Google Assistant already knows how to slowly brighten a smart light to simulate the sunrise, as well as how to gradually dim your smart lights at bedtime. The catch, however, was that it was only able to perform the trick with Philips Hue smart lights, but that's changing starting today. Besides the Assistant's improved "Gentle Sleep and Wake" functionality, Google is also rolling out a new pre-made routine designed to ease the strain of your workday. We'll cover the new Workday routine in a moment. First, Google just announced that over the next few days, it will start rolling out an update that allows Google Assistant to slowly brighten or dim all smart lights, not just those from Philips Hue.

Amazon Prime Day, previously postponed due to the coronavirus pandemic, is now scheduled for Oct. 13-14, and Amazon just might compensate for the three month-long postponement with even better deals and lower prices. The new date was revealed in internal Amazon emails sent to employees, who were also told not to take any vacation leaves Oct. 13-20. One memo said the company will officially confirm Oct. 13-14 in an announcement on Sunday, according to The Verge. "Stay tuned for more details on Prime Day," said an Amazon spokesperson, who also said customers can ask Alexa devices to keep them updated about Prime Day. Prime Days have normally been held July 15, the anniversary Amazon's founding anniversary.

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One year ago, I was visiting with the CEO of a financial services company, and she was telling me about its implementation of digital employees. "They do rote tasks, and they work on projects," she said. "In fact, we even assign them employee numbers!" I was aware of digitalizing routine, repetitive tasks for digital agents to perform, and of the work that was being done with robotic process automation (RPA)--but was surprised at the idea of a digital assistant that was a full-time employee in an organization. Now one year later, digital assistants are being taught to behave in even more human-like fashion so they can assume more responsibilities.

Contextual bandits provide an effective way to model the dynamic data problem in ML by leveraging online (incremental) learning to continuously adjust the predictions based on changing environment. We explore details on contextual bandits, an extension to the traditional reinforcement learning (RL) problem and build a novel algorithm to solve this problem using an array of action-based learners. We apply this approach to model an article recommendation system using an array of stochastic gradient descent (SGD) learners to make predictions on rewards based on actions taken. We then extend the approach to a publicly available MovieLens dataset and explore the findings. First, we make available a simplified simulated dataset showing varying user preferences over time and how this can be evaluated with static and dynamic learning algorithms. This dataset made available as part of this research is intentionally simulated with limited number of features and can be used to evaluate different problem-solving strategies. We will build a classifier using static dataset and evaluate its performance on this dataset. We show limitations of static learner due to fixed context at a point of time and how changing that context brings down the accuracy. Next we develop a novel algorithm for solving the contextual bandit problem. Similar to the linear bandits, this algorithm maps the reward as a function of context vector but uses an array of learners to capture variation between actions/arms. We develop a bandit algorithm using an array of stochastic gradient descent (SGD) learners, with separate learner per arm. Finally, we will apply this contextual bandit algorithm to predicting movie ratings over time by different users from the standard Movie Lens dataset and demonstrate the results.

Increasing users' positive interactions, such as purchases or clicks, is an important objective of recommender systems. Recommenders typically aim to select items that users will interact with. If the recommended items are purchased, an increase in sales is expected. However, the items could have been purchased even without recommendation. Thus, we want to recommend items that results in purchases caused by recommendation. This can be formulated as a ranking problem in terms of the causal effect. Despite its importance, this problem has not been well explored in the related research. It is challenging because the ground truth of causal effect is unobservable, and estimating the causal effect is prone to the bias arising from currently deployed recommenders. This paper proposes an unbiased learning framework for the causal effect of recommendation. Based on the inverse propensity scoring technique, the proposed framework first constructs unbiased estimators for ranking metrics. Then, it conducts empirical risk minimization on the estimators with propensity capping, which reduces variance under finite training samples. Based on the framework, we develop an unbiased learning method for the causal effect extension of a ranking metric. We theoretically analyze the unbiasedness of the proposed method and empirically demonstrate that the proposed method outperforms other biased learning methods in various settings.

Microsoft's Cortana-powered consumer speakers are dead. Long live...Cortana powered Teams speakers? During a Microsoft Ignite keynote by Jared Spataro, the vice president of Microsoft 365, Microsoft showed off a demonstration room powered by some of its latest hardware, including the 85-inch Surface Hub 2S, plus companion devices like Teams Rooms, which are third-party bundles of cameras and small displays for facilitating meetings. Microsoft's idea is that the Teams Rooms devices will manage the meetings, with voice assistance using Cortana, and capabilities like Teams casting and the Room remote app for facilitating conferences. One of the key capabilities of the Microsoft Teams software is its ability to listen to, record, and transcribe the conversation.

You can now use Google Assistant voice controls to navigate Disney content on smart displays like Nest Hub and Nest Hub Max. To use the feature, you'll have to link your Disney subscription to your Google Home or Assistant app. Then, just say something like "Hey Google, play The Mandalorian," to stream content. From the start, Disney has been available on Google Assistant smart displays like Nest Hub. You can already use Assistant to play Netflix, Hulu, CBS All Access and HBO content, so it only makes sense that the same feature would be available for Disney .

Two intriguing functions in Microsoft Outlook, Play My Emails and the Daily Briefing, are scheduled to receive updates that add new Cortana-powered AI to functions that go far beyond just email. Microsoft's AI assistant, Cortana, has moved from being an integral part of Windows to more of an assistive technology. Outlook has been the main beneficiary, however, new Cortana-powered intelligence is coming to Teams, and to the Cortana app within Windows 10 as well. One of the problems with Microsoft's parade of new features is simply keeping track of the timeline. The Daily Briefing functionality debuted in preview mode a year ago, but at the Microsoft Ignite conference it's now becoming officially available for Microsoft 365 users with Exchange Online mailboxes.

Please don't complain to me about literally anything if you've touched human flesh since March. Being very single, I have not, and my Grubhub guy doesn't want a hug. So I am doomed, instead, to online dating in the context of a pandemic. Let me walk you through the torture. It starts typically enough, with endless scrolling through profiles of now-offensively-irrelevant travel photos.