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Machine-learning algorithms can dramatically improve ability to predict suicide attempts
Each year in the United States, more than 40,000 people die by suicide, and from 1999 to 2014, the suicide rate increased 24 percent. You might think that after generations of theories and data, we would be close to understanding how to prevent self-harm, or at least predict it. But a new study concludes that the science of suicide prediction is dismal, and the established warning signs about as accurate as tea leaves. There is, however, some hope. New research shows that machine-learning algorithms can dramatically improve our predictive abilities on suicides.
Introducing Similarity Search at Flickr
At Flickr, we understand that the value in our image corpus is only unlocked when our members can find photos and photographers that inspire them, so we strive to enable the discovery and appreciation of new photos. To further that effort, today we are introducing similarity search on Flickr. If you hover over a photo on a search result page, you will reveal a "โฆ" button that exposes a menu that gives you the option to search for photos similar to the photo you are currently viewing. In many ways, photo search is very different from traditional web or text search. First, the goal of web search is usually to satisfy a particular information need, while with photo search the goal is often one of discovery; as such, it should be delightful as well as functional.
Struggle analytics: Machine learning just made online struggles predictable - IBM THINK Marketing
Thank you for subscribing to the monthly THINK Marketing newsletter. Surely, both are struggles, but at least the alarm clock is anticipated. The way we manage our customer experience isn't all that different. Whether launching a test environment, integrating a third-party app into your checkout process, or monitoring a known bug in your mobile application, some online struggle is anticipated. It's the unanticipated struggle, however, that really causes the pain.
Genpact leverages artificial intelligence to help CFOs run smarter organizations with faster, more accurate financial reporting
New Delhi [India], Mar 10: Global leader in digitally-powered business process management and services Genpact has launched its Artificial Intelligence (AI) Reporting solution that harnesses the power of AI technologies to automate financial planning and analysis (FP&A) operations and drive more timely, insightful reporting. CFOs have fast, seamless access to both internal and external data sources like never before, driving more accurate forecasts for quicker, smarter business decisions. Based on multiple studies including a study done jointly by the Genpact Research Institute and HfS Research, CFOs across the board struggle with three challenges in providing actionable insights to their business leaders, including the ability to get relevant disparate data from internal and external sources; delay and the effort it takes for their teams to manage and do basic analysis on that data, reducing its relevance and leaving little scope for predictive analytics and business insight value adds; and lack of reporting mechanism that creates the user experience for business leaders to use that data to drive real time actions. Genpact's cloud-based AI Reporting solution uses advanced digital technologies to help enterprises reimagine the end-to-end financial reporting process. By integrating structured and unstructured data from internal and external sources, and automating reporting processes with predictive analytics, natural language processing and generation, and machine learning, the solution drives greater agility to adapt to new business requirements.
AI Will Turn Journalists Into Centaurs
Many fear that artificial intelligence (AI) will one day replace huge swaths of the workforce. Last year The World Economic Forum predicted that AI and automation technologies will displace 5 million jobs by 2020, with healthcare, energy, and financial industries experiencing the greatest job losses. Some pundits predict that AI will also replace journalists. The theory is that as machines gain a more nuanced understanding of language, they will be able to produce the type of content that human journalists currently produce. The Washington Post, for example, uses an AI bot called Heliograph to produce news stories.
Artificial Intelligence, UX & The Future of Findability
I'm completely obsessed with the idea of using artificial intelligence, search patterns and information architecture to improve the findability of content. It seems like we're on the cusp of doing amazing things with chatbots and data mining, which can augment manual information architecture work and result in a better user experience overall. Let's say you have a service that includes a search component. Right now your users might be running searches and using manual filters to sort through the results, as search users are wont to do. How do you know if they are finding what they need?
How online retailers are using artificial intelligence to make shopping a smoother experience - ET Retail
The next time you shop on fashion website Myntra, you might end up choosing a t-shirt designed completely by a software--the pattern, colour and texture-without any intervention from a human designer. The first set of these t-shirts went on sale four days ago. This counts as a significant leap for Artificial Intelligence in ecommerce. For customers, buying online might seem simple--click, pay and collect. Behind the scenes, from the warehouses to the websites, artificial intelligence plays a huge role in automating processes.
Why Google's DeepMind next-gen machine learning will stay undercover
Google's DeepMind, a London-based artificial intelligence company the search-and-cloud giant acquired in 2014, has been closely associated with Google's quest to build general AI. Earlier this year, with little publicity, DeepMind unveiled what looks like a useful step in that direction. The DeepMind team released a paper describing a neural network approach that would allow automatic "transfer learning," meaning a neural network could reuse what it already "knows" on new problems. If history is any hint, this is one innovation Google will keep close to its chest. Neural networks are a common type of machine learning that mimic, perhaps distantly, how neurons interrelate in the brain to pass information around.
Genpact leverages artificial intelligence to help CFOs run smarter Latest News & Updates at Daily News & Analysis
Global leader in digitally-powered business process management and services Genpact has launched its Artificial Intelligence (AI) Reporting solution that harnesses the power of AI technologies to automate financial planning and analysis (FP&A) operations and drive more timely, insightful reporting. CFOs have fast, seamless access to both internal and external data sources like never before, driving more accurate forecasts for quicker, smarter business decisions. Based on multiple studies including a study done jointly by the Genpact Research Institute and HfS Research, CFOs across the board struggle with three challenges in providing actionable insights to their business leaders, including the ability to get relevant disparate data from internal and external sources; delay and the effort it takes for their teams to manage and do basic analysis on that data, reducing its relevance and leaving little scope for predictive analytics and business insight value adds; and lack of reporting mechanism that creates the user experience for business leaders to use that data to drive real time actions. Genpact?s cloud-based AI Reporting solution uses advanced digital technologies to help enterprises reimagine the end-to-end financial reporting process. By integrating structured and unstructured data from internal and external sources, and automating reporting processes with predictive analytics, natural language processing and generation, and machine learning, the solution drives greater agility to adapt to new business requirements.
Our Tech Predictions for 2017 โ Kickstarter
Every December, we take a look back at big ideas from the past twelve months that promise to gain momentum in the new year. With more than eleven thousand projects launched between our Design and Tech categories in 2016, we have a nice sample to draw from. More importantly, we have a community of forward-thinking backers who help creators figure out which versions of the future to pursue. Here are some of the emerging trends we expect to see more of in 2017. With the headphone jack inching closer to the endangered-features list this year thanks to Apple, a number of projects have made a compelling case for pushing beyond the limits of traditional stereo sound.