For our first client, we will create a multi-dimensional space in which to pull random samples in a quasi-monte carlo simulation. We will use classical computing for ETL and to create the vectors (one per dimension), then use a quantum computer for the 'hard parts.' Then, we will feed the answers into classical computers...and ultimately a Microsoft Word document. It is relatively easy (based on decades of training and experience) to understand business requirements, and challenging to figure out the mathematical approach. However, it is very challenging to figure out how to explain what we are doing...in plain business language. This is my challenge today...thoughts welcome. Regards, Jeffrey Cohen ![]()
Response to the BLOG Post (July 11, 2019)
Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc. On July 2, 2019, the founder blogged about the challenge of converting quantum computing into business language. He discussed our first beta client, a pizza chain, and how we were going to optimize pizza delivery. It was full of jargon and clever math terms like ‘quasi-Monte Carlo simulation,’ vectors, dimensions, and even ETL (extract, transform and load) the data. We could have discussed stochastic sampling if we liked. This is not helpful in most business or social contexts. People ask about the business and ‘hey, what’s quantum’ and expect an answer they can relate to. Sean, an office colleague, asked about the business yesterday. We spoke about generalities (sales, revenue, hiring, marketing, collaboration, etc.) and then our current client challenge. Here is how I explained the work. Do you gamble with cards? Games like poker or blackjack? “Sure”, he said. You know the computer games where you practice hands at home? If you win 400 out of 500 hands you feel ready to go to the casino and bet real money, but it usually does not work out that way when you go. That is because today’s computers and phones are not good at being random. Quantum computers work super-fast with probabilities and lots of choices. They can also be very random, like the nature it is based on. He said, “So, when you measure it, it’s over, right? Like Schroedinger’s Cat?” Yes, when you ask for the answer, you get the best answer at that moment…a real number. To be sure, you can ask it to repeat the problem and take the most common answer. That answer is what you use. So, you do the up-front calculations and preparation on a regular computer, then call the quantum computer, then go back to regular computers (or write a report) to use the answer. Back to winning at cards. So, imagine we could deal truly random cards. If you won 400 out of 500 hands, you would be more confident heading to the casino (which we believe is random). This made sense to him. Run an analysis many times, using truly random input, and take the most common answer. For pizza delivery, we would also look at the distribution of answers to understand our confidence with the operational, mathematical model we built based on truly random samples of their data. As an aside, post-quantum security requires large amounts of random numbers to create keys to encrypt communications. This is why we see firms pair up quantum key distribution (QKD) and quantum random number generators (QRNG). Key take-aways:
Hope you enjoyed this BLOG post. Jeffrey Cohen @Chicago_Quantum (Twitter) Https://www.chicagoquantum.com +1.312.515.7333 (cell)
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Jeff CohenStrategic IT Management Consultant with a strong interest in Quantum Computing. Consulting for 29 years and this looks as interesting as cloud computing was in 2010. Archives
February 2021
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