Most of the economists and social scientists are concerned about the automation that is taking over the manufacturing and commercial processes. If the digitalization and automation continue to grow at the same pace it is currently happening, there is a high probability of machines partly replacing humans in the workforce. We are seeing some examples of the phenomena in our world today, but it is predicted to be far more prominent in the future. However, Dynes says, “Data scientists are providing solutions to intricate and complex problems confronted by various sectors today. They are utilizing useful information from data analysis to understand and fix things. Data science is an input and the output is yielded in the form of automation. Machines automate, but humans provide the necessary input to get the desired output.”
Most people seem a bit intimidated or confused by machine learning. What is it? Where is it going? Can I have some money now please? All valid questions. The truth is, you’ve been training machine learning models for years now, probably without realizing it. Do you use an iPhone or Apple photos? Or how about Facebook? You know how it shows you a group of faces and asks you to identify them? Well, by tagging those photos, you are training a facial recognition model to identify new faces. Congratulations, you can now say you have experience training machine learning models! But before you do, read these machine learning basics so you can accurately answer any follow up question.
The problem, naturally, is that a huge chunk of the world's economy hinges on the production of phones, TVs, tablets, and all those other things that Facebook thinks could be replaced with this technology. Even Zuckerberg acknowledges it's a long road ahead. That said, this Camera Effects platform, should it succeed in attracting a bunch of users, could go down as a savvy move. The apps that are built for the Facebook Camera today could wind up as the first versions of the apps you'd use with those glasses. In the short term, Facebook's play for augmented reality is going to look a lot like competing with Snapchat — and in a meaningful way, it is. Facebook needs developer and user love, so it needs to keep offering fun and funny tools to keep people from moving away from using its apps.
“The big breakthrough over the last ten years has been deep learning but I think we’ve done that now,” he argues. “People are of course writing more papers than ever about it. But it’s entering a more mature phase where at least in terms of using deep learning. We can absolutely do it. But in terms of understanding deep learning — the fundamental mathematics of it — that’s another matter.” “But the hunger, the appetite of companies and universities for trained talent is absolutely prodigious at the moment — and I am sure we are going to need to do more,” he adds, on education and expertise. Returning to the question of tech giants dominating AI research he points out that many of these companies are making public toolkits available, such as Google, Amazon and Microsoft have done, to help drive activity across a wider AI ecosystem.
Today using Big Data analytics companies and isolate which web pages, IVR logic paths, and customer service agents are starting snowballs and which web pages, IVR logic paths, and customer service agents are successfully resolving them, or melting them; these analytics also spotlight which issues or reasons are not resolved the first time and result in snowballs. Digging into the root causes of both of these areas produces improvements in processes that can help to Eliminate many thorny issues. In addition, analytics and machine learning can help to predict that there might be a snowball, and recommend how to address that customer in that moment in order to prevent a repeat contact from happening. As with the predictive models that I described earlier this forms a much stronger engine – either automated or human provided – that in turns delivers a combination of Best Service is No Serviceand Me2B success.
Ethics also deserves more attention at every educational level. AI technologies face ethical dilemmas all the time — for example, how to exclude racial, ethnic, and gender prejudices from automated decisions; how a self-driving car balances the lives of its occupants with those of pedestrians, etc. — and we need people and programmers who can make well-thought-out contributions to those decision making processes. We’re not obsessed about teaching coding at the elementary levels. It’s fine to do so, especially if the kids enjoy it, and languages such as Snap! and Scratch are useful. But coding is something kids can pick up later on in their education. However, the notion that you don’t need to worry at all about learning to program is misguided. With the world becoming increasingly digital, computer science is as vital in the arts and sciences as writing and math are.
The shell is your friend. But many developers don’t really know the shell, the Unix or Linux command-line environment available in several operating systems. (Bash is the best known, but there are others.) Some of you, when you transitioned from Windows to Mac, took your (slow) clickety habits with you, not realizing that the power laid in that app called Terminal hidden under Applications somewhere. Some of you have been shelling into “the server” to tweak a setting or two without realizing that you could automate your life away without even cracking a devops tool. Whatever brought you to the shell, chances are you’re not using it to its full advantage. Here are my top nine tricks for doing so
Overall mobile adoption among Americans remains relatively low — 31 percent for banking and 17 percent for credit cards, according to J.D. Power. It’s not surprising that card apps are used less, because they’re typically limited to providing balances, payment due dates and loyalty points. Online banking adoption, by contrast, is 80 percent. “Eight out of 10 are comfortable doing their banking electronically, and mobile offers them a more convenient alternative to that, and they have the phone to do it, but they’re still not comfortable with it, particularly older customers,” Neuhaus said. Because 80 percent of Americans have smartphones, “there’s a big pool of potential mobile banking users that have not gotten comfortable with it or have not seen the value yet in making that move,” Neuhaus said.
If someone claims an application, a service, or a machine is smart, you’re almost certainly getting snowed. Of course, people will use the word “smart” as a shortcut to mean “more capable logic,” a phrase that won’t sell anything. But if they don’t explain what “smart” means specific to their offering, you know they think you’re dumb. The fact is that most technologies labeled “smart” are not smart, merely savvy. The difference is that smart requires intelligence and cognition, whereas savvy requires only information and the ability to take advantage of it (it’s no accident that “savvy” come from the French word for “to know”). A savvy app or robot is a good thing, but it’s still not smart. We’re simply not there yet. bEven IBM’s vaunted Watson is not smart. It is savvy, it is very fast, and it can learn.
Many SMBs don’t understand the extent to which their data is at risk, and those who do often don’t know where to start in addressing this problem. In 2015, the U.K. government issued a press release suggesting that businesses need to plan for a cyberattacks. The research revealed that as many as 90% of big businesses and 74% of SMBs had experienced an information-security breach. It’s understandable, then, that a large proportion of small-business owners don’t pay the danger much attention, perhaps failing to realize that something as innocent as a social-media post or a USB stick left in the wrong place can be enough to bring down their whole organization. If you’re in this group, you should start reviewing the risks and putting security procedures in place. This guide gives you a starting point, with five steps you can implement right away to improve the safety of your company.
Quote for the day:
"A good leader can't get too far ahead of his followers" -- Franklin D. Roosevelt