The Cognitive Era

IBM’s CEO, Ginni Rometty declared this week that we are in the “Cognitive Era”.  According to IBM’s release, we are in a new era of technology, a new era of business, a new era of thinking. What does this all mean?  How can we apply it?

To give some context to the cognitive era we have to look at the business computer “eras” that have come before this.  The “Tabulation Era” was the first.  Calculating and accounting for all of the transactions that occurred were used by super computers to keep track of the statistics.  Issuing inventory was kept in a ledger, and then the data was entered into the GL systems for tracing and accounting.

The second era came with the advances in technology to automate processes, or the “Automation Era”.  Think of computer programming and the programs that combined multiple functions together.  ERP systems combined operations processes such as inventory issuance with accounting systems eliminating the need for multiple processes in order to record the transactions.  The system is “rules based” and rigid based on what was programmed.

That brings us to what is being described as the “Cognitive Era”.  Dictionary.com defines “Cognitive” as “relating to the mental processes of perception, memory, judgment and reasoning”.  So the “cognitive era” in our example means that the systems will use all of the information available to manage the supply chain of inventory as it is required based on cognition.  The difference here is that the computer “learns” the system, and makes decisions based on what it concludes, much like a human does. 

So, what does this mean for the new era?  According to IBM, 80% of all data is invisible to computers.  The data they are referring to is “unstructured data”, which are paragraphs of text.  The other 20% has been the subject of what they call “big data”, a term used for all of the massive amounts of data that is being created every time we turn on our smart phones, post a tweet on Twitter, or enter a credit card number for a purchase on Amazon.com.  Decisions across the globe are made every second based on analytics arising from the 20% of structured data that’s analyzed.  Combine these decision paths with the 80% of structured data into a system that “thinks” and you’ll get better outcomes to very difficult problems.

I was recently given a powerful example of the combination of structured and unstructured data in decision making that will change how quickly a company can respond to changing product demands.   In this scenario, a marketer searches keyword terms (unstructured data) on a popular upcoming kid’s movie across all social media.  The keywords are analyzed by the system in a cognitive fashion for the most popular terms associated with the original terms.  That is, the system “thinks ahead” for the marketer using all of the unstructured data at its disposal.  It also refines and learns patters in the data to come up with new techniques in understanding that is being searched for.  The unstructured data is combined with sales data, location information and demographics (structured data) to determine where the product is most needed, by whom, and when.  Data is transformed cognitively into actionable information, in just a few clicks. 

The real difference here from a typical program is that the learning piece is added to the equation.  For computers to think and learn patterns from data is not new, in my opinion.  What is trans formative into this new area is the cognitive system to process all of the data, structured and unstructured, at the velocity and volumes that are being created today.  It’s not just making a decision on the available data that makes this era so unique.  It’s making decisions using ALL of the data.

I once was fortunate enough to have lunch with several others with Steve Mills, Executive Vice President, IBM Software and Systems back in 2011.  He was asked a question by one of the people attending, “How do we know what data to capture?” His answer, in light of this cognitive era was poignant 4 years ago.  “All of it” he answered.

I think he was right.

Hosting a Dinner with Chef Watson

I recently hosted a business dinner to discuss cognitive technologies.  What better way to do this than serve a creation by Chef Watson?  So I gave instructions: this will be a plated dinner, make what you want, BUT you muse serve one course created by Chef Watson, which can be accessed by anyone at https://www.ibmchefwatson.com/.  I was so proud of myself for thinking of this idea, I couldn't contain it.

On the day of the dinner, I was mentioning my proud surprise to a colleague, and was asked "What if the recipe doesn't taste good?"

Ever have one of those moments where you thought you'd thought of everything, but in reality you forgot what might be a fatal flaw?  I became a bit nervous at that moment, to describe it in the least.

When I arrived early to set up materials for dinner, this is what greeted me:

After seeing this I felt a lot better.  After eating this below, I even felt better than that.

Chef Watson eats data, not food, so my concern was valid.  But I'm reminded that there are correlations in data I still haven't found and are waiting to be explored.  We live in exciting times for people that love data.

Now I'm wondering when the Watson App for working off Chef Watson creations will be available on Bluemix?

Tools That Help Me Love Data

I'm a data geek.  A data nerd.  I think about data and I think about how to analyze data.  So much so, that my kids are starting to pick up my habit, or at least answer me in a logical, structured way.

Driving to school yesterday with my 10 year old daughter London,  we started discussing her upcoming research project.  Her school has a project that is done in groups every year from first grade on, and now she is at the level where she gets to do one by herself, on a topic that means a lot to her.

There are 3 things she likes, and one of them is math.  Numbers.  She loves them.  Stats, she understands them.  Calculations, she does them for fun.  You get the idea.

The question she wants to research: "Are girls better at math than boys?"

I stepped lightly into this (potential) minefield  of a discussion, mind you, and began the Socratic method.

Dad:"What do you think?"
London:"I don't know."
D:"How could you find out?"
L:"I could ask a bunch of girls and a bunch of boys."
D:"Would that be objective, or subjective?"
L:"Probably subjective"
D:"How could you get objective data?"

This went on until we determined there are probably some data sets somewhere she can get to analyze the performance of students in math.  Google becomes your best friend in these situations, right?  The world is full of data waiting to be analyzed. Data that's been collected that is just that, collected data.  What we need is to turn that data into information we can use to communicate our finding.

