A Picture is worth 3 billion words

Author: Thomas Gonzalez

One of the phenomenal aspects of the human brain is its ability to behave like a massively parallel set of processors, being able to simultaneously digest multiple streams of information at speeds that would stymie some of the most advanced super computers.

While traditional x86 computer processors can only process one instruction set at a time, albeit at amazing speeds, they can not process information in parallel. While a human might be able to make 1 or 2 mathematical calculations per second, and a computer is capable of billions, a human can still instantly recognize a smile, while a computer can not. All of the computers power comes from its ability to do calculations in serial, one after another, at amazing speeds; at its core all a computer is doing is performing simple Boolean equations between bits that either have a 1 or 0 value. It is just doing billions of them in fractions of a second.

But, when you apply the computers incredible serial processing capabilities to very complex mathematical problems (like using multivariate analysis to discern the meaning of a facial expression) you hit a brick wall very quickly. Using a brute force linear approach to solve these problems will bring some of the most powerful computers to its knees. So if you ask a computer to search gigabytes of text data for the word “flower” it will do an amazingly quick job of finding it (relatively easy mathematical calculations using powerful sort algorithms), but if you scan a picture of your front yard in the spring time and ask the computer to identify a blooming flower, it will have a much more difficult time.

Humans have an amazing ability to process certain types of information in a more instantaneous way, this is most evident in the way we process visual information. A very real example is the way we can analyze numbers represented as visual patterns exponentially quicker than we can analyze a set of numbers in their native form. If you were to look at a spreadsheet filled with hundreds of weekly sales numbers across product lines, versus looking at a simple bar chart with the same data, which would you prefer to determine which products sold more than others?

Lets look at this example more closely. When we look at the bar chart we can “instantly” see each bar in relationship to its neighbor and “instantly” see which ones are higher than others. This analysis and understanding happen in an instant, it isn’t even a conscious thought. It is the same as you identifying what color something is, you simply know it. Conversely, if we were looking at the numbers in a spreadsheet we need to do many more mental gymnastics. First we need to read the number which is a visual pattern in itself, and a combination of visual symbols usually consisting of one or more digits like: “123,456.” We then have to consciously make a mental comparison of each number against the others. This is a conscious and thus linear process, in which we are much slower than a computer.

So if you look at a visual representation of data you are able to process information almost instantly, but if you need to look at a raw data itself, you will be forced to consciously digest it in a linear fashion.

One of the fundamental areas we focus on in our information visualization work at BrightPoint Consulting, is to figure out ways to leverage humans naturally given pattern processing engines. To the degree we can present relevant information in visual patterns that users can take advantage of, we succeed in creating a more effective and efficient interface between the user and the data they interact with.

In the face of the exponential growth of data and information that 21st century humans need to deal with on a daily basis, technologies that allow people to more effectively process that information is not only a great opportunity for new business, but it is something that helps society as a whole. We are relieved of the tedium of repetitive information processing tasks and freed up to focus on higher level functional tasks that result from the understanding of the underlying patterns.