We were on NOVA’s Making Stuff program last week. Here’s the segment where we appeared. It’s pretty … cool.
Cypress Semiconductor Corporation is a semi- conductor design and manufacturing company founded in 1982 by T. J. Rogers and others from AMD. We’re working with them to build bigger and better superconducting circuits — ultimately millions of qubits and billions of devices per chip. The biggest problem we (or any QC effort that follows us) faces is the manufacturability of designs, and Cypress has one of the most incredible fabrication operations I have ever seen. You can see an overhead shot of the Minnesota facility to the right. This doesn’t do it justice. Acres of fab machines. And the people are top rate. Very exciting.
SAN JOSE, Calif. & BURNABY, British Columbia — Cypress Semiconductor Corp. and D-Wave Systems Inc., the world’s first commercial quantum computing company, today announced that D-Wave has successfully transferred its proprietary process technology for building quantum computing microprocessors to Cypress’s Wafer Foundry located in Bloomington, Minnesota. D-Wave selected Cypress as its foundry and started the site change in January of 2013, and Cypress delivered first silicon on June 26. Results from this lot indicate better yields than D-Wave has achieved in the past, validating the quality of Cypress’s production-scale environment.
Ajay Agrawal is the Peter Munk Professor of Entrepreneurship at the Rotman School of Management at the University of Toronto. He is also an old friend. We both went through Haig Farris’ High Tech Entrepreneurship course at UBC. We stayed in touch through the years. Ajay even wrote a Harvard Business School case study on D-Wave when he was there.
In 2012 Ajay started a business incubator at U of T called the Creative Destruction Lab (CDL). You can read about it here. They have been very successful. One of the companies that went through the process is Thalmic Labs. Their initial product, the Myo, sold 25,000 units in the first month after its release.
The CDL runs a model where a group of seven successful entrepreneurs mentors and guides the participants through a very competitive process that focuses resources on companies that look like winners. This group is called the G7. It is a little like the Dragons on Dragons Den.
A couple of months ago, Ajay asked if I would be interested in being a member of the G7 this year. Of course I said yes. It’s a very cool opportunity to help along the next Elon Musk or Marissa Meyer. As the year progresses, I’ll let yall know about some of the interesting companies in this year’s cohort.
Five months ago, I received an email and then a phone call from Google's Creative Lab Executive Producer, Lorraine Yurshansky. Lo, as she prefers to be called, is not your average thirty year-old. She has produced award-winning short films like Peter at the End (starring Napoleon Dynamite, aka Jon Heder), launched the wildly popular Maker Camp on Google+ and had time to run a couple of New York marathons as a warm-up to all of that.
Google produced a most excellent video introducing some of the folks working at the Quantum Artificial Intelligence Lab. Here it is!
You can see some cool shots of our new facility in the piece, like this one.
There are more that a dozen of these machines doing interesting things now. They are crunching away on everything from basic physics experiments, probing entanglement on scales that humans have never been able to before, to commercial applications of machine learning — like the wink detector in the Google Glass product.
There are some great memes in the video. One of my favorites was raised by Sergio Boixo. He says at 4:25, ‘… [this machine] teaches us that we shouldn’t be naive about the world, and we shouldn’t think about the world as a simple machine. It forces us to consider more sophisticated notions of how the reality around us is actually shaped.’
I lay awake at nights wondering whether simply we as a species are simply too stupid to figure out the Universe that we are investigating, and maybe we need some other species one percent smarter than we are, for which string theory would be intuitive, for which all the greatest mysteries of the Universe, from dark matter, dark energy, the origins of life, and all the frontiers of our thought, would be something that they would just self-intuit. I’m jealous of that possibility. Because I want to be around for those discoveries.
I feel a lot of sympathy for this position. It got me thinking that waiting for the “real one percenters” to show up might be dangerous. Maybe it’s a better strategy to try to create them. If only we had some type of quantum artificial intelligence…
Yesterday I was part of a session at IDC’s HPC user forum. This session was interesting because it was about quantum computing. This was the first time the HPC user forum has had a session on quantum computing. I think there will be many more in the future.
Not only was there an entire session on the topic, but the keynote speaker at the event was Charlie Bennett, an IBM Fellow who is well-known to quantum information folks, as (among other things) he co-invented quantum cryptography. I’m going to do a separate post on what he was talking about as it was fascinating.
The session I was part of was led off by Isaac Chuang from MIT, who gave an overview of where he felt the field of quantum information science and technology was. There was a pretty comprehensive overview of a set of experimental results that had been obtained c. 2002 and c. 2013, showing an impressive advance in these results from being able to do about 10 gates on 1 qubit in 2002 to about 10s of gates on about 10 qubits in 2013. Unfortunately, he completely omitted any mention at all of any of our work, or the work of independent folks doing science on our machines. I will send him some copies of Nature.
I was next, and started the festivities by stating that basically I disagreed with everything Ike had said, and was going to give a very different perspective. I felt bad about being confrontational (obviously I still haven’t watched enough Hitchens, I am working on it). But he was in the room, so if he wanted to call me on something he could (he didn’t). A smart non-expert audience that hears completely conflicting stories is going to be confused and wonder what’s up. So I thought it would be in the interests of the audience to put a name on it.
Anyway, once the drama was out of the way, I gave my talk. Here are the slides.
After my talk, Hartmut Neven from Google talked about their D-Wave machine, and what they were doing with it. He described three use cases for machine learning, including finding extremely sparse classifiers, reducing the negative effects of improperly labeled items in supervised machine learning methods, and training and inference in deep learning. One very interesting thing he revealed was that the first of these was used to train blink detectors in the Google Glass product. This is the very first time that a quantum algorithm has been used to develop commercially deployed software.
This is extremely cool, and the beginning of what I see as a new use case opportunity for us. The scenario where you need an always on detector / classifier onboard a device with extreme power constraints is increasingly common. I just absolutely love the idea that the software that makes mobile devices work can be designed by quantum computers.
Next, Dave Wecker from Microsoft gave an overview of his group’s work on building software for programming, compiling and visualizing quantum circuits. The work they are doing is really top notch, and the presentation was great.
Finally, Jay Gambetta from IBM Yorkton Heights gave a talk about the IBM work on transmon qubits. I think the main point of interest for me about this work is how difficult / impossible it would be to scale any of it up. Lots of microwave lines!!!