Cortana may not be the personal assistant she once was, but a new update as part of the Windows Insider Dev Channel means that her capabilities to find files have improved. The new "File Skill" in the Cortana app appears in the new Windows 10 Insider Preview Build 20270, part of the Dev Channel. In this experimental app, Cortana's skills have been honed to the point where she can find files in the cloud, with a better understanding of what you're looking for. If your PC is enrolled in the Windows 10 May 2020 Update or later, some of these capabilities will already be available. As long as you have speech recognition enabled on your PC, you can ask Cortana "find my recent files," and it should unearth the last two or three files you've used on your PC.

Poor customer experiences are the primary cause for low conversion rates, lost leads and customer churn. In fact, a customer who suffered a third-rate experience will tell five times as many people about what happened than if they had a great experience. These bad impressions tend to stick with people and influence their future decisions for months or even years later. As a result, frustrated Sales Managers and Marketers often blame these sour interactions on substandard or poorly deployed software. Similarly, many marketers prefer today to keep things as hands-on as possible.

Gift giving has become a bit onerous. In the past, a recipient could keep a present or return it, but the gifts didn't raise significant questions or concerns. Even electronic gifts like a DVD player or remote-controlled car were inconsequential. Giving tech-focused products now requires a different mindset going in. A $20 or $30 Amazon Echo Dot might be the right price and readily available with free two-day shipping, but it raises some legitimate privacy concerns that you, as the giver, should be able to answer for.

In this article, we will have a detailed listing at AI Services supported and provided by Microsoft. Artificial Intelligence is a branch of computer science that aims to create intelligent machines, in simple terms, Human Intelligence processed by Machines, specifically computers. AI can be categorized as either weak and strong. Weak AI is AI systems which are specifically designed and trained for a particular task. A good example is personal assistants, such as Apple's Siri, Google Assistance, Microsoft Cortana, Amazon's Alexa are a form of Weak AI.

Due to researchers'aim to study personalized recommendations for different business fields, the summary of recommendation methods in specific fields is of practical significance. News recommendation systems were the earliest research field regarding recommendation systems, and were also the earliest recommendation field to apply the collaborative filtering method. In addition, news is real-time and rich in content, which makes news recommendation methods more challenging than in other fields. Thus, this paper summarizes the research progress regarding news recommendation methods. From 2018 to 2020, developed news recommendation methods were mainly deep learning-based, attention-based, and knowledge graphs-based. As of 2020, there are many news recommendation methods that combine attention mechanisms and knowledge graphs. However, these methods were all developed based on basic methods (the collaborative filtering method, the content-based recommendation method, and a mixed recommendation method combining the two). In order to allow researchers to have a detailed understanding of the development process of news recommendation methods, the news recommendation methods surveyed in this paper, which cover nearly 10 years, are divided into three categories according to the abovementioned basic methods. Firstly, the paper introduces the basic ideas of each category of methods and then summarizes the recommendation methods that are combined with other methods based on each category of methods and according to the time sequence of research results. Finally, this paper also summarizes the challenges confronting news recommendation systems.

Next destination recommendation is an important task in the transportation domain of taxi and ride-hailing services, where users are recommended with personalized destinations given their current origin location. However, recent recommendation works do not satisfy this origin-awareness property, and only consider learning from historical destination locations, without origin information. Thus, the resulting approaches are unable to learn and predict origin-aware recommendations based on the user's current location, leading to sub-optimal performance and poor real-world practicality. Hence, in this work, we study the origin-aware next destination recommendation task. We propose the Spatial-Temporal Origin-Destination Personalized Preference Attention (STOD-PPA) encoder-decoder model to learn origin-origin (OO), destination-destination (DD), and origin-destination (OD) relationships by first encoding both origin and destination sequences with spatial and temporal factors in local and global views, then decoding them through personalized preference attention to predict the next destination. Experimental results on seven real-world user trajectory taxi datasets show that our model significantly outperforms baseline and state-of-the-art methods.

Power systems are becoming more complex to operate in the digital age. As a result, real-time decision-making is getting more challenging as the human operator has to deal with more information, more uncertainty, more applications and more coordination. While supervision has been primarily used to help them make decisions over the last decades, it cannot reasonably scale up anymore. There is a great need for rethinking the human-machine interface under more unified and interactive frameworks. Taking advantage of the latest developments in Human-machine Interactions and Artificial intelligence, we share the vision of a new assistant framework relying on an hypervision interface and greater bidirectional interactions. We review the known principles of decision-making that drives the assistant design and supporting assistance functions we present. We finally share some guidelines to make progress towards the development of such an assistant.

Success in creating effective AI, could be the biggest event in the history of our civilisation. So we cannot know if we will be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it. Artificial Intelligence (AI) is the term to describe a machine's learning, logic, reasoning, perception and creativity which were once considered unique to humans but now replicated by technology and use in every industry. Artificial Intelligence is the use of computer science programming to imitate human thought and action by analysing data and surroundings, solving or anticipating problems, learning of self-teaching or adapting to a variety of tasks. AI can relieve humans of various repetitive tasks.

Microsoft has revealed a number of features it's bringing to Teams calls. It will soon offer CarPlay support, so you can place and answer Teams calls using Siri while you're on the road. Microsoft didn't say whether it would add a similar function for Android Auto or Alexa-enabled cars. Elsewhere, Microsoft has overhauled the call interface with a streamlined design (which it unveiled at its Ignite conference) that pulls together your contacts, voicemail and call history into a single view. Other features include an option to merge calls, enhanced reverse number lookup (i.e.

There was a time when we heard terms like Artificial Intelligence and Machine Learning only in sci-fi movies. But today, technological advances have brought us to a point where businesses across verticals are not only talking about, but also implementing artificial intelligence and machine learning in everyday scenarios. AI is everywhere, from gaming stations to maintaining complex information at work. Computer Engineers and Scientists are working hard to impart intelligent behavior in the machines making them think and respond to real-time situations. AI has evolved from being a research topic to being at the early stages of enterprise adoption.