There's been a lot of hand-wringing about artificial intelligence and robots taking away jobs--by one recent estimate, AI could replace up to six percent of jobs in the U.S. by 2021. While most of those will be in customer service and transportation, a recent study suggests that at least one job requiring highly skilled labor could also be getting some help from AI: dermatologist. Susan Scutti at CNN reports that researchers at Stanford used a deep learning algorithm developed by Google to diagnose skin cancer. The team taught the algorithm to sort images and recognize patterns by feeding it images of everyday objects over the course of a week. "We taught it with cats and dogs and tables and chairs and all sorts of normal everyday objects," Andre Esteva, lead author on the article published this week in the journal Nature, tells Scutti. "We used a massive data set of well over a million images."

Sage has integrated its Pegg chat bot with Sage One, adding artificial intelligence technology to the company's cloud-based accounting software. The U.K.-based company is launching the capability in the U.S. first before marketing it in other countries. Sage showed off the technology last year during its Sage Summit conference in Chicago (see Accounting bot launched at Sage Summit). The bot, developed in collaboration with Gupshup, a San Francisco-based developer, uses AI technology to provide a "virtual accounting assistant." Pegg allows users to submit expenses and track receipts, and see who is late on paying an invoice, via mobile messaging apps such as Facebook Messenger and Slack. According to Sage, 20,000 customers in 110 countries have already begun using Pegg as early adopters since it launched six months ago.

As many jobs are disappearing to automation, the latest profession to also start seeing the future may be dermatology. Stanford University researchers have developed a deep convolutional neural network, an artificial intelligence technique for building a knowledge set, to learn how to spot suspect cancer lesions. Today this process is manual and prone to errors of subjectivity. Dermatologists simply look through a dermatoscope and judge based on their education and experience. The Stanford system was given 130,000 images of skin lesions simply labeled with previously established diagnoses that included more than 2,000 diseases.

Since everyone seems to be talking about the hottest trend -- artificial intelligence and machine learning -- broadly, 62 percent of large enterprises will be using AI technologies by 2018, says a report from Narrative Science. But why AI is considered to be the next big technology? Because it can enhance and change everything about the way we think, interact, manufacture and deliver. Last year, we saw a significant number of high-profile hacks targeting big organizations, governments, small enterprises, and individuals -- What's more worrisome? It's going to get worse, and we need help.

A constant presence on Google Play and the App Store's top apps charts, it's one of the first apps you'll download when you buy a new phone and almost certainly your biggest source of notification on a typical day. The app has developed dramatically since it emerged almost a decade ago, picking up the ability to transfer files and make voice and video calls – all now core features – along the way. More useful than SMS, slicker than Hangouts and easier to use than Skype, it's no wonder WhatsApp is the number one communications service of choice for hundreds of millions of smartphone users. Even if you use it on a daily basis, WhatsApp is packed with lots of handy, little-known features you might not be familiar with. We've rounded up the best.

Anyone who uses Twitter knows that it can be home to very hostile exchanges, some of which may even constitute cyberbullying. In a world where that kind of danger is a mere click away, what can parents do to keep their children safe without monitoring their every digital move? Analytics and machine learning are offering new options. Bark CEO Brian Bason founded his company after having a couple of kids of his own and finding himself concerned about online safety. Bark offers a machine learning-backed app and service to help parents work together with their children to navigate the dangers of today's digital world.

In this document, we are going to focus specifically on how to use the machine learning capability of Falcon Host to prevent malware. Machine Learning allows Falcon Host to protect against known and unknown malware without using signatures. As a reminder, Falcon Host uses multiple methods to prevent and detect malware. Those methods include Machine Learning, but also exploit blocking, blacklisting and indicators of attack. Once in the App, the default page is the Prevention Policy.

Could 2017 be any more turbulent than 2016? Some would argue that because of this year's unprecedented surprises, fluctuating markets & politics and real-world events, next year couldn't possibly offer any more shocks. In the midst of all of this, the technology world continues unabated, with the FinTech sector holding some exciting new developments for the year ahead. For too long, consumers have had to bear the "Your call is very important to us, please continue to hold" banality, but 2017 could be the year where this unintelligent automation disappears. The advances in Artificial Intelligence have caused a small explosion of sorts in the FinTech sector, but this small bang could expand with the mainstream introduction of chatbots and smartbots, with human help only required for the really tricky questions.

"Nanodegree" is a registered trademark of Udacity. Udacity is not an accredited university and we don't confer traditional degrees. Udacity Nanodegree programs represent collaborations with our industry partners who help us develop our content and who hire many of our program graduates.

This configuration is typically called Level 1 Cache, as it contains one level of cache only. Level 1 caches are normally used for Session and Application state management. Although effective, this approach is not optimal when dealing with applications that move large quantities of data over multiple geographies, which is the scenario that we want to optimise. First of all, large data requires large cache to be effective, which in turn is memory intensive, thus requiring expensive servers with a big allocation of volatile memory. In addition, syncing nodes across regions implies large data transfers, which, again, is expensive and introduces delays in availability of the information in the subordinate nodes.