LG has announced that the G8 will arrive on April 11th, with pre-orders starting March 29th at major carriers including AT&T, Sprint, T-Mobile and Verizon (Engadget's parent company). It'll undercut its South Korean rival's price by a fair margin -- pricing starts at $820 up front versus Samsung's $900, and that's before the usual promos that knock as much as $150 off the price. Whether or not it's worth the savings over the S10 will likely depend on just how much you like LG's rather unusual priorities. You don't get a telephoto lens or 8GB of RAM ('just' 6GB) for the money, but you do get party tricks like in-the-air hand gestures, an OLED display that doubles as the speaker and a more secure, depth-based face unlock. That's not including more familiar staples like the quad DAC and a dedicated Google Assistant button.

When you're shopping, you probably have a general look in mind. But how do you describe that to a shopping site? It's implementing a feature that uses computer vision to find items that resemble what you're looking at. Tap the three-dot menu next to a product and it'll give you both simple category buttons (such as "athletic shoes") as well as a "looks like this" option to find visually similar items. Eye a green set of sneakers, for instance, and you should see comparable footwear without having to construct an elaborate search. This AI-guided shopping is available in eBay's Android and iOS apps right now, though it's currently only available in the US, UK, Australia and Germany.

President Donald Trump and his top U.S. military adviser met with Google's CEO about concerns that Silicon Valley's AI collaborations in China may benefit the Chinese military. Such worries reflect awareness of how certain technologies developed for civilian purposes can also provide military advantages in the strategic competition playing out between the United States and China. The meeting comes after General Joseph Dunford, chairman of the Joint Chiefs of Staff, leveled pointed criticism at Google for pursuing technological collaborations with Chinese partners, during his testimony before the Senate Armed Services Committee on 14 March. The spotlight's glare on Google grew harsher when President Trump followed up on Twitter: "Google is helping China and their military, but not the U.S. Terrible!" But beyond the focus on Google, the Pentagon seems more broadly concerned about U.S. tech companies inadvertently giving China a leg up in developing AI applications with military and national security implications.

Scientists have developed and tested an artificial intelligence (AI)-based computer system to predict the risk of early death due to chronic diseases in a large middle-aged population. The system of computer-based'machine learning' algorithms was very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts, according to the study published in the journal PLOS ONE. Researchers at the University of Nottingham in the UK used health data from over half a million people aged between 40 and 69 recruited to the UK Biobank between 2006 and 2010 and followed up until 2016. "Most applications focus on a single disease area but predicting death due to several different disease outcomes is highly complex, especially given environmental and individual factors that may affect them," said Stephen Weng, Assistant Professor at the University of Nottingham. "We have taken a major step forward in this field by developing a unique and holistic approach to predicting a person's risk of premature death by machine-learning," Weng said in a statement.

The Montreal Institute for Genocide and Human Rights Studies (MIGS) is organizing the Human Rights and Artificial Intelligence Forum on April 5. The event will take place at Concordia's 4TH SPACE, an innovative and immersive venue for state-of-the-art installations, which will permit leading experts from around the world to gather to discuss this emerging technology's implication for human rights. MIGS has convened thought leaders and practitioners with the goal of understanding how new technologies are disrupting global affairs. MIGS has worked with Global Affairs Canada and Tech Against Terrorism to explore how artificial intelligence (AI) can counter online extremism and how non-state actors might use AI for nefarious purposes. MIGS has also presented work on AI at the Hague Digital Diplomacy Camp organized by the Dutch Foreign Ministry.

"If you program a machine, you know what it's capable of. If the machine is programming itself, who knows what it might do?" ― Garry Kasparov Artificial Intelligence is a complex subject. However, reading and acquiring knowledge through books written on Artificial Intelligence, Machine Learning, Data Science and other related topics can help technology enthusiasts to a great extent. Here is a list of ten books on AI and Machine Learning that provide the information on basics of technology, its present, the future paradigm and the most rabid fictionalized set-ups that are expected to arrive in the coming future. We have rated the books on a scale of 1-5, considering their depth, research, uniqueness, reader's review, and the AiThority News Quotient.

The team of healthcare data scientists and doctors have developed and tested a system of computer-based'machine learning' algorithms to predict the risk of early death due to chronic disease in a large middle-aged population. They found this AI system was very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts. The study is published by PLOS ONE in a special collections edition of "Machine Learning in Health and Biomedicine." The team used health data from just over half a million people aged between 40 and 69 recruited to the UK Biobank between 2006 and 2010 and followed up until 2016. Leading the work, Assistant Professor of Epidemiology and Data Science, Dr Stephen Weng, said: "Preventative healthcare is a growing priority in the fight against serious diseases so we have been working for a number of years to improve the accuracy of computerised health risk assessment in the general population. Most applications focus on a single disease area but predicting death due to several different disease outcomes is highly complex, especially given environmental and individual factors that may affect them. "We have taken a major step forward in this field by developing a unique and holistic approach to predicting a person's risk of premature death by machine-learning.

Medical researchers have unlocked an unsettling ability in artificial intelligence (AI): predicting a person's early death. Scientists recently trained an AI system to evaluate a decade of general health data submitted by more than half a million people in the United Kingdom. Then, they tasked the AI with predicting if individuals were at risk of dying prematurely -- in other words, sooner than the average life expectancy -- from chronic disease, they reported in a new study. The predictions of early death that were made by AI algorithms were "significantly more accurate" than predictions delivered by a model that did not use machine learning, lead study author Dr. Stephen Weng, an assistant professor of epidemiology and data science at the University of Nottingham (UN) in the U.K., said in a statement. To evaluate the likelihood of subjects' premature mortality, the researchers tested two types of AI: "deep learning," in which layered information-processing networks help a computer to learn from examples; and "random forest," a simpler type of AI that combines multiple, tree-like models to consider possible outcomes. Then, they compared the AI models' conclusions to results from a standard algorithm, known as the Cox model.

Government usually isn't the place to look for innovation in IT or new technologies like artificial intelligence. But Ott Velsberg might change your mind. As Estonia's chief data officer, the 28-year-old graduate student is overseeing the tiny Baltic nation's push to insert artificial intelligence and machine learning into services provided to its 1.3 million citizens. "We want the government to be as lean as possible," says the wiry, bespectacled Velsberg, an Estonian who is writing his PhD thesis at Sweden's Umeå University on using the Internet of Things and sensor data in government services. Estonia's government hired Velsberg last August to run a new project to introduce AI into various ministries to streamline services offered to residents.

We present RAPID (Real-time Automated Photometric IDentification), a novel time-series classification tool capable of automatically identifying transients from within a day of the initial alert, to the full lifetime of a light curve. Using a deep recurrent neural network with Gated Recurrent Units (GRUs), we present the first method specifically designed to provide early classifications of astronomical time-series data, typing 12 different transient classes. Our classifier can process light curves with any phase coverage, and it does not rely on deriving computationally expensive features from the data, making RAPID well-suited for processing the millions of alerts that ongoing and upcoming wide-field surveys such as the Zwicky Transient Facility (ZTF), and the Large Synoptic Survey Telescope (LSST) will produce. The classification accuracy improves over the lifetime of the transient as more photometric data becomes available, and across the 12 transient classes, we obtain an average area under the receiver operating characteristic curve of 0.95 and 0.98 at early and late epochs, respectively. We demonstrate RAPID's ability to effectively provide early classifications of transients from the ZTF data stream. We have made RAPID available as an open-source software package (https://astrorapid.readthedocs.io) for machine learning-based alert-brokers to use for the autonomous and quick classification of several thousand light curves within a few seconds.