One of the most anticipated features that came on the iPhone 4S was a new thing called: Siri. Zooming out before concentrating on Siri, mobile assistants were the new rage. Beforehand, people were fascinated by the cloud, and how you could store your files in the Internet and retrieve it from anywhere. You could store your file at home, and get it at your workplace to make a presentation. However, next came virtual assistants. When you’re in the car, it’s hard to send text messages. It’s hard to call people. It’s hard to set reminders that just popped into your head onto your phone. Thus, came the virtual assistant: a new way to be able to talk to your phone to be able to do what you want it to do, and in this case, text message, or call people, and many other features. Apple jumped onto the bandwagon with the iPhone 4S and came out with the new feature: Siri, a virtual assistant that is tailored to assist you in your endeavours by your diction.

Getting started with Siri

To get Siri in the first place, you need an iPhone 4S; although you may have the latest updates on your iPhone 4 or earlier, having an iPhone 4S means you have the hardware that is required to run Siri on your phone. Therefore, if you are interested in using Siri, check into getting an iPhone 4S, as they are getting cheaper every single day.

IT jobs are without a doubt some of the highest paying jobs with information architects, data-security analysts and UX designers taking home $100,000 or more a year. But then again, these are high demand; high expertise jobs so don’t jump with joy as yet. But like every job and IT industry to be specific, not everyone commands such higher salaries. There are a large number of IT professionals who at some point of their career feel that their salaries have hit a standstill. Even if you are an IT professional and a great one at that, your technical expertise alone may not help you exceed the IT earning barrier. To continuously exceed your salaries, you need to work hard and smart. Here is how you can exceed the earning barrier in IT.

·         Gain Business Knowledge and Move Up The Management Ladder: IT departments for the most part are considered a part of “back office” operations. What this means is that despite being a core part of the business, IT professionals do not often get enough say in revenue generating components of the business and as a result seldom have a chance to take up senior management roles.  So if you do not want to stay content with a project manager or senior project management salary, invest time and money in gaining business knowledge. It could be through a formal business degree, online training courses or just by keeping your eyes and ears open while in the organization. Having the technical experience with business knowledge will instantly make you stand apart and open the doors for you to draw senior management salaries. For example, a survey conducted highlighted that CIOs were the biggest salary winners which clearly demonstrates the value of technical and business knowledge

·         Gain expertise on the “Hot” Technologies and Keep Learning: Say you are an expert in Java and draw a respectable salary in the industry. However, someone with less years of experience than you joins the organization and draws a higher salary than you! Why you ask. It could very well be because he/she is an expert in say big data technology such as Hadoop. Information Technology is one of the most dynamic industries with new technologies and languages coming up every now and then. When a new technology comes to the foray and gains traction, there is an instant demand-supply gap created which means that those with the specific skill sets are in a position to demand high salaries. If you have to break the IT earning barrier, always be ready to reinvent yourself by learning new technologies and this way you will be well positioned to jump on the high paying opportunities in the IT industry

·         Work On Your Own Side Projects: This one might seem controversial but let me clarify that I do not mean doing freelance work because even though your organization may never find out, it is ethically in breach of contract with your contract. If you have been lucky enough to be trained in some web based technologies such as Java, .NET or even HTML etc. spare sometime after office to build your own side projects. They could be very small projects tackling some problem that only you might have but there are multiple benefits of developing side projects. Worst case scenario, you will improve your technical skills. On the up side, you might end up creating your own business. A lot of technology start-ups were actually side projects the founders tinkered on with while they were employed full-time. You may not always succeed but there is no downside to the same

The future looks just as bright for information technology as it did ten years ago when this career field started growing in huge numbers due to major internet technological advances and the popularity of mobile devices such as the smartphone and eReaders like Amazon’s Kindle.  In classrooms and libraries across the nation, information technology has become instrumental in the way students learn and the way teachers give lessons, and thanks to online education more adults have access to a better education without incurring a lot of debt. Needles to say, the need for qualified workers in information technology will continue in times to come. Some of the technological careers that are rapidly growing in popularity in the last decade are a direct reflection of current trends.

Information Technology Managers

The information technology manager is responsible for handling all computer activities for a business and performs upgrades on computer software and hardware, installs new security features on computers, creates budgets and goals for the IT department, supervises other IT employees and troubleshoots computers when needed. According to the Bureau of Labor Statistics, there were 332,700 information technology management jobs filled in 2012 and a majority of these positions were in the computer systems sector. Most information technology managers hold a bachelor's degree in computer science or information technology, and a growing number of employers prefer a graduate degree. The job growth is expected to grow at 15% between now and 2022.

Mobile Application Developers

This job will grow by leaps and bounds as millions of people continue to purchase mobile devices and download apps for business and entertainment purposes. It creates expanded opportunities for those who want to become mobile application developers. A mobile application developer often works with other developers to create mobile-friendly apps or mobile-friendly versions of business websites for consumers. The developer may have his own firm or he may be employed with a larger company, and he will need to understand the basics of web design and different kinds of codes to succeed in this career. The Bureau of Labor Statistics states that the job growth is expected to be at 28% by 2020.

Health Information Technology

Another fast growing sector within information technology is health information technology and there are various jobs to choose from. You can work with health insurance providers and your duties would include processing patients' insurance claims and managing patients' insurance information using a computer database. Another option is to work as a medical biller in a doctor's office preparing patient’s invoices. The good thing about these jobs is that you do not need a four-year degree to get the training; you can obtain a two-year associates degree or a certificate in health information technology.

Search Engine Optimization Consultant

This is an important information technology career because most businesses have websites and if these websites are going to receive high traffic from visitors and earn profit, proper search engine optimization is necessary. The SEO consultant's job is to ensure that a business website gets high rankings on the major search engines and plenty of traffic from visitors. A good SEO consultant at a minimum will know how to research keywords effectively and implement these into the website's content based on the website's theme and he would utilize web analytics as part of the job. An SEO consultant may work on a freelance basis or be employed with an advertising company as an example.

Best Cities for Technology Careers

If you're thinking about relocating for your career, here are some of the best cities currently for information technology jobs listed in Forbes. 

Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.