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.

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.”

1. The IRS is enabling taxpayers to download their tax transcripts over the internet from the Internal Revenue Service. The official secure URL for the transcripts download followed immediately after The White House fact sheet confirmed the decision. According to the Tech Crunch You Can Now Download Your Tax Returns From The IRS  article, there are some minor bug issues when registering. Given that security has long been problematic with the IRS, the best course of action for the public is to take some precautions when downloading personal information on mobile devices, pc’s and laptops. Installing disk encryption software on all your devices will protect your files reduce risk
2. Have an awesome Start-Up with products in ‘stealth or private beta” that you want like to pitch for a chance to get a table at Disrupt NY? TechCrunch is heading to Atlanta and New Orleans February 18^th and 20^th 2014 and will host a beer fest night in exchange for your thoughts and pitches. Tickets are $5, and all entrepreneurs, investors, dreamers or tech enthusiast are welcome.
3. Cloutex, a cloud computing future enabler has just secured their first round of seed funding.  Cloutex is an Estonian tech startup, which connects and syncs various web applications such as e-marketing, CRM and accounting tools under one convenient hub. The United Partners, SmartCap and EstBan business angels seeded the start-up with $6000, 000.
4. Could you get everything important that you need to know about living successfully from a computer program? Ryan Dube seems to think so. In his 6 Life Habits That Programming Could Teach You Today  he speaks in flow charts, loops and program modules, in the same breath as paying off debt or buying a house.  How can your programming skills help in life skills by modeling some of the same principles?
5. 10 Incredibly Simple Things You Can Do To Protect Your PrivacyPassword protect your devices.  Put alerts on your name in Google; simple tasks that can be significant in protecting your privacy.
6. Adobe Brings 3D Printing Support to PhotoshopAmong the latest updates in Adobe, Photoshop users have the ability to design 3D models from scratch as well as being able to toy around with color, shape and angles.

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?