Purchases you make through our links may earn us a commission. I don't know about you, but I've never gotten a techy or tech-adjacent gift I wasn't excited about--it's true. Opening up a gift and getting a new pair of headphones or a fun gadget I wasn't expecting is almost always fun, even if it isn't something I thought I wanted. That's the problem with trying to buy a fun new tech gift for a giftee: How do you single out the small margin of great products from the ocean of sub-par stuff? Easy--you check out our picks below. Reviewed tests tech all year long and this list is chock full of our favorite gadgets. Roku's fancy "Ultra" media streaming device has been our favorite for a couple years running now, and for good reason. Processing is snappy and the UI is extremely friendly and intuitive, making it easy to settle in for a night of Netflix (or Hulu, or Amazon Prime, or YouTube, or Twitch, or anything else) without a hitch.

Locked down singles in Britain looking for love on Tinder, one of the world's most popular dating apps, can now video chat with their matches. Tinder had announced it is rolling out its'Face to Face' feature to its global customer base today. To prevent creeps and weirdos exploiting the feature to berate or harass their matches, video calling only becomes available when both parties opt in. It is designed to be used to compliment and boost conversation once a spark has been established. Tinder had announced it is rolling out its'Face to Face' feature today to its users around the world.

When most people think of Artificial Intelligence (AI) they probably think about their Amazon's Alexa, self-driving cars or Apple's Siri. However, AI can help be used for many other functions, including marketing and construction. Home builders and developers can incorporate AI in their marketing and construction efforts to impact growth in business and employee retention. The benefits of AI include improving efficiency in the workplace, solving complex problems, and even freeing up your time. Many businesses use AI-related machines or bots and other technologies today so they can use their time more wisely.

Artificial Intelligence (AI) has been improving the performance of systems for a diverse set of tasks and introduced a more interactive generation of personal agents. Despite the current trend of applying AI for a great amount of areas, we have not seen the same quantity of work being developed for the tourism sector. This paper reports on the main applications of AI systems developed for tourism and the current state of the art for this sector. The paper also provides an up-to-date survey of this field regarding several key works and systems that are applied to tourism, like Personal Agents, for providing a more interactive experience. We also carried out an in-depth research on systems for predicting traffic human flow, more accurate recommendation systems and even how geospatial is trying to display tourism data in a more informative way and prevent problems before they arise.

Spotify is the largest on-demand music services in the world and has 299 million monthly users, including 138 million paying subscribers. One of the exciting features of the Spotify is Discover Weekly. It's a custom mixtape of 30 songs they've never listened to before but will probably love, and it's pretty much magic. Songza used to curate playlists manually in the early 2000s which was not able to fulfil the music needs of the consumers as it was developed as on specific interest of the curator. Pandora used tagging the songs manually with attributes like'folk', 'rock' and curating playlist with similar tags using the code. Collaborative filtering: It works by comparing people with similar tastes.

The primary appeal of motorized top-down/bottom-up shades is their ability to open and close in two directions: They can open by dropping the top of the shade down from the window's head to the sill, and by lifting the bottom of the shade up from the sill to the head. But Hunter Douglas couldn't justify the lofty price tag of its Duette with PowerView Automation shades unless they were also the most luxurious and innovative shades we've reviewed to date. Top-down/bottom-up shades are a fantastic option because they enhance privacy without completely blocking light from entering the room. If your window faces a busy street, you can lower the shade down from the top to admit light without exposing your room to a view from the street. Or you can drop the top of the shade down in the early morning, so the room is bathed in morning sunlight without impeding your ability to move about the room freely--anyone looking toward your window will only be able to as much of you as you wish to expose. And since these are motorized smart shades, you can create automated schedules to reposition the shades as many times each day and night that you'd care to program, including at sunrise and sunset.

Planning to invest in a mobile app? Here are the top 15 AI/ML/VR/AR app development ideas that ensure your success in 2020–21! With the availability of around 5 million apps existing in the app stores, the trends of developing ordinary mobile apps are just fading away. The increasing usage of mobile applications with each passing year also pushes the demand for innovative technologies to meet future mobile app users' demands. And Artificial Intelligence and Machine Learning (AI & ML) have become the most influencing technologies in the field of mobile app development and creating a plethora of opportunities for startups in 2021.

The linear submodular bandit problem was proposed to simultaneously address diversified retrieval and online learning in a recommender system. If there is no uncertainty, this problem is equivalent to a submodular maximization problem under a cardinality constraint. However, in some situations, recommendation lists should satisfy additional constraints such as budget constraints, other than a cardinality constraint. Thus, motivated by diversified retrieval considering budget constraints, we introduce a submodular bandit problem under the intersection of $l$ knapsacks and a $k$-system constraint. Here $k$-system constraints form a very general class of constraints including cardinality constraints and the intersection of $k$ matroid constraints. To solve this problem, we propose a non-greedy algorithm that adaptively focuses on a standard or modified upper-confidence bound. We provide a high-probability upper bound of an approximation regret, where the approximation ratio matches that of a fast offline algorithm. Moreover, we perform experiments under various combinations of constraints using a synthetic and two real-world datasets and demonstrate that our proposed methods outperform the existing baselines.

The recent advances in artificial intelligence namely in machine learning and deep learning, have boosted the performance of intelligent systems in several ways. This gave rise to human expectations, but also created the need for a deeper understanding of how intelligent systems think and decide. The concept of explainability appeared, in the extent of explaining the internal system mechanics in human terms. Recommendation systems are intelligent systems that support human decision making, and as such, they have to be explainable in order to increase user trust and improve the acceptance of recommendations. In this work, we focus on a context-aware recommendation system for energy efficiency and develop a mechanism for explainable and persuasive recommendations, which are personalized to user preferences and habits. The persuasive facts either emphasize on the economical saving prospects (Econ) or on a positive ecological impact (Eco) and explanations provide the reason for recommending an energy saving action. Based on a study conducted using a Telegram bot, different scenarios have been validated with actual data and human feedback. Current results show a total increase of 19\% on the recommendation acceptance ratio when both economical and ecological persuasive facts are employed. This revolutionary approach on recommendation systems, demonstrates how intelligent recommendations can effectively encourage energy saving behavior.

Have you ever used Google Assistant, Apple's Siri, or Amazon Alexa to make decisions for you? Perhaps you asked it what new movies have good reviews, or to recommend a cool restaurant in your neighborhood. Artificial intelligence and virtual assistants are constantly being refined, and may soon be making appointments for you, offering medical advice, or trying to sell you a bottle of wine. Although AI technology has miles to go to develop social skills on par with ours, some AI has shown impressive language understanding and can complete relatively complex interactive tasks. In several 2018 demonstrations, Google's AI made haircut and restaurant reservations without receptionists realizing they were talking with a non-human.