business process management

The Next Era in Business Process Management: Artificial Intelligence - RTInsights


By using supervised machine learning, a BPM tool could find valuable patterns in data and automate business processes. In the past, the goals of digital transformation were met primarily with business process management (BPM) tools, which aim to help companies orchestrate resources, route work to the right people, automate routine manual tasks, and enable self-service where none existed before. The idea is that by connecting AI to existing BPM tools, and delivering the data generated by digitized processes to AI systems, companies could do even more work to cut human latency (and thus costs) out of processes while also delivering a better end product to customers. By eliminating the manual processes from determining the best targets for marketing, the BPM tool allows human employees to focus on more complex processes that drive more productivity and revenue, such as fine-tuning those personalized campaigns for higher conversion rates.

Silicon Valley Bank survey finds big data, AI will have greatest impact on healthcare industry


Artificial intelligence and big data are shaping up to have the biggest impact on the healthcare industry, and most of that money will be coming from venture capital funds, according to a new survey of digital health executives and investors. Silicon Valley Bank surveyed 122 founders, executives and investors in health technology, asking about the biggest opportunities and threats for the industry in the next year. Almost half of respondents say big data, followed by artificial intelligence (35 percent) are the most promising technologies in terms of impact on investment. Venture capital will offer the most funding, nearly 62 percent of survey respondents said, with the next closest expected to be corporate ventures.

Impact of deep learning on computer vision


The technological challenges that must be addressed before autonomous cars can be unleashed onto the streets are quite significant. Using deep learning techniques, the computer can look at hundreds and thousands of pictures, e.g., an electric guitar, and start to learn what an electric guitar looks like in different configurations, contexts, levels of daylight, backgrounds and environments. Sitting behind all this intelligence are neural networks; computer models that are designed to mimic our understanding of how the human brain works. The following year there were of course multiple deep learning models and Microsoft broke records recently when its machine was able to beat their human control subject in the challenge.

Don't You Look Smart: 45 Artifical Intelligence Startups Targeting Retail In One Infographic


Using CB Insights data, we dove into the wide array of AI startups focused on retailers and e-commerce businesses, including AI-powered personal shopping apps, natural language processing and image recognition tools for shopping websites, predictive inventory allocation tools, and more. Real-time product targeting - Machine learning to present online shoppers with personalized product recommendations. Natural language search - Algorithms that use natural language processing to improve search functionality in e-commerce websites. Location-based marketing & analytics - Startups that combine digital and physical store analytics, while also integrating beacon technology to track shoppers' locations.

How the Brain Decodes Sentences


Words working together make sentences, and sentences can express meanings that are unboundedly rich. In contrast, when the person in the scanner is reading an entire sentence, brain activation patterns from several words are present at the same time. Computer models which extract meaningful information from large patterns of data are developed in the field of research known as "machine learning", also often referred to as "data science." Andy has expertise that spans all the required domains: computational models of the meanings of words, machine learning, and brain imaging.

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Based in Reston, VA, Intelligize provides a leading analytics solution enabling legal, academic and business professionals to efficiently mine data and insights from SEC filings, M&A contracts, transactional agreements and corporate governance documents. Intelligize delivers documents and data analytics by leveraging advanced natural language processing and machine learning technology applied to the vast data contained within SEC and other related databases. By building or acquiring solutions that deliver advanced natural language processing and machine learning technologies, LexisNexis helps professionals work more efficiently, make more informed decisions and drive success for their clients, practice and business. About LexisNexis Legal & Professional LexisNexis Legal & Professional is a leading global provider of content and technology solutions that enable professionals in legal, corporate, tax, government, academic and non-profit organizations to make informed decisions and achieve better business outcomes.

Outlier Detection Gets a Makeover - Surprise Discovery in Scientific Big Data - Statistics Views


For such projects, various measures of interestingness in large databases and in high-rate data streams are needed for rapid detection and characterization of the most interesting and potentially most important events (i.e., changes, anomalies, novelties). Such discoveries will span the full spectrum of statistics: from rare one-in-a-billion (or one-in-a-trillion) type objects, to the complete statistical and astrophysical specification of a class of objects (based upon millions of instances of the class). It will monitor the sky, measuring hundreds of parameters for billions of objects repeatedly for 10 years. The final image archive will be 100-200 PB, and the final LSST astronomical object catalog ( object-attribute database, representing time series for 50 billion objects) is expected to be 20-40 PB, comprising over 200 attributes for each one of the 20 trillion independent source observations.

Forget single platform iMessage: Google releases Allo smart messaging app for Android and iOS


The predominant messaging app on iOS is iMessage and its easy for Apple to focus on this single app. In addition to text messages, Allo supports sending resized text, emojis, photos, and sketches. These functions look similar to the new iOS 10 iMessage app, but remember Allo works across Android and iOS. The Google Assistant takes the power of Google Now and Google Search and brings in a personal touch where you can interact with Google Assistant as it offers suggestions in chats, answers questions you may have about anything, and works to serve as your personal assistant.

Google launches Allo smart messaging app for Android and iOS


Google today launched Google Allo, a messaging app for Android and iOS with Smart Reply and Google Assistant. Instead, you can opt to chat in Incognito mode (like Smart Reply was borrowed from Inbox, Incognito comes from Chrome). The logical way forward, assuming these new apps manage to gain decent traction, is to build Duo's video calling feature into Allo, with Knock Knock of course. Allo already lets you message through SMS with non-Allo Android users and even chat right via app preview messages through notifications, so just add Messenger's RCS functionality and you're good to go.