Being one of the recurring themes of science fiction, we all have at least a vague idea of what Artificial Intelligence (AI) is. In countless novels and movies, often in the guise of an ominous and threatening machine, other times instead portrayed as a technology so futuristic as to seem almost unattainable, AI has risen to the role of a mysterious entity that mostly belongs to fiction. At least, this was the scenario a few years ago. More recently, in fact, we all came to know AI by witnessing its expansion and pervasiveness to a point where it constitutes a substantial part of our daily interactions, either via smart assistants (e.g., Amazon's Alexa or Apple's Siri, just to name a few), or even by the AI-powered features of our smartphones (e.g., facial and fingerprint screen unlocking, or photo enrichment), not to mention self-driving cars. However, despite being already deployed in millions of products and services around the world, AI is still something obscure.

A TikTok video showing a woman's shock at how much voice data Amazon has collected on her has received millions of views and been liked hundreds of thousands of times. "I requested all the data Amazon has on me and here's what I found", she said in a video. The woman has two Amazon Echo Dot speakers and another Echo device to control her smart home lightbulbs. "When I downloaded the ZIP file these are all the folders it came with," she said. The audio files reveal thousands of short voice clips, which she describes as "so scary".

It seems that the world is gradually turning everything into data, and we are storing data at lightspeed. How are banks capitalising on new sources of data and using it to develop new services? Our watches now track our sleep, our movement, our heart rate and much more. With it they can "coach" us with training plans that are specific to our individual capabilities. At the top end of smartwatches, you have the ability to pay for things, listen to music, get guided GPS navigation and more.

Artificial agents that support people in their daily activities (e.g., virtual coaches and personal assistants) are increasingly prevalent. Since many daily activities are social in nature, support agents should understand a user's social situation to offer comprehensive support. However, there are no systematic approaches for developing support agents that are social situation aware. We identify key requirements for a support agent to be social situation aware and propose steps to realize those requirements. These steps are presented through a conceptual architecture that centers around two key ideas: (1) conceptualizing social situation awareness as an instantiation of `general' situation awareness, and (2) using situation taxonomies as the key element of such instantiation. This enables support agents to represent a user's social situation, comprehend its meaning, and assess its impact on the user's behavior. We discuss empirical results supporting that the proposed approach can be effective and illustrate how the architecture can be used in support agents through a use case.

In addition to the new Pixel 6 and Pixel 6 Pro, Google also released more details about new capabilities that its Tensor chip enables. One of them is a much more intelligent way of handling those calls to businesses that sometimes have you waiting hours on end just to speak to a representative. Now, the Pixel will show you the current and projected wait times before you even place a call so you can call when it works for you. Additionally, when you do call and encounter an endless list of options (like, "Press 1 for branch location and hours" if you're calling a bank), you don't need to remember all of them carefully. Instead, Google will listen to them for you and show the automated menu options on the screen for you to tap.

Setting up the Nest Cam is quick and easy in the Google Home app. Setting up the camera took me about five minutes. Plug it into a power outlet, open the Google Home app, and follow the in-app instructions. Drywall anchors, screws, and a base with a built-in mounting bracket are also included in the box. The Google Home app is where you can view and manage notifications, as well as toggle video recordings settings.

You might think that artificial intelligence is only something the tech giants are focused on and that it doesn't have any impact on your household or everyday life. But the reality is different. Whether you realize it or not, Artificial Intelligence is everywhere. The application of AI is not only for big sectors or finance or manufacturing, it is also impacting our daily lives. So, let's find out about the applications of AI in your daily life.

Artificial intelligence (AI) is transforming the landscape of 21st century marketing. Long gone are the days of throwing spaghetti on the wall and shooting in the dark to acquire new customers and to regain their business. With the amount of data growing exponentially on a daily basis, AI can help businesses scale their marketing efforts and leverage the data for actionable insights leading to greater ROI. Look up the term "marketing" and you'll find something that mentions actions or activities involving a business or company, promoting or selling products or services. Is that something that you or your company does?

Vida Health, a virtual chronic care platform, announced that it is rolling out a new value-based price structure, which puts Vida's fees at-risk for behavioral and physical health. This news comes just months after the company landed $110 million in Series funding. The service includes a number of health conditions, including obesity, diabetes, hypertension, depression and anxiety.

In a content-based approach to recommendation, a lot of information is available for both items and users which is useful to create profiles. We used a graph model to represent these profiles, connecting each item to its features and each user to features of interest. Even the nearest neighbor network was built using only this information. The collaborative filtering approach, on the other hand, relies on data related to the different kinds of interactions between users and items. Such information is generally referred to as a user–item dataset.