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.

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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.

Recommendation systems have been widely used in various domains such as music, films, e-shopping, etc. After mostly avoiding digitization, the art world has recently reached a technological turning point due to the pandemic, making online sales grow significantly as well as providing quantitative online data about artists and artworks. In this work, we present a content-based recommendation system on contemporary art relying on images of artworks and contextual metadata of artists. We gathered and annotated artworks with advanced and art-specific information to create a completely unique database that was used to train our models. With this information, we built a proximity graph between artworks. Similarly, we used NLP techniques to characterize the practices of the artists and we extracted information from exhibitions and other event history to create a proximity graph between artists. The power of graph analysis enables us to provide an artwork recommendation system based on a combination of visual and contextual information from artworks and artists. After an assessment by a team of art specialists, we get an average final rating of 75% of meaningful artworks when compared to their professional evaluations.

In the late summer of 2020, when much of normal social life was suspended, a relationship that I had been in for several years abruptly collapsed. I was thirty-nine and scared by the idea that I would not be reproducing the kind of heteronormative nuclear family I had grown up in. I wandered the sidewalks of my Brooklyn neighborhood, where discarded masks littered the gutters, with a sense of having been exiled from my own life. My apartment, with its cat and its plants, still existed but was no longer my home; I could get a glass of cold prosecco at my favorite bar, but the people I used to see there seemed to have vanished. In Haruki Murakami's novel "1Q84," a character climbs down a ladder into a parallel existence in which things appear to be the same but nothing really is.