Dr David Levy, an expert on artificial intelligence (AI), said in an interview with the Daily Star that the way technology is developing nowadays, the world might soon face a serious challenge from AI-equipped robots of all types. Levy complained that governments are acting too slowly when it comes to introducing new laws and addressing the new challenge, recalling how the Dutch Ministry of Defence had ignored his warnings regarding the potentially malign use of drones and, less than a year later, simple drones were able to paralyse the work of Gatwick Airport in the UK during Christmas season. The AI expert argues that in order to draw more attention to the problem, a "Greta Thunberg of the robot world" is needed, adding that dangerous robots are likely to harm humanity sooner than climate change. Thunberg, a famous teenage environmental activist, rose to prominence globally in recent years by rallying students around the world to take part in her "strikes for climate", which are designed to draw attention to ecological problems. She also made an appearance at a UN committee devoted to the topic, delivering a passionate speech in which she accused global leaders of doing too little to address climate change.

You take a picture of a person, upload it and get to see public photos of that person along with links to where those photos appeared. By Kashmir Hill Until recently, Hoan Ton-That's greatest hit was an app that let people put Donald Trump's distinctive yellow hair on their own photos. Then Ton-That did something momentous: He invented a tool that could end your ability to walk down the street anonymously and provided it to hundreds of law enforcement agencies. His tiny company, Clearview AI, devised a groundbreaking facial recognition app. You take a picture of a person, upload it and get to see public photos of that person along with links to where those photos appeared.

More than a decade has passed since the British government issued an apology to the mathematician Alan Turing. The tone of pained contrition was appropriate, given Britain's grotesquely ungracious treatment of Turing, who played a decisive role in cracking the German Enigma cipher, allowing Allied intelligence to predict where U-boats would strike and thus saving tens of thousands of lives. Unapologetic about his homosexuality, Turing had made a careless admission of an affair with a man, in the course of reporting a robbery at his home in 1952, and was arrested for an "act of gross indecency" (the same charge that had led to a jail sentence for Oscar Wilde in 1895). Turing was subsequently given a choice to serve prison time or undergo a hormone treatment meant to reverse the testosterone levels that made him desire men (so the thinking went at the time). Turing opted for the latter and, two years later, ended his life by taking a bite from an apple laced with cyanide.

Yesterday, The New York Times ran an alarming piece by Kashmir Hill about Clearview AI, a startup that allows third parties to quickly learn many details about you based on only seeing your face; The New York Times further reported that Clearview's technology is already in use by government agencies across the United States. Today, therefore, I am sharing some tips on how to prevent yourself from being recognized by facial recognition systems. I have personally utilized some of these techniques in test environments – and they worked. Others I have seen demonstrated. Keep in mind that not all of the tips that I provide below apply in all environments – normally, people seeking not to be recognized also do not want to stand out.

For e-retailers, deep learning offers immense opportunities to increase conversion rates and improve the brand image through positive customer experience. According to a 2018 U.S. Census Bureau report, the e-Commerce industry has shown impressive growth in the past one decade. The online revenues have steadily eaten into an additional 1.5% of the yearly retail sales for the past several years. Tech giant Amazon is projected to make up half of all eCommerce sales in the US by 2021. Statista predicts the global e-Commerce sales will amount to $ 4.88 trillion; thereby, showcasing a yearly growth of 20%.

Spectral clustering has been one of the widely used methods for community detection in networks. However, large-scale networks bring computational challenge to it. In this paper, we study spectral clustering using randomized sketching algorithms from a statistical perspective, where we typically assume the network data are generated from a stochastic block model. To do this, we first use the recent developed sketching algorithms to derive two randomized spectral clustering algorithms, namely, the random projection-based and the random sampling-based spectral clustering. Then we study the theoretical bounds of the resulting algorithms in terms of the approximation error for the population adjacency matrix, the misclustering error, and the estimation error for the link probability matrix. It turns out that, under mild conditions, the randomized spectral clustering algorithms perform similarly to the original one. We also conduct numerical experiments to support the theoretical findings.

The robots are coming...in the form of voice-first, conversational A...I-based chatbots that use Natural Language Processing and Machine Learning to "understand" human commands and questions and respond appropriately, at scale, in real time, on behalf of individuals and institutions. The "Harvard UltraBot" could represent the university to potential applicants, the media, and other universities, through their respective UltraBots. A "LinkedIn UltraBot" from Microsoft could give voice to users and allow them to build and interface with their networks in a direct and intuitive way, by speaking. Harvard, Stanford, and UC Berkeley may soon all be racing to produce prototype and production models of their respective UltraBots. Etopia Media Consulting is advising every 2020 Presidential candidate to read "Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World," by Marco Iansiti and Karim Lakhani, both at Harvard Business School.

It has penetrated almost every industry and is helping them become innovative, develop authentic tools, and build strategies towards a sustainable future. Researchers are eagerly exploring new use cases of artificial intelligence that have the power to radically transform societies around us. But as we develop intelligence artificially, will be there a room for this AI to rewire us as humans? Artificial intelligence has come a long way since its inception. We are at the brink of a massive change where world leaders are constantly discussing whether AI will take over the world and start controlling us. Even though it might not seem possible at the moment, there are plenty of theories that suggest the deadly impact of AI in the future.

A couple of years ago, Vladimir Putin warned Russians that the country that led in technologies using artificial intelligence will dominate the globe. He was right to be worried. Russia is now a minor player, and the race seems now to be mainly between the United States and China. But don't count out the European Union just yet; the EU is still a fifth of the world economy, and it has underappreciated strengths. Technological leadership will require big digital investments, rapid business process innovation, and efficient tax and transfer systems.

Alphabet, the tech giant formerly known as Google, on Thursday night became the fourth company in history to reach a trillion-dollar (£776bn) valuation. In less than 24 hours, some analysts were predicting that the company, founded in a messy Silicon Valley garage 21 years ago, could double in value again to become a $2tn firm "in the near future". The consensus among Wall Street bankers is nothing can stop the runaway share price rises of Alphabet or the other so-called "Faang" tech companies. Facebook, Amazon, Apple, Netflix and Google have seen their combined market value increase by $1.3tn over the past year – that's the equivalent of adding half the value of all the companies in the FTSE 100, or the entire GDP of Mexico. "It's such a phenomenally large number that it's difficult for most of us even to quantify the value," said Paul Lee, the global head of technology research at Deloitte.