Ethan BatraskiContributor

Ethan Batraski is a partner at Venrock, where he invests across sectors with a particular focus on hard engineering problems such as developer infrastructure, advanced computing and space.

Every major technology breakthrough of our era has gone through a similar cycle in pursuit of turning fiction to reality.

It starts in the stages of scientific discovery, a pursuit of principle against a theory, a recursive process of hypothesis-experiment. Success of the proof of principle stage graduates to becoming a tractable engineering problem, where the path to getting to a systemized, reproducible, predictable system is generally known and de-risked. Lastly, once successfully engineered to the performance requirements, focus shifts to repeatable manufacturing and scale, simplifying designs for production.

Since theorized by Richard Feynman and Yuri Manin, quantum computing has been thought to be in a perpetual state of scientific discovery. Occasionally reaching proof of principle on a particular architecture or approach, but never able to overcome the engineering challenges to move forward.

Thats until now. In the last 12 months, we have seen several meaningful breakthroughs from academia, venture-backed companies, and industry that looks to have broken through the remaining challenges along the scientific discovery curve. Moving quantum computing from science fiction that has always been five to seven years away, to a tractable engineering problem, ready to solve meaningful problems in the real world.

Companies such as Atom Computing* leveraging neutral atoms for wireless qubit control, Honeywells trapped ions approach, and Googles superconducting metals, have demonstrated first-ever results, setting the stage for the first commercial generation of working quantum computers.

While early and noisy, these systems, even at just 40-80 error-corrected qubit range, may be able to deliver capabilities that surpass those of classical computers. Accelerating our ability to perform better in areas such as thermodynamic predictions, chemical reactions, resource optimizations and financial predictions.

As a number of key technology and ecosystem breakthroughs begin to converge, the next 12-18 months will be nothing short of a watershed moment for quantum computing.

Here are eight emerging trends and predictions that will accelerate quantum computing readiness for the commercial market in 2021 and beyond:

1. Dark horses of QC emerge: 2020 will be the year of dark horses in the QC race. These new entrants will demonstrate dominant architectures with 100-200 individually controlled and maintained qubits, at 99.9% fidelities, with millisecond to seconds coherence times that represent 2x-3x improved qubit power, fidelity and coherence times. These dark horses, many venture-backed, will finally prove that resources and capital are not sole catalysts for a technological breakthrough in quantum computing.

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Eight trends accelerating the age of commercial-ready quantum computing - TechCrunch

Bradley Rotter is a visionary investor who has pioneered investments in many new alternative investments classes including having been an early backer of hedge funds in 1982 while speculating on the Chicago Mercantile Exchange. He was also an early investor in Bitcoin and other cryptocurrency ecosystems and at a dinner with OODA CEO Matt Devost in 2012 predicted Bitcoin would exceed the price of gold.

Bradley moved to San Francisco in mid 80s to be close to the technology fountainhead of the Bay Area. In 1995 he was famously quoted saying this internet thing is going to be big and this vision guided his investments in several successful technology companies.

Bradley has made numerous VC and PE investments, with a particular focus on internet and technology and spanning from hedge funds to satellites.

This wide ranging conversation hits on multiple high tech topics including quantum computing, crypto currencies and the data analytics.

Podcast Version:

Additional Reading:

Quantum Computing Sensemaking

Is Quantum Computing Ushering in an Era of No More Secrets?

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OODAcast: Bradley Rotter On The Future Of Work, CryptoCurrencies, Quantum Computing and Leadership - OODA Loop

By U.S. Department of EnergyAugust 6, 2020

To keep qubits used in quantum computers cold enough so scientists can study them, DOEs Lawrence Berkeley National Laboratory uses a sophisticated cooling system. Credit: Image courtesy of Thor Swift, Lawrence Berkeley National Laboratory

A quintillion calculations a second. Thats one with 18 zeros after it. Its the speed at which an exascale supercomputer will process information. The Department of Energy (DOE) is preparing for the first exascale computer to be deployed in 2021. Two more will follow soon after. Yet quantum computers may be able to complete more complex calculations even faster than these up-and-coming exascale computers. But these technologies complement each other much more than they compete.

Its going to be a while before quantum computers are ready to tackle major scientific research questions. While quantum researchers and scientists in other areas are collaborating to design quantum computers to be as effective as possible once theyre ready, thats still a long way off. Scientists are figuring out how to build qubits for quantum computers, the very foundation of the technology. Theyre establishing the most fundamental quantum algorithms that they need to do simple calculations. The hardware and algorithms need to be far enough along for coders to develop operating systems and software to do scientific research. Currently, were at the same point in quantum computing that scientists in the 1950s were with computers that ran on vacuum tubes. Most of us regularly carry computers in our pockets now, but it took decades to get to this level of accessibility.

In contrast, exascale computers will be ready next year. When they launch, theyll already be five times faster than our fastest computer Summit, at Oak Ridge National Laboratorys Leadership Computing Facility, a DOE Office of Science user facility. Right away, theyll be able to tackle major challenges in modeling Earth systems, analyzing genes, tracking barriers to fusion, and more. These powerful machines will allow scientists to include more variables in their equations and improve models accuracy. As long as we can find new ways to improve conventional computers, well do it.

Once quantum computers are ready for prime time, researchers will still need conventional computers. Theyll each meet different needs.

DOE is designing its exascale computers to be exceptionally good at running scientific simulations as well as machine learning and artificial intelligence programs. These will help us make the next big advances in research. At our user facilities, which are producing increasingly large amounts of data, these computers will be able to analyze that data in real time.

Quantum computers, on the other hand, will be perfect for modeling the interactions of electrons and nuclei that are the constituents of atoms. As these interactions are the foundation for chemistry and materials science, these computers could be incredibly useful. Applications include modeling fundamental chemical reactions, understanding superconductivity, and designing materials from the atom level up. Quantum computers could potentially reduce the time it takes to run these simulations from billions of years to a few minutes. Another intriguing possibility is connecting quantum computers with a quantum internet network. This quantum internet, coupled with the classical internet, could have a profound impact on science, national security, and industry.

Just as the same scientist may use both a particle accelerator and an electron microscope depending on what they need to do, conventional and quantum computing will each have different roles to play. Scientists supported by the DOE are looking forward to refining the tools that both will provide for research in the future.

For more information, check out this infographic:

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A Quintillion Calculations a Second: DOE Calculating the Benefits of Exascale and Quantum Computers - SciTechDaily