This when got me thinking of another problem: How am I going to teach data analysis to a (smart) 10 year old?  Something I've spent my career learning to effectively do?  Where do I start? Spreadsheets?  A stats program like SPSS?

London is lucky in a few ways.  1.  She is good at asking questions. 2.  She knows how to use a web browser.  3.  She can upload a file.

Because of this, her research analysis just became a lot easier (for both of us).  I helped London create her own IBM ID, the only other prerequisite other than the 3 above that is needed to get started immediately with Watson Analytics.  The videos explain step by step how to upload data and begin analysis right away.  The best part?  She can use her inquisitive mind to ask Watson questions and Watson will give her answers. It's so easy, so easy that a 10 year old can get value out of using cognitive technologies to learn.

Structured vs Unstructured Data Analysis

Reviewing the landscape

Watson technology is exciting.  IBM has made is easy for developers to access artificial intelligence tools to add to their designs through Bluemix, a platform-as-a-service offering from IBM.  What does this mean?  It means quite simply that anyone can use watson and develop Watson solutions.

Some of my favorites are there...Q&A, Personality Insights, and speech recognition.  Others, though, seem to be missing.  Where is Watson Analytics?  The existing Watson APIs on Bluemix do a great job handling unstructured (paragraphs of text) but missing is the power to analyze structured data (database type).

To analyze structured data, there is a platform of Watson Analytics that allows anyone to find correlations in their data for free.  The issue I have at this time is that they are both under the Watson banner, but don't work together in the way that all other Watson products work together. Watson Analytics is a suite of analytics tools that include natural language processing options, but aren't available as an API to integrate the 2 types of data in one query.

Hopefully we will see an addition to the Watson API options soon.

The Benefits of Watson Analytics - or How I Improved my Golf Game

OK, so I've been going on about Watson Watson, or alternatively Watson Artificial Intelligence.  I haven't talked deeply on the use of Watson Analytics.

Watson Analytics (WA) is new to the product portfolio, but is poised to be the most important in my humble opinion.  You'll see why here in a moment, but a quick rundown first.

WA is three products in one, and makes sense of event the biggest problems where data is available, but analysis is difficult.  WA is incredible at helping to understand your business problem through data, find predictors of future events, and then tell a story around these findings.

I play golf.       A.  Lot.  Of.  Golf.     Every weekend I can be found banging balls at my golf club, complete with dreams of winning tournaments.  But alas, I never win.  Typically I come in at the bottom of the golf flight.  Sometimes I come out of the gate pretty hot, but I always find a way to "snatch defeat from the jaws of victory."

Ben Hogan said "the key to golf is in the dirt", ie, hitting lots and lots of golf balls.  Because I have taken this adage to heart, I have kept my scores along with my statistics for a while, and being the data geek that I am, turned to WA to see what it told me.  This picture tells the story, straight from WA:

Watson Analytics analysis of my golf game

What WA helped me determine, was that I needed to work on getting my driver in the fairway more, and to reduce the number of putts.  This seems obvious to the casual observer, but it help me to identify and focus myself on the correct practice routine. I took the answers WA gave me, set up a practice regimen to focus on improving my driver accuracy and putting effectiveness.  Am I ready for the PGA tour now?  No, but lets have a look at my latest tournament scores.  You might have to squint, but you can see the tournament ranking in red in the picture below:

Thinking of ways to apply Watson technologies

So Watson isn't just the computer that competed on Jeopardy! I've come to realize.  I have conversations all the time where I am getting flushed with excitement over the use of Watson and what it can do.  I guess you can say that I'm looking at the world through Watson colored lenses.  I find myself looking at problems where it's obvious that applying Watson technologies can provide for a better outcome.

I live here in San Angelo, in the desert of West Texas, a community of about 100,000.  What's interesting about this area is that there is more barren land than population.  Although the density of people is outnumbered by livestock, communities of people dot the thousands of square miles out here in the edge of the desert.

How does Watson fit in?  The other day I was doing some research on this area concerning water (a very important topic here in the desert, especially when they report when you might run out of it and it's before your next birthday) and I realized there are multiple municipalities, agencies, departments, communities, citizens, authorities.....you get the idea...talking about weather and water.  I thought to myself, if you collate all of the unstructured (paragraph type data) data that was contained on websites, in city council meeting transcripts, and in blog posts on various forums, guess what you'd have?  A 360 degree view of all of the information, conversations, and most importantly DATA around this lifesaving topic.  Q and A type search each on what can be done to help, understand or find solutions. What Google did for searching websites Watson can do for searching ideas.

I have thoughts like these every day how the world can be changed with this technology.  It's kind of like when you see something you can't "unsee" it. 

My first recipe with Chef Watson

OK, so I got a bit zealous...and tried to be smart with Chef Watson.  I wanted to create cookie, and it had to use cornmeal and bacon.  Here is what Chef Watson gave me:

Actual recipe courtesy of Chef Watson

Now, I asked ICE Director of Culinary Development James Briscione point blank: "Can you tell me what recipes didn't work from Chef Watson?"  He replied that they all "worked", just chefs have to use their better judgement of the quantities and the inclusion of ingredients.  That answer reminds me of the disclaimer software vendors give you before you see potential products that hold them harmless if what they show you doesn't work out.

OK, so I make the Cornmeal Cookie from the recipe above.  Guess how it turned out?  If you read the ingredients in the picture above, I think you can figure it out.