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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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The third of three new exa-scale computers set to be purchased and built by Secretary Rick Perry and the Department of Energy. Robin Goldstone, a solution architect at LLNL, gave an interview at the Red Hat Summit 2019. She suggested el capitan will be 10x the performance of Sierra (which is 125 petaflops, and "so El Capitan's targeted to be 1.2, maybe 1.5 exaFLOPS, or even more. Again, that's peak performance, it doesn't necessarily translate into what our applications can get out of the platform." In concept, we can use this to "push a workload through 10 times faster or we can look at a simulation that's 10 times more resolved" (better detail). There will be an El Capitan Center of Excellence at LLNL (deployment and production use from 2023 - 2038). It should focus on AI and machine learning, and advancing the goal of intelligent simulation or cognitive computing. El Capitan (ATS-4) is the successor to Sierra, and will be succeeded by (ATS-6) in 2027-2028 timeframe. In March 2019's DoE FY2020 Congressional Budget Justification: Highlights of the FY 2020 Budget:
LLNL needs more computing capability to achieve and advance its mission. "More computing capability is needed." (Original in bold.) Good one pagers on the DoE Exascale Computing Project (ECP) (thank you Rick Stevens, Argonne National Laboratory & The University of Chicago):   Sources:
https://video.cube365.net/v/Plqw-LotHfo https://asc.llnl.gov/content/assets/docs/ElCap_IntelligentSimCOE_whitepaper.pdf https://en.wikichip.org/wiki/supercomputers/ats-4 https://www.energy.gov/sites/prod/files/2019/04/f62/doe-fy2020-budget-volume-1.pdf http://www.sci.utah.edu/~chris/Rick-Stevens-DSCI-Lecture-2019.pdf https://exascale.llnl.gov/ https://www.exascaleproject.org/ By Jeffrey Cohen, @chicago_quantum, Founder of Chicago Quantum. June 10, 2019 Seven facts about Frontier (from the sources): - Weighs over a million pounds - Performance equals the world's top 160 fastest supercomputers. - Performance of 1.5 exaflops, equals 1.5 quintillion operations per second, equals 1.5 x billion x billion operations per second. - Partnership between Oak Ridge National Laboratory (ORNL), U.S. Department of Energy, Cray and AMD, with a Cray contract including $6oom for a CoE, early delivery systems, the main Frontier system, and multi-year system support. - Cray Programming Environment (Cray PE) will be enhanced in 3 ways: enhanced high-level software development environment, integrated with AMD technology with Cray Slingshot to take better advantage of the hardware, and integrated with a full machine-learning software stack. - Establish a Center of Excellence by Cray and Oak Ridge National Lab Frontier will be based on Cray's architecture, AMD's CPU and GPU technologies. - Lawrence Livermore Lab will have an exascale computer too (pre-announced), and Argonne National Lab's Aurora @ 1.0 exaflops was recently announced (Intel and Cray for $500M). Sources: https://www.cray.com/resources/how-frontier-measures-up https://www.cray.com/blog/doe-and-cray-announce-exascale-supercomputer-frontier/#comment-757096 http://investors.cray.com/phoenix.zhtml?c=98390&p=irol-newsArticle&ID=2397457 Implications: While Energy Secretary Rick Perry discusses how we will 'win' the race to develop quantum computers, he is ensuring the U.S. has access to exascale classical computing too. Start watching this video, here: https://youtu.be/KnxLoScPCcQ, or here: https://quantumxc.com/watch-quantum-xchanges-tedx-talk/ at 5:39:45 to hear John Prisco, CEO of Quantum Xchange, discuss how QKD works, why we need it, and the general context of encryption. I took away three key points: 1) the Chinese government has a 1,240 mile QKD link between Beijing and Shanghai, showing this can happen over land...over long distances, 2) they also have a satellite link that uses QKD, showing this can happen through space, and 3) Quantum Xchange has their link in the Holland Tunnel (and in fiber cables around the East Coast). I read somewhere else that the US can now do this via an airplane and ground station, allowing for secure communications to aircraft. OK, so the video only covered points 1 and 2. I learned the 3rd point today from a news article that @Quantum_Xchange tweeted. Here is Quantum Xchange's website: https://quantumxc.com/ So, how does it work? We entangle photons (each is '1' or '0' and together those bits make up a quantum inspired algorithm key) and send them down the link. If somebody tries to look at them, they lose their entanglement and change. They show someone looked (tamper apparent). It is like Schroedinger's Cat...if someone looks the wave function collapses, and quantum values collapse to classical ones. Pretty cool stuff. Photonics based networking. Speed of light, slowed by repeaters and other equipment. I am still waiting for data teleportation and instantaneous communication of states between photons and electrons (if I do something here, it immediately determines the value there...and there could be very far away). Thank you for reading. Jeffrey Cohen, May 30, 2019, Founder & CEO of Chicago Quantum, a division of US Advanced Computing Infrastructure, Inc. Another update on June 6, 2019. I just posted yesterday about British Telecom (BT) going live with their 125km QKD network in England in March 2019 on this website. I tweeted on it @chicago_quantum.
