The Zen of Python, by Tim Peters has been adopted by many as a model summary manual of python's philosophy.  Though these statements should be considered more as guideline and not mandatory rules, developers worldwide find the poem to be on a solid guiding ground.

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

The short answer is, yes and no. It depends upon who you are. The purpose of this entry is to help you determine, yes or no.

Full disclosure. This entry is created on a Mac mini. And doing so on Windows 8 (Release Preview). If you are a developer, in my humble opinion you need to test on all platforms you expect your app to run or you are not much of a developer.

To be successful you need to leave politics in geographical territory known as Washington DC. My definition of that is: 14 mi.² of real estate surrounded by reality.

Only in politics can we afford to take sides. Those of us in IT, especially developers need to do our best to be all things to all people. Certainly this is a technical impossibility. However in our game we can get some points for at least being serviceable if not outstanding.

Microsoft has now come up with a surface tablet to compete with the Apple iPad. The Surface is the known as the ‘iPad killer’ and ‘Microsoft iPad’. Microsoft has stuck to production of software till date but this is one of its latest hardware devices that is expected to take over the Apple iPad. This is a new challenge posed by Microsoft to Apple.

            The Microsoft Surface saw its official release on 19^th June in the city of Los Angeles. It has made a great first impression and seems to be beginning a new start in the competition between the best tablets in the international market. It has 10.6’’ screen and a magnetic cover that can be used as a keyboard and also as a kickstand in order to place the device upright on tables. There has been a paradigm shift in Microsoft’s policy when it decided to do away with the tile-based Metro theme for its Desktop that is almost a trademark with it.

            There are many features that make the Surface more like a laptop than like a tablet- the most prominent one being the built- in keyboard that will be useful for business customers. As Microsoft Surface employs Windows 8 as an operating system, which is also used in its computers and laptops, it will be a lot easier for customers to switch among their devices.

            The tablet was announced by Microsoft’s CEO, Steve Ballmer, in Los Angeles at a special press conference. It was hailed to be the first of an entirely new family of a number of devices being created and developed by the company. The Surface has a thickness of 9.3mm and weighs 1.5 pounds. It has a kickstand and keyboard for its cover. It is 0.1 mm thinner than the iPad 3, which is the latest iPad from Apple.

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.”