video camera designed for developers to learn machine learning (ML). Using the machine learning techniques in this post, you can build virtual boundaries for restricted areas that automatically shut down equipment or sound an alert when humans come close. For this project, you will train a custom object detection model with Amazon SageMaker and deploy the model to an AWS DeepLens device. Object detection is an ML algorithm that takes an image as input and identifies objects and their location within the image.

What do strange dogs pooping in your yard and the way some people are responding to Covid-19 have in common? Both are undesirable behaviors that can be hard to detect and correct – until now. Applying the phrase, "with conflict comes creativity," we got creative and designed and deployed an efficient and powerful ML/AI solution for detecting and correcting problems like these. One night I had walked down the hill in the dark to fetch our garbage cans. About 30 minutes later I began getting that familiar whiff.

These are just a few examples of how artificial intelligence (AI) at the edge, combined with connected devices, could improve quality of life and business and help solve problems facing consumers and businesses today. A convergence of several overlapping technology trends is making new usages like these possible. Edge computing – another name for applications, data, and services located at the edge of a network rather than in a centralized datacenter – is poised to grow by 35 percent annually and become a $34 billion industry by 2023. Meanwhile, the development of human-aware AI systems and the deployment of AI technologies beyond the datacenter are huge opportunities thanks to the available compute power in today's systems. The benefits of AI at the edge are well demonstrated in the Smart Home, where the technology can help people manage the day-to-day running of the home and provide peace of mind and.

With a solution to almost every machine learning problem, Amazon Machine Learning offers a rich set of tools for machine learning engineers to work with. Amazon also adds new services every few months based on new use cases, making it one of the most dependable platforms for engineers to build AI solutions for their customers. Hope you enjoyed the article. If you have any questions, let me know in the comments. You can also signup for my newsletter to receive a summary of articles once a week.

It comes with all of the sensors and software tools to help developers build machine learning models to drive the car around a course -- or really do anything else they want it to do. The $399 DeepRacer launched at AWS's massive re:Invent show in late 2018. At the time, it seemed like a bit of a gimmick, but AWS has put a lot of its weight behind it and is currently running a DeepRacer league at its various events around the world. At these events, developers can pit their models against each other and learn more about building a specific kind of machine learning model in the process. It's not like DeepRacer cars are likely to add to AWS's bottom line anytime soon.

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From time to time, usually on garbage night, the animals wander into Sivasubramanian's backyard to pillage his trash. But try as they might, he and his family had never managed to spot the intruders. "My wife really wanted to see these bears in action," says Sivasubramanian, Amazon's VP of machine learning. "She will always try to stay up looking for bears to visit, and she wants me to give her company." He founded his solution in DeepLens, a new video camera system from Amazon Web Services that lets anyone with programming skills employ deep learning to automate various tasks.

We are bringing you four challenges to choose from–sustainability, games, health and inclusivity. Now you can be inspired to create machine learning projects with AWS DeepLens and make a difference at the same time! Use these challenges to gain machine learning experience with fun, collaborative, and inspiring projects. In addition, you'll be making a positive impact on improving people's lives and supporting non-profit organizations that benefit our society. You are invited to enter a single challenge or as many of them as you want.