Recently, I asked my friend, Ray, to list those he believes are the top 10 most forward thinkers in the IT industry.  Below is the list he generated. 

Like most smart people, Ray gets his information from institutions such as the New York Times, the Wall Street Journal, the Huffington Post, Ted Talks ...  Ray is not an IT expert; he is, however, a marketer: the type that has an opinion on everything and is all too willing to share it.  Unfortunately, many of his opinions are based upon the writings/editorials of those attempting to appeal to the reading level of an 8th grader.  I suppose it could be worse.  He could be referencing Yahoo News, where important stories get priority placement such as when the voluptuous Kate Upton holds a computer close to her breasts.

Before you read further, note that missing from this list and not credited are innovators: Bill Joy, Dennis Ritchie, Linus Torvalds, Alan Turing, Edward Howard Armstrong, Peter Andreas Grunberg and Albert Fent, Gottfried Wilhelm Leibniz/Hermann Grassmann ... You know the type:  the type of individual who burns the midnight oil and rarely, if ever, guffaws over their discoveries or achievements.

I will begin our blog on Java Tutorial with an incredibly important aspect of java development:  memory management.  The importance of this topic should not be minimized as an application's performance and footprint size are at stake.

From the outset, the Java Virtual Machine (JVM) manages memory via a mechanism known as Garbage Collection (GC).  The Garbage collector

• Manages the heap memory.   All obects are stored on the heap; therefore, all objects are managed.  The keyword, new, allocates the requisite memory to instantiate an object and places the newly allocated memory on the heap.  This object is marked as live until it is no longer being reference.
• Deallocates or reclaims those objects that are no longer being referened. 
• Traditionally, employs a Mark and Sweep algorithm.  In the mark phase, the collector identifies which objects are still alive.  The sweep phase identifies objects that are no longer alive.
• Deallocates the memory of objects that are not marked as live.
• Is automatically run by the JVM and not explicitely called by the Java developer.  Unlike languages such as C++, the Java developer has no explict control over memory management.
• Does not manage the stack.  Local primitive types and local object references are not managed by the GC.

So if the Java developer has no control over memory management, why even worry about the GC?  It turns out that memory management is an integral part of an application's performance, all things being equal.  The more memory that is required for the application to run, the greater the likelihood that computational efficiency suffers. To that end, the developer has to take into account the amount of memory being allocated when writing code.  This translates into the amount of heap memory being consumed.

Memory is split into two types:  stack and heap.  Stack memory is memory set aside for a thread of execution e.g. a function.  When a function is called, a block of memory is reserved for those variables local to the function, provided that they are either a type of Java primitive or an object reference.  Upon runtime completion of the function call, the reserved memory block is now available for the next thread of execution.  Heap memory, on the otherhand, is dynamically allocated.  That is, there is no set pattern for allocating or deallocating this memory.  Therefore, keeping track or managing this type of memory is a complicated process. In Java, such memory is allocated when instantiating an object:

String s = new String();  // new operator being employed
String m = "A String";    /* object instantiated by the JVM and then being set to a value.  The JVM
calls the new operator */

The interpreted programming language Python has surged in popularity in recent years. Long beloved by system administrators and others who had good use for the way it made routine tasks easy to automate, it has gained traction in other sectors as well. In particular, it has become one of the most-used tools in the discipline of numerical computing and analysis. Being put to use for such heavy lifting has endowed the language with a great selection of powerful libraries and other tools that make it even more flexible. One upshot of this development has been that sophisticated business analysts have also come to see the language as a valuable tool for those own data analysis needs.

Greatly appreciated for its simplicity and elegance of syntax, Python makes an excellent first programming language for previously non-technical people. Many business analysts, in fact, have had success growing their skill sets in this way thanks to the language's tractability. Long beloved by specialized data scientists, the iPython interactive computing environment has also attracted great attention within the business analyst’s community. Its instant feedback and visualization options have made it easy for many analysts to become skilled Python programmers while doing valuable work along the way.

