Shamayita Acharya

DataRobot of Boston has raised approximately $200M in a Series E funding round to help accelerate development of its automated machine learning and AI software, according to a recent report in xconomy.  That makes the company’s total venture funding over $400 million. The company is now in “unicorn” territory with a valuation over $1 billion.  DataRobot was founded in 2012 by data scientists from Travelers casualty insurance. CEO Jeremy Achin had been director of research and modeling at Travelers; DataRobot co-founder Tom de Godoy, now the firm’s CTO, was senior director of research and modeling for Travelers. The DataRobot platforms aims to automate data science functions enterprises and aggressively pursuing. In banking, for example, the software could be used to automatically assess credit default risk and track fraudulent transactions. In healthcare, it could be used to estimate hospital readmission risk. Read the source article at xconomy. from AI Trends https...

A growing range of fields and general advancements in technologies push programming languages to constant improvement and adaptation to the present-day needs. Now we have a bunch of languages serving different purposes: some of them emerged as an independent project, while others bud off from established and well-known languages. The colossus of Java, for example, has a number of offspring; some of them have proved to be a success. One of them, Kotlin, was backed by Google as the official language for Android development in 2017 and was reported to be the second most loved and wanted a programming language in 2018 Stack OverFlow survey and remains in Top 5 in this year’s survey. Another successful member of Java-based languages is Groovy that is gaining popularity among developers. At the same time, the 2018 Stack OverFlow survey listed Groovy among the most dreaded languages. In this setting, it seems unfair to compare the languages, but let’s see whether Groovy is so dreadful compa...

Cybersecurity in the healthcare sector presents an ongoing challenge for industry professionals. Hacking incidents have increased at a steady rate since 2016, and the spike between 2017 and 2018 was startling on its own. The total number of exposed records nearly tripled from 5,579,438 to 15,085,302. As these cyberattacks continue to jeopardize the personal information of patients, the subject of cybersecurity has received greater attention. Professionals in health information management have taken on more responsibilities, shifting in their role as they work in coordination with their organization's IT department. Unfortunately, we have few simple solutions to the problem. Cybercriminals grow more sophisticated with each passing year, refining their former techniques as they adapt and improve. They've developed new methods to bypass the security of modern organizations and collect the sensitive data of vulnerable people. As context, we've seen more than one breach pe...

The customer journey is incredibly complex today - thanks to rapid technological advancement. Our digitally-focused culture allows businesses to connect with their customers through more channels than ever before. But, it also makes it even more challenging to optimize and determine which methods are driving in the best results. In order to figure out which specific marketing campaigns are delivering the best results in terms of lead generation and conversions, an attribution model is often used to track links and other marketing tools to record interactions. However, when it comes to mobile marketing, the traditional attribution approach is not always perfectly accurate. The reason why mobile attribution is a totally different ballgame than traditional marketing attribution is because of its complexity. It is far easier to track a customer’s journey on a desktop version of a website by using cookies, image tags, and customized URL parameters. However, this is far more complicated ...

By Lance Eliot, the AI Trends Insider Taxes seem to be the bane of our existence. Whenever a new technology or innovation appears, one of the questions that inevitably gets raised is whether or not to tax it (the answer usually is yes) and how to do so. Consider for example the advent of online retailing, which has increasingly become a favored way for people to shop and seems to inexorably be undercutting storefront retailers. On the taxes side of things, a now famous U.S. Supreme Court case seemed to settle a thorny question about taxes as it relates to online retailers (a case pitting South Dakota versus Wayfair Inc.). The United States Supreme Court ruled that online retailers would henceforth be required to collect sales taxes in states for which those online firms have no actual physical presence, assuming that the respective state wants those retailers to collect such taxes (yes, most states if not all will – it is essentially “free” revenue for the state). Brick-and-mort...

From its presence in our daily apps to larger business applications, AI impacts our everyday lives in varying degrees — even if we’re not always aware of it. In the field of business intelligence, however, AI has a more visible impact. Business professionals are aware of the changing nature of business intelligence, largely due to the disruption caused by AI. As stated in an article on GoodData, “Artificial intelligence in business intelligence helps democratize data and improve analytics adoption. Radical advances in computing power, predictive analytics, machine learning, and AI have opened the door to a new generation of BI tools.” Today, traditional analytics as a component of business intelligence is becoming a thing of the past. The way forward seems to be rooted in AI applications. Here, we will explore how AI is changing the nature of business intelligence processes, and what these changes mean for us as humans. AI and Business Intelligence Data analysis, namely prescript...

Sponsored by: For senior leaders, managing data science is crucial to gain the most benefit from investments in AI and data analytics. Effective management involves people, culture, technology, and process. In this episode of CXOTalk, industry analyst, Michael Krigsman, interviews a top data scientist and business leader, who shares advice on how to create and manage a data science team. Dr. Bülent Kiziltan  is an AI executive and an accomplished scientist who uses artificial intelligence to create value in many business verticals and tackles diverse problems in disciplines ranging from the financial industry, healthcare,  astrophysics , operations research, marketing, biology, engineering, hardware design, digital platforms, to art. He has worked at Harvard, NASA and MIT in close collaboration with pioneers of their respective fields. In the past 15+ years he has led data driven efforts in R&D and built multifaceted strategies for the industry. He has been a data scien...

Sponsored by: Artificial intelligence offers the promise of better health, faster drug discovery and testing, to create improved medical outcomes for patients. We talk with a world expert on using AI in life sciences to discover and develop drugs faster and less expensively. Dr. Alex Zhavoronkov  is the founder and CEO of  Insilico Medicine , a leader in the next-generation artificial intelligence for drug discovery, biomarker development, and aging research. Prior to Insilico, he worked in senior roles at ATI Technologies, NeuroG Neuroinformatics, the Biogerontology Research Foundation and YLabs.AI. Since 2012 he published over 130 peer-reviewed research papers and 2 books. For six years in a row, he has organized the annual Aging Research for Drug Discovery and Artificial Intelligence for Healthcare forums at Basel Life/EMBO in Basel. Alex is an adjunct professor at the Buck Institute for Research on Aging. TRANSCRIPT Michael Krigsman: Artificial in...