If you ever feel like Gen Z is speaking an entirely different language, you are definitely not alone. Luckily for all the baffled parents out there, a new Alexa update should help you avoid giving your kids the ick with your sus Gen Z slang. From today, Amazon users will be able to ask Alexa to'talk Gen Z to me' to reveal one of 20 phrases using Gen Z's favourite words. That might include phrases such as'the math isn't mathing' which Alexa defines as'something is incorrect or unreasonable, something doesn't add up or make sense'. And as Amazon's survey of 2,385 Britons reveals that 83 per cent of Gen Z say the older generation fails to understand them, a little extra assistance might be welcome.

Recent advancements in the field of Artificial Intelligence (AI) have taken the world by storm. Deepfakes, DALL-E 2, ChatGPT, and all of their sister concerns have prepared the path for several arguments about the ethics, prospects, and eventual future of AI. Now, by using mid-journey AI, a Facebook user named Razib Jahan Ferdous rendered some pictures of the top Hollywood celebrities having iftar. In a Facebook post, he shared twelve pictures with the caption, "After the Eid shopping, in an iftar invitation at Sultan's Dine." In the picture, we can see actors like Morgan Freeman, Leonardo DiCaprio, Will Smith, Robert Downey Jr, Christian Bale, Tom Hanks, Tom Cruise, Brad Pitt, Dwayne Johnson, Arnold Schwarzenegger, Chris Hemsworth, and Angelina Jolie having iftar like us in a very Islamic way.

When people think about artificial intelligence, they rarely imagine the technology being used to sift through complex data sheets or find out how many people buy something because of a billboard, or figure out when a dog has sniffed cancer cells. That's typically the kind of thing AI is being used for these days – and while they're all cool, the common Dick and Jane probably aren't getting all too hyped up about it. However, hope is not lost for dreamers wishing for a Bradbury-esque future of machines creating things that are cool, even to the layman. There exists a growing field in AI technology devoted to "synthetic media" – art, content and creative materials that have been produced by an artificially intelligent creator. The current buzz in synthetic media is centered around AI image generation, with platforms such as DALL-E, CrAIyon and Midjourney leading the pack in the creation of art based on text prompts. Israeli start-up D-ID is the pioneer of a slightly different spin on the idea: taking a still photo of someone and turning it into a talking video.

The results you get when you search for an image on Google have something in common with Siri's ability to listen to your commands. All of these features are fed by enormous piles of data. These datasets might contain thousands of pictures of faces or gigabytes of audio logs of human speech. They are the raw material used by nearly everyone who wants to work with A.I., and they don't come cheap. It takes expertise and investment to build them.

Several deep models, esp. the generative, compare the samples from two distributions (e.g. WAE like AutoEncoder models, set-processing deep networks, etc) in their cost functions. Using all these methods one cannot train the model directly taking small size (in extreme -- one element) batches, due to the fact that samples are to be compared. We propose a generic approach to training such models using one-element mini-batches. The idea is based on splitting the batch in latent into parts: previous, i.e. historical, elements used for latent space distribution matching and the current ones, used both for latent distribution computation and the minimization process. Due to the smaller memory requirements, this allows to train networks on higher resolution images then in the classical approach.

But a traditional Tinder account is just too basic for the rich and famous (especially if they want to hookup with mutually wealthy people). Enter Loveflutter "Blue," the latest premium app aimed at celebs -- only this new dating service comes with a twist. The app exclusively caters to verified Twitter users. Hence its name, which refers to the platform's blue tick community. Its creators claim it's all about authenticity.

Sex robots modeled on celebrities are set to take the world by storm, a leading expert has warned. Leaps in technology have meant that even more shockingly realistic mechanical lovers will soon be on the market. Experts in the field of robotics have now revealed that the next logical step is for designers to create sex robots to look exactly like your favourite celebrities. David Levy, author of "Love and Sex with Robots", said the demand was "absolutely" there. The expert is convinced the sexy cyborgs would fly off the shelves.

Object queries are essential in information seeking and decision making in vast areas of applications. However, a query may involve complex conditions on objects and sets, which can be arbitrarily nested and aliased. The objects and sets involved as well as the demand---the given parameter values of interest---can change arbitrarily. How to implement object queries efficiently under all possible updates, and furthermore to provide complexity guarantees? This paper describes an automatic method. The method allows powerful queries to be written completely declaratively. It transforms demand as well as all objects and sets into relations. Most importantly, it defines invariants for not only the query results, but also all auxiliary values about the objects and sets involved, including those for propagating demand, and incrementally maintains all of them. Implementation and experiments with problems from a variety of application areas, including distributed algorithms and probabilistic queries, confirm the analyzed complexities, trade-offs, and significant improvements over prior work.