Microsoft Shifts from “A PC on every Desktop” to “Deep Learning in Every Software”

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The Machine Learning Age is the New PC Age.

“ A PC on every Desktop” has been Microsoft’s goal ever since Bill Gates started the company in 1975. That was when the idea of a personalised information machine was far too extravagant to be taken seriously. Especially since computers at the time were clunky and expensive.

It was only until the 1980s when computers really began to take off with the introduction of the Commodore 64. In addition to its relatively low cost $400 USD price tag, it came with 64kB of RAM. The specs coupled with the price of the machine rivalled all other previous models making the specs and price the mains selling points.

As time went on though, other companies started to produce more inexpensive machines:

Amiga 500 with Color Monitor $849 New York 1988
Daisy Wheel Printer $289.00 New York 1988
IBM PC $895 New York 1988
Logitech Mouse $89.99 New York 1988
PC 30 mb Hard Disc with monitor 512k memory $1,249 New York 1988
Star NX 1000 Printer $189 New York 1988
Tandy 1000 Computer and Monitor $999 Ohio 1985
TRS 80 PC1 $149.95 Maryland 1982
-The People History

but none of which could match the specs of the Commodore. Even so, with the advent of the computer age, Microsoft was finally starting to deliver on that promise of a “PC on every desk”. Now, most of the world in 2016 has access to a computer device of some sort whether a desktop, laptop, phone or tablet.

So, with Bill Gates’ initial goal nearing completion, many wondered what was next?

Artificial Intelligence (AI) and Machine/Deep Learning

As we begin to close of 2016 and usher in a new year, machine learning will start to play a more prominent role in the apps we use, the devices we have and the world around us.

There are many examples to illustrate just that:

1.) The new Google Pixel Phone had to be constructed and programmed by Google in order to have full control over the new AI functionality they installed.

2.) Google funding a AI Research Group in Montreal

3.) Microsoft’s AI Twitter dilemma

4.) Facebook investing heavily in Artificial research by opening up a new division called FAIR.

5.) Tesla’s Self -Driving AI cars

6.) Google Translate and Google Play Music Updates using Machine Learning

7.) Google Alpha Go Winning Go Matches

The above are just a few examples of how AI is already taking over the tech ecosystem. We will expect much more advancement next year and in the years to come. Especially as companies such as Microsoft star to offer open source toolkits for free.