The term artificial intelligence (AI) refers to computing systems that perform tasks normally considered within the realm of human decision making. These software-driven systems and intelligent agents incorporate advanced data analytics and Big Data applications. AI systems leverage this knowledge repository to make decisions and take actions that approximate cognitive functions, including learning and problem solving. AI, which was introduced as an area of science in the mid 1950s, has evolved rapidly in recent years. It has become a valuable and essential tool for orchestrating digital technologies and managing business operations.

Recent model-based Recommender Systems (RecSys) algorithms emphasize on the use of features, also called side information, in their design similar to algorithms in Machine Learning (ML). In contrast, some of the most popular and traditional algorithms for RecSys solely focus on a given user-item-rating relation without including side information. The goal of this case study is to provide a performance comparison and assessment of RecSys and ML algorithms when side information is included. We chose the Movielens-100K data set since it is a standard for comparing RecSys algorithms. We compared six different feature sets with varying quantities of features which were generated from the baseline data and evaluated on a total of 19 RecSys algorithms, baseline ML algorithms, Automated Machine Learning (AutoML) pipelines, and state-of-the-art RecSys algorithms that incorporate side information. The results show that additional features benefit all algorithms we evaluated. However, the correlation between feature quantity and performance is not monotonous for AutoML and RecSys. In these categories, an analysis of feature importance revealed that the quality of features matters more than quantity. Throughout our experiments, the average performance on the feature set with the lowest number of features is about 6% worse compared to that with the highest in terms of the Root Mean Squared Error. An interesting observation is that AutoML outperforms matrix factorization-based RecSys algorithms when additional features are used. Almost all algorithms that can include side information have higher performance when using the highest quantity of features. In the other cases, the performance difference is negligible (<1%). The results show a clear positive trend for the effect of feature quantity as well as the important effects of feature quality on the evaluated algorithms.

In task-oriented dialogue (ToD), a user holds a conversation with an artificial agent  with the aim of completing a concrete task. Although this technology represents one of  the central objectives of AI and has been the focus of ever more intense research and  development efforts, it is currently limited to a few narrow domains (e.g., food ordering,  ticket booking) and a handful of languages (e.g., English, Chinese). This work provides an  extensive overview of existing methods and resources in multilingual ToD as an entry point  to this exciting and emerging field. We find that the most critical factor preventing the  creation of truly multilingual ToD systems is the lack of datasets in most languages for  both training and evaluation. In fact, acquiring annotations or human feedback for each  component of modular systems or for data-hungry end-to-end systems is expensive and  tedious. Hence, state-of-the-art approaches to multilingual ToD mostly rely on (zero- or  few-shot) cross-lingual transfer from resource-rich languages (almost exclusively English),  either by means of (i) machine translation or (ii) multilingual representations. These  approaches are currently viable only for typologically similar languages and languages with  parallel / monolingual corpora available. On the other hand, their effectiveness beyond these  boundaries is doubtful or hard to assess due to the lack of linguistically diverse benchmarks  (especially for natural language generation and end-to-end evaluation). To overcome this  limitation, we draw parallels between components of the ToD pipeline and other NLP tasks,  which can inspire solutions for learning in low-resource scenarios. Finally, we list additional  challenges that multilinguality poses for related areas (such as speech, fluency in generated  text, and human-centred evaluation), and indicate future directions that hold promise to  further expand language coverage and dialogue capabilities of current ToD systems. 

It's not often that you upgrade your TV, but Amazon Prime Day is a good time to consider doing so. Prime members can get steep discounts right now on Fire TVs and sets from other companies like Sony, Samsung and others. And not every sale on Prime day is exclusive to Prime members -- there are some discounts that are available to anyone, so it's worth checking out the televisions on sale during the two-day shopping event. If you're not looking for a brand new TV, there are other home entertainment gadgets on sale too, including streaming devices, soundbars and more. Here are the best TV and home entertainment deals we found for Prime Day 2022.

Shopping for a new way to enjoy your favorite music, podcasts, or TV shows? Below you'll find the best headphones and speakers we've seen on sale this Prime Day. Be sure to check out our guides to the Best Wireless Headphones, Best Noise-Canceling Headphones, Best Workout Headphones, and Best Bluetooth Speakers for more information about what's hot right now. The WIRED Gear team tests products year-round. We sorted through hundreds of thousands of deals by hand to make these picks.

In addition to e-readers, cameras and smartwatches, you can also get streaming devices at a huge discount this Prime Day. NVIDIA's Shield streamers, for instance, are currently listed for the lowest prices we've seen for them on the website. You can get the base NVIDIA Shield TV streaming media player for $125, or $25 less than its original retail price. Meanwhile, the NVIDIA Shield TV Pro will now only set you back $170, which gives it a discount of $30 and is $9 lower than its previous all-time low. Both devices are powered by Android TV and come with built-in Google Assistant, allowing you to control them with voice commands through a Google Home speaker.

While Prime Day deals have discounted most of Amazon's gadgets, one of the most affordable you can get is the Echo Dot. The company has knocked 60 percent off the small smart speaker, bringing it down to a new record low of $20. The Echo Dot with Clock is also cheaper than ever right now at only $33, while the full-sized Echo speaker has dropped to $60. We've recommended the Echo Dot in many gift guides because it combines Alexa chops with decent audio quality in an attractive, compact package. The fabric-covered orb is small enough to fit on a nightstand easily and we like that you can control it via Alexa commands or the few touch options on the device itself.

Are you ready to learn what is artificial super intelligence? You undoubtedly hear a lot about artificial intelligence these days if you live on our planet. AI is considered a threat to human employment opportunities even though we use artificial intelligence in everyday life. What is artificial super intelligence is the question of the day. The term "artificial superintelligence" describes the stage at which computer intelligence exceeds that of humans. Since the 1970s, the phrase "artificial intelligence" has been used to describe computers' capacity for human-like thought.

There's arguably no better time than Prime Day to buy a piece of tech made by Amazon. You'll find most of Amazon's gadgets are on sale for Prime Day, including the latest models of things like the Kindle Paperwhite and the Echo Show 8. Also, Amazon-owned devices, like Eero routers and Blink security cameras, are cheaper than ever, too. Here are the best deals on Amazon devices you can get for Prime Day 2022. Amazon's Echo smart speaker has dropped to $60. It earned a score of 89 from us for its solid audio quality, attractive design and its inclusion of a 3.5mm audio jack.

Raghu Ravinutala is CEO and co-founder of enterprise-grade conversational AI platform Yellow.ai. After 27 years since the commercialization of the internet, 5 billion people have an online presence today. The first two phases of the Web--Web 1.0 and 2.0--were relatively staid compared to what's coming. Today, we're on the threshold of Web3 and the metaverse--internet environments where transactions are logged on the blockchain and powered by AI. By 2026, Web3 technologies--such as digital twins, smart spaces, virtual and augmented reality, and advanced virtual assistants--will transform how people interact with the world.