Looks like BT has been working on this since 1993 (when they sent their first quantum encrypted message). Just read articles about Google, D-Wave, IonQ, IBM and generically about AI / Quantum intersection. IonQ. The first 2 had hardware innovations, the 3rd said be patient, the fourth improved interpretation and modeling, and the 5th helped us see that Quantum and AI are improving faster together, with synergies.
Worth a read... Jeffrey Cohen, May 21, 2019 There is so much in this article, that I suggest you read it. It is not comprehensive, and may not be entirely correct...but it summarizes information that I understand, and ties together some new insights (e.g., IBM has shown the ability to use a supercomputer to simulate a 49 qubit system).
By Jeffrey Cohen, May 16, 2019
After spending ~30 minutes reading through meetup.com invitations and groups, and not signing up for a single one (not feeling social) I came across this article by the Kellogg School of Management at Northwestern University (May 1, 2019 - access via the button above). Maybe the four tips would help me network more... 1) Prepare a Repertoire of Questions—but Maintain a Curious Mindset 2) Choose Conversation Partners Wisely 3) Focus on Relationships, Not Business Cards 4) Know When to Move On At this level, I didn't learn anything new...but there were small nuggets of insight. 1) Be interested in the answers to the questions you ask, or don't ask them. Don't fake it. Listen carefully. Look for things in common, and ways that you are similar. 2) Read the room first, quick hello to the senior executives, and focus on meeting new people. Don't pick people that look 'senior' or 'executive' and keep learning new things from people. 3a) It is ok to meet just one or two people, if it can lead to a deeper professional relationship 3b) Connect people appropriately to others to help or collaborate; this is a valuable skill. 4) Transition out of a conversation quickly enough with a thank you, interest in continuing the conversation at another time, and exchange information. We are there to network... Hope that helps. Thank you to Holly Raider, Clinical Professor of Management at Northwestern. According to their website (graphics are posted there too): "Nanoco leads the world in the research, development and large-scale manufacture of heavy-metal free quantum dots and semiconductor nanoparticles for use in displays, lighting, solar energy and bio-imaging." In short, Nanoco Group PLC makes quantum dots at scale, without heavy metals, that adjust and tune light. Energy and light comes in, and can be tuned to emit the color you want...all by adjusting the length (think column) of the Cadmium Free Quantum Dots (CFQD).   What does it do/what is it? "CFQD® quantum dots are fluorescent semiconductor nanoparticles typically between 10 to 100 atoms in diameter, which is about 1/1000th the width of a human hair. When one of these particles is excited by an external light source, it absorbs the energy and re-emits the light in a different colour depending on the size of the particle. Therefore, by tuning the size of these particles, one is able to control the colour of light emitted to any colour in the spectrum." What could that mean in quantum computing? Not sure...except it is good to see other use-cases for commercial quantum materials, in this case lighting and displays. It improves display and lighting performance and reduces energy consumption. Who does/did Nanoco work with? Dow Chemical, Merck, and Wah Hong Industrial (as of 2016). Sources: http://optics.org/news/7/8/2 http://www.nanocolighting.com/technology/ Other uses include making hydrocarbons from carbon dioxide, solar cells, treating antibiotic and treatment resistant strains of infections, spintronic semiconductor devices (qubit), humidity and pressure sensors, imaging of cancer tumors, miniature lasers for high speed data transfer, and as listed above, TV or computer displays.
This is worth listening to. Three start-ups and a University of Chicago professor enlighten the House Energy Subcommittees on Environment and Digital Commerce and Consumer Protection in May 2018.
My take-aways: 1) I hear mostly the same discussion of quantum computing, as a start-up technology, hard to explain, highly technical, need to use analogies, many challenges, futuristic applications, and great potential. I feel myself being pulled towards it, like an early American settler who hears "go West young man" in spite of the dangers ahead. 2) There is a search for a 'killer app' for quantum. (I have said this before in prior notes) 3) Workforce enablement is a very important constraint limiting the development of commercial quantum computing, and not just due to a lack of seats and teachers. It is a complex learning curve. It is hard to learn advanced math, physics, computer science, and materials sciences, along with specific industry domains (e.g., settlement of trades), software development lifecycle, and agile, consulting methods. My favorite part of the video came at 1:10:00 for the next 3 minutes when congressman Larry D. Bucshon M.D. asked for the Quantum Computing Federal Funding 'elevator pitch.' Nobody got it right in my opinion. This is what my brother and mentor, Seth Cohen, Canterbury Eleven CEO, asked me to focus on last week in Florida. Check back for more interesting news and ideas. I try to post at least weekly...and sometimes daily. Jeffrey Cohen, Founder & CEO, Chicago Quantum, a division of U.S. Advanced Computing Infrastructure, Inc. May 9, 2019 Labor productivity over the past four quarters is the largest since 3Q/2010.
Q1/2019 highlights (seasonally adjusted annual rates): - Output up 4.1% - Hours Worked up 0.5% - Unit labor costs down 0.9% (a net factor) Download the news release here: https://www.bls.gov/news.release/pdf/prod2.pdf My analysis: It wasn't in Manufacturing...output declined, labor hours worked declined faster, and relative unit labor cost became more expensive by 0.8%. |
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
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