Jun 14th, 2016 was a pivotal day in my life.

It was the date when I executed my first program on a quantum computing server. This machine is very cold – 0.018 Kelvin (that’s 2,7 degrees celsius colder that the universe). Inside the enigmatic machine, there are five so-called q-bits. Consider them as small balls, which can either be black, white or gray. On top of this, IBM has created a language that can manipulate the balls, turning them into small elements, which can be programmed to perform certain actions.

That all sounds very regular, but consider this: the balls can be black, white, or black and white at the same time (let’s call that state for gray). They are the size of exactly one atom – and can affect each other through something called quantum entanglement, meaning they do not need to touch each other to change their states. In fact, in order to do do what they do, they need to exist in multiple parallel universes at the same time.

Practically, we look at a given problem from a solution perspective. Let’s say we have two dice, each with six sides, and we want to calculate the different combinations of the two, that give the number 5. Intuitively, we know it must be 1+4 and 2+3, but a classic computer program would have to run through each combination, evaluate the result, and only output the result if the success criteria (sum = 5) is met. That is at least 2 steps.

A quantum computer only needs one step. We start by identifying the result 5, and the quantum computer will then – through the weird logical operators – return all the input values that meet the success criteria in one go.

So is it magic? No. Is it exotic and awesome? Hell, ya’!

The IBM quantum computer has created a visual programming language called “scores”. It follows the analogies of musical scores on a note sheet or strings on a guitar. Each “note” is an operation, like add, subtract, and entangle, and once your score is completed, you can “play” it inside the quantum computer. The result is a “chord”, like on a guitar, and the digital representations of the chord are the results.

In this example, I have three q-bits (or three guitar strings) that can either be 0 or 1. Initially, they are all 0 [0,0,0]. The green boxes with the “X” turn them into [1,1,1]. Then, I use the turquoise operator with the “+” sign to change the value of the third bit to be 0 (a so-called NOT operation). If I did the same again, it would be 1, as NOT 0 = 1, and NOT 1 = 0. Finally, a measurement of the three q-bits return the results from interdimensional space to the real world and provides the output [1,1,0] – as expected.

“What’s all the fuzz about”, you may ask, “you’ve just added two numbers, my PC can do that too?” – and yes, that is correct. But imagine a more sophisticated quantum computer. One with 256 qbits. Such a device is a just few years around the corner.

Remember the example with the dice. A quantum computer could calculate the two combinations that had a sum of 5 in just one calculation, where a regular computer needed at least 2 tries.

A 256-bit number is rather large: 2^256 = 115.792.089.237.316.195.423.570.985.008.687.907.853.269.984.665.640.564.039.457.584.007.913.129.639.936. Or, in other words, the estimated number of atoms in the entire universe. A normal computer would need 1 trillion billion lifespans of the universe to complete a fraction of this calculation. A quantum computer would need less than 1/100 of a second. Thus, it would be able to crack SSL, the internet communication cryptography standard for secure transmissions. Effectively, anyone with a 256 qbit quantum computer would be able to read all your mails, have a peek at you account balance in your bank, and log in to your Facebook account.

So, progress moves forward. New cryptography standards emerge, and we will in time be able to counter the threat. However, we will also gain access to unlimited computing power, giving us a giant leap in everything from cancer research and space exploration to artificial intelligence. Here, at Innovation Lab, we are keeping a close eye on this technology, as we are sure it will shape the next 10 years of the future.

Want to try? Go ahead! Dig into quantum computing yourself at IBM Quantum Computing, and have fun. Questions? send me a mail at: bigdata@ilab.dk. And if you are interested in more explanations of complex concepts, take a look at my blog post about the difference between big data and small data.

Regs,

Mads Voigt Hingelberg

This is the age of Big Data. It surrounds us, like the clouds in the skies, seeming to be a solid mass. Yet, it is nothing but a haze, when we look inside from an airplane on our way home from vacation.
It is not tangible or clearly defined. However, at Innovation Lab, we have found a statement that tries to epitomize the concept. Big Data is the difference between what we want to do with data, and what we can do with data.

This is an age-old problem. Since the dawn of day, people have struggled with the compiling and structuring of information – and to turn that into decisions regarding future business strategies. In fact, this was why International Business Machines came to build computers. Originally, IBM produced typewriters, but a lot of the information typed in by staff in e.g. banks was compiled in archives, from where searches would take ages to perform. That was Big Data back then. In other words, the requirement to find files quickly, to provide information for decision making, and the inability to do so, made them create the computer, which we use today. In fact, the reason why files on a computer are called files, was because originally, it was physical files. The digital files were stored in a database. A file storage, from where the files could be instantly extracted and written to printers on demand.

Today, the usage of data to drive decision-making is a must-have for bigger businesses. However, these still struggle with data. Furthermore, as the amount of data increases exponentially, our ability to interact with data does not follow.

Youtube can show videos, but cannot decode the content, narrative, and meaning of a guy eating chili or a girl doing makeup. Images post a big problem too. Even Google and Facebook, for all their clear minds and unlimited resources, cannot figure out how to make real sense of an image…and the list goes on…

Small data is equally puzzling for decision makers. Usually, small data is a product of a small business or a business that is not traditionally data driven. We don’t see many mechanics do analysis on the number of bolts and joints, used for different vehicle types, over a year in order to optimize the stock of spare parts. Also, a flower shop owner will have a reasonable sense of season, flower species, and quantities to acquire from their supplier, but deep analysis of the exact optimal mix over time to optimize revenue is an uncommon practice. However, the challenge is the same. But the difference lies in the structuring, collection, and analysis, whereas the big businesses challenge lies in the complexity of data.

In Denmark, as in most – if not all – countries, the major part of the GDP is provided by small and medium businesses. Therefore, an added benefit to the GDP of an increased use of data for decision-making must come from that particular segment of businesses. Alas, enter the toolbox, without the tools.

SMBs do not have the tools and competencies needed to work with data. Business analysis is for professionals, like yours truly. It is expensive and not easily accessible. That person, who develops a tool to ease the SMBs in their use of data, and ease their decision-making, without having a statistical or financial background, will make a lot of money. However, we still need to see someone take up the challenge.

In Big Data, the data is too complex to analyze, are too large to understand, or is moving too fast to make sense of. With Small data, the collecting and analysis of data are the main problems. Both problem statements require solutions, and both are equally difficult.

If you want to know more about Big and Small Data, reach out to me at bigdata@ilab.dk, and let’s have a talk! I have also defined Quantum Computing, if you are looking for even more practical takes on complex concepts.