Quantum Computing

This week on The Digital Life, we discuss the strange and exciting world of quantum computing. Quantum computers operate on an atomic level, harnessing the power of quantum mechanics to perform processing tasks much more rapidly than computers designed using classical physics. They have the potential to perform calculations much, much faster than any of our silicon-based super computers today — up to 100 million times faster, in fact.

Research in quantum computing has up until recently, been largely theoretical, with the practical technology needed to achieve it beyond reach. But now both Google and D-Wave, a Canadian company, have made some significant progress. Will there be a coming revolution in computing power? Will quantum computers one day replace our silicon chip based computing devices?

Subscribe on iTunes

Moore's Law -- putting more and more transistors on a chip -- accelerated the computing industry by so many orders of magnitude, it has (and continues to) achieve seemingly impossible feats. However, we're now resorting to brute-force hacks to keep pushing it beyond its limits and are getting closer to the point of diminishing returns (especially given costly manufacturing infrastructure). Yet this very dynamic is leading to "a Cambrian explosion" in computing capabilities… just look at what's happening today with GPUs, FPGAs, and neuromorphic chips. Through such continuing performance improvements and parallelization, classic computing continues to reshape the modern world.

But we're so focused on making our computers do more that we're not talking enough about what classic computers can't do -- and that's to compute things the way nature does, which operates in quantum mechanics. So our smart machines are really quite dumb, argues Rigetti Computing founder and CEO Chad Rigetti; they're limited to human-made binary code vs. the natural reality of continuous variables. This in turn limits our ability to work on problems that classic computers can't solve, such as key applications in computational chemistry or large-scale optimization for machine learning and artificial intelligence. Which is where quantum computing comes in.

But what is quantum computing, really -- beyond the history and the hype? And where are we in reaching the promise of practical quantum computers? (Hint: it will take a hybrid approach to get there.) Who are the players -- companies, countries, types of people/skills -- working on it, and how can a startup compete in this space? Finally, what will it take to get "the flywheel" of application development and discovery going? Part of the answer comes full circle to the same economic engine that drove previous computing advances, argues Chris Dixon; Moore's Law, after all, is more of an economic principle that combined the forces of capitalism, a critical mass of ideas, and people moving things forward by sheer will. Quantum computing is finally getting pulled into the same economic forces as well.

a16z Podcast: Quantum Computing, Now and Next

A funny thing happened on the way to quantum computing: Unlike other major shifts in classic computing before it, it begins -- not ends -- with The Cloud. That's because quantum computers today are more like "physics experiments in a can" that most companies can't use yet -- unless you use software, not just as cloud infrastructure for accessing this computing power commercially but for also building the killer app on top of it. What will that killer app be? With quantum virtual machines and special languages for connecting and trading off classic and quantum computing, companies and developers may be able to help figure that out, not to mention get ahead of this next computing platform (before it surprises them).

Ok, sounds great. Only the old rules don't all apply: You have to fundamentally rethink algorithms for quantum computing, just as with previous waves of high-performance computing before it -- from CPU to GPU to TPU and now to QPU. Because as chips evolve, so do algorithms, and vice versa, in an iterative way. But the chicken-egg question of which came first (the algorithm or the specialized hardware for running it?) doesn't matter as much because the answer itself involves herding chickens: "You're trying to get all of these independent processes to run and cooperate with each other to produce an answer and do so in a way that was faster" than the other way before it, observes Jeff Cordova, interim head of software engineering at quantum computing startup Rigetti Computing. "In hindsight, we really care about the statistical model, not watching the entire movie", shares general partner Vijay Pande, based on his own experiences in the world of high-performance computing.

In this episode of the a16z Podcast (in conversation with Sonal Chokshi), Cordova and Pande talk all about the realities of engineering -- and using -- the next computing platform beyond scientific research and hardening it into practical, commercial, industrial-scale reality. Luckily, the cloud provides a map to get us there, today.

Quantum Computing

karthik kumar