Amazon is having an internal crisis over Alexa right now--its voice assistant is on pace to lose $10 billion this year--so it might not be the best idea to invest in the company's lineup of Alexa-powered devices right now. However, Amazon makes a ton of other hardware, from Kindles, which are some of the best ebook readers in the market, to Fire tablets and Fire TV sticks. Everything is heavily discounted right now for Cyber Monday, so now's one of the best times to buy. We test products year-round and handpicked these deals. Products that are sold out or no longer discounted as of publishing will be crossed out . We'll update this guide through Cyber Monday.

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Artificial intelligence (AI)--the use of algorithms and software to interpret and understand complex data--has proven to be a disruptive force in modern medicine and has impacted everything from biomedical research to clinical practice. The rapid development of AI tech has seen its incorporation into increasingly specific applications and clinical settings. In particular, the field of cardiology has seen AI integrated with a variety of tools and devices in recent years and presents new opportunities for data-driven improvements to patient care. Today's AI applications in cardiology aim to enhance physician decision-making through data analysis. Interpretation of test results such as electrocardiograms or angiograms can be guided by AI algorithms trained to detect abnormalities and reduce diagnosis time.

An approach called federated learning trains machine learning models on devices like smartphones and laptops, rather than requiring the transfer of private data to central servers. The biggest benchmarking data set to date for a machine learning technique designed with data privacy in mind is now available open source. "By training in-situ on data where it is generated, we can train on larger real-world data," explains Fan Lai, a doctoral student in computer science and engineering at the University of Michigan, who presents the FedScale training environment at the International Conference on Machine Learning this week. A paper on the work is available on ArXiv. "This also allows us to mitigate privacy risks and high communication and storage costs associated with collecting the raw data from end-user devices into the cloud," Lai says.

Researchers in the US have developed a perovskite-based device that could be used to create a high-plasticity architecture for artificial intelligence. The team, led by Shriram Ramanathan at Purdue University, has showed that the material's electronic properties can be easily reconfigured, allowing the devices to function like artificial neurons and other components. Their results could lead to more flexible artificial-intelligence hardware that could learn much like how the brain does. Artificial intelligence systems can be trained to perform a task such as voice recognition using real-world data. Today this is usually done in software, which can adapt when additional training data are provided.

The last time I saw my friend James was at the townie bar near our old high school. He had been working in roofing for a few years, no longer a rail-thin teenager with lank hippie hair. I had just gotten back from a stint with the Peace Corps in Turkmenistan. We reminisced about the summer after our freshman year, when we were inseparable--adventuring in the creek that sliced through the woods, debating the merits of Batman versus the Crow, watching every movie in my father's bootlegged VHS collection. I had no idea what I wanted to do next.

At dinner, I mentioned that I would like to go hiking in Patagonia. I never searched for these trips or anything like it. Yet, an hour later, I started getting ads on my phone about hiking adventures in Patagonia. While there's been no concrete evidence that your device's microphone is always listening, many Americans believe apps and sites routinely collect their voice data and use it for marketing purposes. Your smart speaker with its virtual assistant is always listening.

Facebook is testing a new feature for Messenger that allows users to better protect their messages from prying eyes. When enabled, users will need to authenticate their identity using Face ID, Touch ID, or their passcode before they can view their inbox, even if their phone is already unlocked. You can also set a designated period of time after leaving the app for when you'll need to re-authenticate. The company is currently testing the new security feature among a small percentage of Messenger's iOS users, though it could eventually be available more widely, including on Android. "We want to give people more choices and controls to protect their private messages, and recently, we began testing a feature that lets you unlock the Messenger app using your device's settings," a Facebook spokesperson said in a statement.

A study at Canada's University of Alberta found some virtual assistants are far better than others at providing users reliable, relevant information on medical emergencies. Researchers at the University of Alberta in Canada have found that virtual assistants do not live up to their potential in terms of providing users with reliable, relevant information on medical emergencies. The team tested four commonly used devices--Alexa, Google Home, Siri, and Cortana--using 123 questions about 39 first aid topics, including heart attacks, poisoning, nosebleeds, and splinters. The devices' responses were measured for accuracy of topic recognition, detection of the severity of the emergency, complexity of language used, and how closely the advice given fit with accepted first aid treatment and guidelines. Google Home performed the best, recognizing topics with 98% accuracy and providing relevant advice 56% of the time.

As Python 2.7 will reach end of life on January 1, 2020, TensorFlow 2.1 will be the last version to support it. TensorFlow is an open source software library for ML that was originally developed by the Google Brain team in 2015. It has since become very popular within the open source community and was found to be the 5th most popular open source project on GitHub in the latest State of the Octoverse report. Among the breaking changes are API renamings as well as removals, and six APIs are now stable. The tensorflow pip package has received an update: GPU support is now included by default for Linux and Windows on machines with and without NVIDIA GPUs.