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.

Computers. They’re a part of our everyday lives. Most of us couldn’t imagine living a day without them. We use them for school, work, and fun and use them to stay connected to those we love and care about. Since the invention of the web cam, millions of us use webcams to communicate with loved-ones and business contacts far away.

Web camera use has leveled the playing field for business entrepreneurs and given teenagers a fun way to chat with friends. However, solid citizens aren’t the only ones who make use of this popular modern technology. Recently, there have been reports of criminals using a type of webcam spy hack to insert themselves unseen into the living rooms and bedrooms of millions of unsuspecting users.

The Webcam Spy Hack

The most popular way criminals gain access to your webcam is through innocent-looking emails. You may receive an e-card from someone in your contacts list. When you click on it, you’re directed to another website to view the e-card. While you’re listening to music and watching animated puppies scroll across the screen, a Trojan horse is silently installed into your computer’s hard drive.

The job market is extremely tight these days, with several qualified workers being available for each empty position. That means that should you find yourself looking for work, for whatever reason, you need to make sure your interview skills are up to snuff. We will be taking a look at a variety of different tips that will help ensure your success during the interview process, including how to make sure your employers know about your C training experience. Here are some others:

• Do your own research in advance – Before you even step through the doorway to initiate the application process with a company, you should already know quite a bit about it. Investigate the corporate culture, speak with contacts who have experience with the firm, or search online; however you do it, having as much information as possible can really help you get an advantage during the hiring process. If you have specific experience, such as C training, that is of exceptional value to the firm you are applying to you can market yourself more effectively to the hiring agent.
• Dress Appropriately – In a perfect world, programming skill and experience such as C training should be the only factors in consideration when looking at a prospective hire; in real life this is often not the case. Don’t miss out because you gave a bad impression to someone, and strive to look your absolute best during your job interview. It is unfortunate, but the IT industry in particular tends to have a reputation for lacking in this department, so breaking the mold can be of great benefit to you.
• Be ready to interview at all times – You may be surprised how often job candidates are asked to participate in an off-the-cuff phone interview on the spot. Same-day in person interviews also are rising in popularity. Make sure you are always able to respond quickly if these situations come up and you get a fast interview. Memorize a few points in advance you can use to pump yourself up, such as an anecdote about your C training or other particular skills you may possess.

Job interviews are notoriously stressful for many people. Using simple tips like these can help you to prepare in advance for situations you may encounter during the interview process, and help you ultimately secure that new job. Make sure to emphasize whatever makes you special as an individual, such as your extensive C training.

I remember the day like it was yesterday. Pac Man had finally arrived on the Atari 2600.  It was a clear and sunny day, but it was slightly brisk. My dad drove us down to the video store about three miles from our Michigan house. If I remember correctly, the price for the game was $24.99.  It was quite expensive for the day, probably equaling a $70 game in today’s market, but it was mine. There *was* no question about it. If you purchase a game, it’s your game… right?

You couldn’t be more wrong.  With all the licensing agreements in games today, you only purchase the right to play it. You don’t actually “own” the game. 

Today, game designers want total control over the money that comes in for a game. They add in clauses that keep the game from being resold, rented, borrowed, copied, etc. All of the content in the game, including the items you find that are specifically for you, are owned by the software developer. Why, you ask, do they do this? It’s all about the money.

This need for greed started years ago, when people started modifying current games on the market. One of the first games like this was Doom. There were so many third part mods made, but because of licensing agreement, none of these versions were available for resale. The end user, or you, had to purchase Doom before they could even install the mod.  None of these “modders” were allowed to make any money off their creation.