Alex Pretti's Minneapolis death was murder, Americans declare in damning poll as voters issue new demand to Trump... and reveal how few back the shooting'Greedy pig' Harry Styles is shamefully exploiting obsessed women. I know... because it happened to me: LIZ JONES My sister confided an unbearable secret about her boyfriend. Keeping quiet is intolerable... our mother will be devastated: DEAR JANE Trump accounts: Million-dollar baby plan aims to create a fortune for America's newest arrivals before age 30 Nicki Minaj flashes dagger-long nails as she clutches Trump's hand after gushing she's his No. 1 fan Bryan Kohberger's warped requests from behind bars leave prison guards sickened... as new pictures of Idaho murders reveal full extent of his barbarity Bruce Willis' wife Emma makes heartbreaking admission about star's dementia battle Hilarious live gaffe on David Muir's World News Tonight that'triggered behind the scenes meltdown' Haley Kalil confident her bitter lawsuit with ex-NFL star husband will be thrown out as she cites'free speech' after revealing size of his manhood'He was Mr Perfect... now we're seeing his true colours': How Harry Styles cultivated his'good boy' image... and why fans are now turning on him after this controversial new move Mom who gave all four of her daughters the same name slams critics: 'Our family doesn't need outside approval' Brooklyn Beckham and Nicola Peltz share photo of the'world's most expensive wine' at £17,000 a BOTTLE... as it's revealed she gets a '$1m monthly allowance' from her billionaire father Would YOU sit on it? Scientists develop a futuristic chair that puts you in an'altered state of mind' within minutes READ MORE: People are using'binaural beats' to simulate the effects of drugs Would you be brave enough to sit on a chair that can send you into an'altered state of mind' within minutes? That is the wild promise of the Aiora chair, a futuristic seat designed by scientists from the University of Essex and British furniture company DavidHugh LTD.

Our friends from across the pond have been known to struggle with British sarcasm on occasion. But improved Anglo-American relations may be on the horizon, as experts have developed a device that can detect when someone is being sarcastic. A team from the University of Groningen have created an algorithm that analyses someone's speech to work out if they are using irony. It works by examining the pitch, talking rate and energy in speech, and then transcribing the speech into text for it to be analysed further for language cues. 'We extracted acoustic parameters such as pitch, speaking rate, and energy from speech, then used Automatic Speech Recognition to transcribe the speech into text for sentiment analysis,' author Xiyuan Gao said.

A huge, super-fast indestructible robot hand might seem like a terrifying prop from a science-fiction film. But this hefty 4.1kg (9.9lbs) hand is very real and is already being used to develop the next generation of AI robots. Designed by UK-based Shadow Robot Company, this three-fingered claw can go from fully open to closed in just 500 milliseconds. However, the robot hand is still tough enough to resist being bashed with hammers or pounded by pistons. That toughness is designed to help the hand survive the rigorous and often destructive process of teaching AI how to interact with the world.

It's a problem that drives the parents of most teenagers mad. But clothes piled up on the bedroom floor may soon be a problem of the past as scientists have developed a cleaning robot to pick up dirty laundry. Scientists from UC Berkeley say their clothes-collecting bot solves the'Teenagers Problem; of how to most efficiently pick up mess. Using a combination of colour and depth-sensing cameras the robot collects laundry into piles before finding the best place to grab the clothes. Professor Ken Goldberg, the study's lead author, says that this technology could become commercially available in the decade, meaning we may soon all have a robotic helper around the house.

For centuries, humankind has been captivated by the thought of life on other planets. But how will we recognise it when we see it? Researchers have developed an artificial intelligence system that can detect signs of life with 90 per cent accuracy. And they say it signifies a'significant advance' in our abilities to discover life across the solar system and beyond. Many of the components necessary for life, such as amino acids and nucleotides needed to make DNA, have been detected in space.

The robo-chef can learn how to create the perfect dish, simply from watching cooking videos. Researchers at the University of Cambridge have programmed a machine to make a meal by following how a human makes it. Using sophisticated AI, the robot is able to work out from every frame which objects it is looking at – such as a vegetable, hand, or knife – and how it is being used. Over time, it is then able to identify which ingredients work best together – and even point out when the human chef may have used the wrong amount. Robotic chefs have been featured in science fiction for decades, but in reality, cooking is a challenging problem for a robot.

Associate Professor of the Department of Information Technologies and Computer Sciences at MISIS University, Ph.D., mathematician and doctor Alexandra Bernadotte has developed algorithms that significantly increase the accuracy of recognition of mental commands by robotic devices. The result is achieved by optimizing the selection of a dictionary. Algorithms implemented in robotic devices can be used to transmit information through noisy communication channels. The results have been published in the peer-reviewed international scientific journal Mathematics. The task of improving the object (audio, video or electromagnetic signals) classification accuracy, when compiling so-called "dictionaries" of devices is faced by developers of different systems aimed to improve the quality of human life.

While most of us think of airport security as fairly accurate, studies have shown that screeners fail to detect weapons, drugs, and explosives up to 80 per cent of the time. But a new X-ray method could make it much easier for screeners to detect these illegal and dangerous items. Researchers from University College London used AI to develop the approach, which they say can detect items with 100 per cent accuracy. Tristram Riley-Smith, co-author of the study, said: 'This research has demonstrated the potential to transform the detection of covert threats around the world, as well as such varied contraband as narcotics and illicit wildlife commodities.' The X-ray technique relies on the fact that microscopic changes or irregularities in objects cause X-ray beams to bend as they pass through them – something the researchers discovered in previous research.

Have you ever lost your grip on something that you've dropped into the swimming pool, or worse, toilet? Scientists may have developed a solution to holding onto underwater objects, but it is not primarily intended to help you rescue your iPhone from a watery fate. Researchers at Virginia Tech have developed a glove that will allow divers to get a firm grasp while, for example, rescuing someone or salvaging a shipwreck. The'octa-glove' is inspired by octopus tentacles, and is covered in robotic suckers equipped with sensors that can tell how far away an object is. When the sensors detect a nearby surface, it sends a signal to the controller which will activate the sucker's adhesion.

According to a new KAUST study, machine learning approaches can achieve an assumption-free analysis of epidemic case data with amazingly good prediction accuracy and the flexibility to incorporate new data dynamically. Yasminah Alali, an intern in KAUST's 2021 Saudi Summer Internship (SSI) program, developed a proof of concept that reveals a possible alternative to traditional parameter-driven mechanistic models by removing human bias and assumptions from analysis, revealing the underlying story of the data. Using publicly released COVID-19 incidence and recovery data from India and Brazil, Alali leveraged her experience working with artificial intelligence models to design a framework to fit the characteristics and time-evolving nature of epidemic data in collaboration with KAUST's Ying Sun and Fouzi Harrou. To create an effective Gaussian process regression (GPR) based model for forecasting recovered and confirmed COVID-19 cases in two significantly impacted countries, India and Brazil, the researchers first used Bayesian optimization to modify the Gaussian process regression (GPR) hyperparameters. However, the time dependency in the COVID-19 data series is ignored by machine learning models.