One Drop, a leader in the development of digital therapeutics solutions for people with diabetes, today announced the launch of Blood Glucose Prediction and Automated Decision Support. Through these new features, the One Drop Mobile app will provide users: (1) blood glucose "forecasts" up to 12 hours into the future; and (2) behavioral recommendations based on those forecasts, thereby empowering users to manage diabetes proactively and reduce the risk complications. Through One Drop's predictive analytic capabilities, people with diabetes will now be able to receive actionable insights into how their behavior (diet, physical activity, etc.) affects their blood glucose levels, without any intervention from a health care provider. The app will simply display insights for the user as they become relevant. Blood glucose predictions come from One Drop's machine learning models, which are powered by over 1.1 billion data points collected by more than 860,000 One Drop Mobile app users worldwide.
Its revenue jumped 50 per cent to $166.5 million for the year to December 31, underlying earnings before interest, tax, depreciation and amortisation rose 62 per cent to $28.1 million and underlying net profit after tax rose 86 per cent to $19.7 million. RBC Capital Markets equity research vice-president Paul Mason said Appen had historically been conservative in its forecast numbers at the full-year end and often ended up upgrading its estimates following its half-year results – which he believed could be contributing to the company's recent share price surge. "Its guidance in February shocked the market and was way ahead of consensus. At the AGM a month ago it said it's trending to the upper end of its guidance and that was predicated on a currency number, which means it could exceed it further," he said. "The market had been too bearish and it's realising this and re-examining the stock right now."
We're now four or five years into the current explosion of machine learning, and pretty much everyone has heard of it. It's not just that startups are forming every day or that the big tech platform companies are rebuilding themselves around it - everyone outside tech has read the Economist or BusinessWeek cover story, and many big companies have some projects underway. We know this is a Next Big Thing. Going a step further, we mostly understand what neural networks might be, in theory, and we get that this might be about patterns and data. Machine learning lets us find patterns or structures in data that are implicit and probabilistic (hence'inferred') rather than explicit, that previously only people and not computers could find.
Smart Visualization is not the only way of making AI transform BI in a big way. There are other ways too. Before coming to those, let us discuss smart visualization a little more. As we understand from my previous post, it helps in eliminating the gap between experts and non-experts. That means it helps in getting better business results by actually involving and engaging business experts who are not too tech savvy and don't use any query languages.
If you've spent much time on crypto Twitter within the past couple of days, you may have seen some discussion and even hysteria regarding a recently-mined block. Block #528249's six leading characters were "21e800", a phrase that has grabbed the attention of conspiracists and curious individuals throughout the cryptocurrency space. "An Exceptionally Simple Theory of Everything" is often referred to as E8 Theory, the mathematical model on which it is based. The Theory of Everything asserts that the interaction of all forces within the universe can be explained through a single mathematical model. It was first introduced in 2007, and remains unproven.
With the advent of new technologies, experts now say the definition of intelligence is changing. Smart people are not just individuals capable of solving complicated problems on their own, but also those who understand the way artificial intelligence, or AI, can best serve them. Simply put, understanding technology is essential. Yet technology and artificial intelligence often scare people who get tangled in complicated explanations of what AI is and how it works. Two professors, Nick Polson from the University of Chicago Booth School of Business and James Scott from the University of Texas at Austin, tried to put a face on the technology by writing a book that illustrates the beginning of AI through several examples of historical figures and other individuals who developed algorithms for humanity's different problems.
Now, if a clerk asks to help you, it probably means you've been acting shady. Artificial intelligence continues to seep into our daily lives, touching up photos, developing snacks, and imitating school girls online. Now, AI has been tasked with tackling a crime as old as retail itself: shoplifting. A recent study by telecom giant NTT found that Japanese businesses lose around 400 billion yen (US$3.7B) annually through five-fingered discounts. No store is immune to this larceny, except perhaps anvil shops, and technology has yet to come up with a strong enough solution to effectively combat it, until now.
NEW YORK: The outcome of robotic-assisted surgery and traditional open surgery are equally effective in treating bladder cancer, say researchers, led by one of an Indian-origin. The results, published in the journal The Lancet, may help patients and doctors to make informed decisions on the use of robotic surgery, which is not cheap, the researchers said. There has been an assumption that patients who receive robotic surgery will perceive a better quality of life than patients who have open surgery. However, the trial showed that both groups had a significant return to their previous quality of life, and there was no advantage of one group over the other at three and six months after surgery. "We have done more than four million surgeries with the robotic approach since the device came into existence, and on average we do close to a million robotic surgeries a year globally," said Dipen J. Parekh, Chief Clinical Officer at the University of Miami, Florida in the US.
Published Sunday, Jun. 24, 2018, 12:48 pm Dear EarthTalk: What are some ways artificial intelligence is being used to fight climate change and otherwise protect the environment? Artificial intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet.
Editor's Note: SHRM has partnered with Harvard Business Review to bring you relevant articles on key HR topics and strategies. Today, executives have to cut through a lot of hype around automation. Leaders need a clear-eyed way to think about how these technologies will specifically affect their organizations. The right question isn't which jobs are going to be replaced, but rather, what work will be redefined, and how? Based on our work with a number of organizations grappling with these issues, we've found that the following four-step approach can help.