Using iPython and appropriate notebooks for it, for example, business analysts can easily make interactive use of such tools as cohort analysis and pivot tables. iPython makes it easy to benefit from real-time, interactive researches which produce immediately visible results, including charts and graphs suitable for use in other contexts. Through becoming familiar with this powerful interactive application, business analysts are also exposing themselves in a natural and productive way to the Python programming language itself.

Gaining proficiency with this language opens up further possibilities. While interactive analytic techniques are of great use to many business analysts, being able to create fully functioning, independent programs is of similar value. Becoming comfortable with Python allows analysts to tackle and plumb even larger data sets than would be possible through an interactive approach, as results can be allowed to accumulate over hours and days of processing time.

This ability can sometime allow business analysts to address the so-called "Big Data" questions that can otherwise seem the sole province of specialized data scientists. More important than this higher level of independence, perhaps, is the fact that this increased facility with data analysis and handling allows analysts to communicate more effectively with such stakeholders. Through learning a programming language which allows them to begin making independent inroads into such areas, business analysts gain a better perspective on these specialized domains, and this allows them to function as even more effective intermediaries.

Related:

Who Are the Main Players in Big Data?

The innovators in technology have long paved the way for greater social advancement. No one can dispute the fact that the impact of Bill Gates and Microsoft will be far reaching for many years to come. The question is whether or not Microsoft will be able to adapt and thrive in emerging markets. The fact that Microsoft enjoys four decades of establishment also makes it difficult to make major changes without alienating the 1.5 billion Windows users.

This was apparent with the release of Windows 8. Windows users had come to expect a certain amount of consistency from their applications. The Metro tile, touch screen interface left a lot to be desired for enough people that Microsoft eventually more thoroughly implemented an older desktop view minus a traditional Start menu.

The app focused Windows 8 was supposed to be a step towards a greater integration of Cloud technology. In recent years, Microsoft lagged behind its competitors in getting established in new technologies. That includes the billions of dollars the emerging mobile market offered and Cloud computing.

Amazon was the first powerhouse to really establish themselves in the Cloud technology market. Google, Microsoft, and smaller parties are all playing catch up to take a piece of the Cloud pie. More and more businesses are embracing Cloud technology as a way to minimize their equipment and software expenses. While it does take a bit for older businesses to get onboard with such a change, start ups are looking at Cloud computing as an essential part of their business.

But what does that mean for Microsoft? Decisions were made to help update the four decade old Microsoft to the "always on" world we currently live in. Instead of operating in project "silos", different departments were brought together under more generalized headings where they could work closer with one another. Electronic delivery of software, including through Cloud tech, puts Microsoft in the position of needing to meet a pace that is very different from Gates’ early days.

The seriousness of their desire to compete with the likes of Amazon is their pricing matching on Cloud infrastructure services. Microsoft is not a company that has traditionally offered price cuts to compete with others. The fact that they have greatly reduced rates on getting infrastructure set up paves the way for more business users of their Cloud-based apps like Microsoft Office. Inexpensive solutions and free applications open the doors for Microsoft to initiate more sales of other products to their clients.

Former CEO Steve Ballmer recognized there was a need for Microsoft to change directions to remain competitive. In February 2014, he stepped down as CEO stating that the CEO needed to be there through all stages of Microsoft's transition in these more competitive markets. And the former role of his chosen successor, Mr. Satya Nadella? Head of Microsoft's Cloud services division.

Microsoft may not always catch the initial burst of a new development in their space; but they regularly adapt and drive forward. The leadership of Microsoft is clearly thinking forward in what they want to accomplish as sales of PCs have stayed on a continuous decline. It should come as no surprise that Microsoft will embrace this new direction and push towards a greater market share against the likes of Amazon and Google.

Related:

Who Are the Main Players in Big Data?

Is Cloud Computing Safe for Your Business?

Is The Grass Greener in Mobile App Development?