Disruptive technologies such as hand-held devices, cloud computing and social media are rattling the foundations upon which traditional businesses are built. Enterprise customers have grown smarter at ensuring the latest technological trends work in their favor. Everyone is trying to zero in on their core competencies by employing commodity services to run their business.

Likewise, enterprise application vendors need to zero in on their core competencies and enhance more value to the businesses of their clientele by leveraging standards-based commodity services, such as IaaS and PaaS, provided by leaders in those segments (e.g. Amazon EC2, Google Cloud Platform etc.).

What else enterprises need to do is learn to adopt new and emerging technologies such as cloud, utility and social computing to build on them to penetrate new market avenues.

New small and medium-sized entrants into the market are constantly challenging enterprises given their ability to rapidly turnaround and address the requirements of the customers in a cost-effective manner. Additionally, these new advancements also affect how enterprises create, deploy, and manage solutions and applications. If you take the example of Force.com, for instance, you find that it’s a common war zone for enterprise application vendors to furnish SME markets with their applications, with the new entrants mostly having an edge.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

Many individuals are looking to break into a video game designing career, and it's no surprise. A $9 billion industry, the video game designing business has appeal to gamers and non-gamers alike. High salaries and high rates of job satisfaction are typical in the field.

In order to design video games, however, you need a certain skill set. Computer programming is first on the list. While games are made using almost all languages, the most popular programming language for video games is C++, because of its object-oriented nature and because it compiles to binary. The next most popular languages for games are C and Java, but others such as C# and assembly language are also used. A strong background in math is usually required to learn these languages. Individuals wishing to design games should also have an extensive knowledge of both PCs and Macs.

There are many colleges and universities that offer classes not only in programming but also classes specifically on game design. Some of these schools have alliances with game developing companies, leading to jobs for students upon graduation. Programming video games can be lucrative. The average game designer's salary is $62,500, with $55,000 at the low end and $85,000 at the high end.

Programmers are not the only individuals needed to make a video game, however. There are multiple career paths within the gaming industry, including specialists in audio, design, production, visual arts and business.

Designing a video game can be an long, expensive process. The average budget for a modern multiplatform video game is $18-$28 million, with some high-profile games costing as much as $40 million. Making the game, from conception to sale, can take several months to several years. Some games have taken a notoriously long time to make; for example, 3D Realms' Duke Nukem Forever was announced in April 1997 and did not make it to shelves until July 2011.

Video game programmers have a high level of job satisfaction. In a March 2013 survey conducted by Game Developer magazine, 29 percent of game programmers were very satisfied with their jobs, and 39 percent were somewhat satisfied.

If you're interested in a game development career, now's the time to get moving. Take advantage of the many online resources available regarding these careers and start learning right away.

Memory management is always a priority in pretty much any programming language you would want to use. In the lower level languages such as C, there are a number of functions which help you manage the memory your application uses, but they are not the easiest to use. Some of the more modern programming languages such as Python, Ruby, Perl, and of course the subject of this article, Javascript all have a built in feature called garbage collection.

Garbage collection essentially means that the languages compiler will automatically free the memory being occupied by unused variables and objects, but there is no telling when this could occur. It is purely down to the compiler to decide when the garbage collection process should be initiated.