Information Technology

Data Virtualization: A Supermarket for Data


Here's an analogy using a concept that we can all relate to: a supermarket. Picture the scene: Shopping list in one hand, shopping basket in the other, you're ready to tackle your weekly shopping in your local supermarket. Your items range from fruit and vegetables to washing detergent, perhaps with some free-range eggs thrown in for good measure. Quite the eclectic mix, but you know that you'll be able to find all you need under one roof. The fact that this is possible is in itself quite remarkable.

Google's Waymo expands to Atlanta to test self-driving cars


Google-owned Waymo on Monday announced it will expand its test program of self-driving minivans to Atlanta. Google's self-driving cars involved in 11 crashes Google comes clean on the number of accidents its driverless cars have been in over the past six years. Waymo didn't detail when the rollout in Atlanta will begin or how many vehicles will be used for testing. "Now that we have the world's first fully self-driving vehicles on public roads in AZ, we're looking to take our tech to more cities," Waymo tweeted. According to The Verge, Google began mapping downtown Atlanta last week to have an accurate accurate 3D map for its self-driving fleet.

The Differences Between Machine Learning, Deep Learning & Prescriptive Analytics NetApp Blog


Digital transformation is the key imperative in the corporate suite of most forward-thinking enterprises. IDC coined the term Digital Darwinism to reflect the impact of digital transformation on businesses of all sizes and across industries. According to IDC, organizations are moving away from business as usual and embracing digital transformation to become more competitive. Key components of enacting digital transformation are the applied sciences of artificial intelligence, machine learning, deep learning, and prescriptive analytics, the creation of computational systems that allow autonomous decision making. Through prescriptive analytics, organizations will redefine how business decisions are made.

Neural Network and Machine Learning in a simple game


This post is about implementing a – quite basic – Neural Network that is able to play the game Tic-Tac-Toe. For sure there is not really a need for any Neural Network or Machine Learning model to implement a good – well, basically perfect – computer player for this game. This could be easily achieved by using a brute-force approach. But as this is the author's first excursion into the world of Machine Learning, opting for something simple seems to be a good idea. The motivation to start working on this post and the related project can be comprised in one word: AlphaGo.

The best metric to measure accuracy of classification models CleverTap


Unlike evaluating the accuracy of models that predict a continuous or discrete dependent variable like Linear Regression models, evaluating the accuracy of a classification model could be more complex and time-consuming. Before measuring the accuracy of classification models, an analyst would first measure its robustness with the help of metrics such as AIC-BIC, AUC-ROC, AUC- PR, Kolmogorov-Smirnov chart, etc. The next logical step is to measure its accuracy.

New AI System Predicts How Long Patients Will Live With Startling Accuracy


By using an artificially intelligent algorithm to predict patient mortality, a research team from Stanford University is hoping to improve the timing of end-of-life care for critically ill patients. In tests, the system proved eerily accurate, correctly predicting mortality outcomes in 90 percent of cases. But while the system is able to predict when a patient might die, it still cannot tell doctors how it came to its conclusion. Doctors must consider an array of complex factors, ranging from a patient's age and family history to their response to drugs and the nature of the affliction itself. To complicate matters, doctors have to contend with their own egos, biases, or an unconscious reluctance to assess a patient's prospects for what they are.

Artificial intelligence is as important as fire--and as dangerous, says Google boss


Google CEO Sundar Pichai believes artificial intelligence could have "more profound" implications for humanity than electricity or fire, according to recent comments. Pichai also warned that the development of artificial intelligence could pose as much risk as that of fire if its potential is not harnessed correctly. "AI is one of the most important things humanity is working on," Pichai said in an interview with MSNBC and Recode, set to air on Friday, January 26. "It's more profound than, I don't know, electricity or fire." Pichai went on to warn of the potential dangers associated with developing advanced AI, saying that developers need to learn to harness its benefits in the same way humanity did with fire.

2018 might be Amazon's year to take a leading role in online advertising


Andrew Keen is the author of three books: Cult of the Amateur, Digital Vertigo and The Internet Is Not The Answer. He produces Futurecast, and is the host of Keen On. Few people have a better overview of the tech economy than Sir Martin Sorrell, the co-founder and longtime CEO of the world's largest advertising company, WPP. With WPP's over 200,000 employees and a $75 billion media book, Sir Martin has a uniquely privileged insight into the future of the online advertising industry. And he believes that 2018 might be the year that a third company joins what he calls the Facebook/Google "duopoly" in online advertising and search.

AI and robots are displacing science and tech workers. The question is: How quickly?


There is little debate that there are huge benefits and risks to AI, both for agencies and their clients. Instead, industry discussions have now turned toward how to maintain the balance: embracing the day-to-day convenience machine intelligence can provide, while at the same time, walking the thin line of fear that society still feels for any kind of artificial intelligence. This unknown is the source of widespread industry debate, generating countless misconceptions along the way, the biggest of which is that AI is ready to replace humans to perform very complex tasks like UX or UI design. This is compounded by Adobe's recent launch of numerous AI-driven design and development tools. However, agencies have nothing to worry about yet and there a few important reasons why....