Google's Potential in Quantum Machine Learning
Google and Microsoft will leverage Quantum Advantage for A.I.
I’m on vacation today on the 4th of July, but I’ve been thinking about how the Cloud is going to leverage quantum computing startups, their IP and align their own initiatives to be leaders in machine learning powered by QML.
Will QML Provide an Exponential Advantage?
From Time Crystals, to Quantum Supremacy and now Quantum Advantage in machine learning, Google wants us to believe that it’s on the bleeding edge of quantum computing. Whether that’s actually true or not, Google Cloud needs to leverage Quantum computing with its already world-class (world leading) group of A.I talent at Deepmind, Google AI, Google Brain and so forth.
Scientists say they have proved quantum advantage in machine learning. Practical applications of the tech may not be far away.
The ability of Amazon, Microsoft and Google to lead how machine learning and QML evolves for the future of artificial intelligence is now very high in the early 2020s. I write pretty frequently on artificial intelligence, if that interests you.
The End of Classical Computing
In the next 20 years we’re very likely to witness the end of classical computing. Hybrid Cloud and hybrid Quantum systems are likely the future. Some believe Quantum Machine Learning (QML) is going to be a game-changer. I’m in the bullish camp here.
BigTech companies already dominate how software languages and their communities evolve, the same is likely to occur with QML. Google is very incentivized to at least keep up with Amazon and Microsoft in this domain, as will any global Cloud player like Alibaba, Baidu, Salesforce, IBM and others.
This means that the cash-cow revenue that is Cloud computing, will enable incredible R&D occur in the 2020s, but especially in the 2030s as quantum computers are more likely to solve scalability of qubit systems well over 100,000.
By following the research of Microsoft, Google AI and Amazon along with QC startups and their PR, you can get a fairly good idea at the probable intersection of machine learning and QML.
Just as A.I. language models (Towards Data Science) are proliferating today, QML will enter its golden age circa 2027 to 2039. This is of course just my opinion.
In October 2019, Google scientists announced they’d achieved “quantum supremacy,” the long-sought proof that a computer built around the strange properties of quantum mechanics can, at least in certain cases, carry out calculations exponentially faster than a computer built around classical bits. Google now claims they have an inside-track on leveraging Quantum Advantage.
Google not Microsoft or AWS are Best Equipped to Leverage Quantum Machine Learning
While Microsoft have a superior and better diversified business model. And while AWS has a much more interesting current architecture for Cloud services including Braket, it’s actually Google that has the best R&D potential to commercialize QML, Google is closest to a pure-play A.I. company, than Microsoft or Amazon likely ever will be.
Due to this we have to take what Google claims at fair value. Even Quantum Insider finally covered this. If I could interview people in the academic world who have insider knowledge of AI at the intersection of the future of QML I would, but my coverage of the Cloud and BigTech suggests to me that significant consolidation will likely occur and it will occur rapidly. This is also because America has chosen a winner-takes-all Capitalism where antitrust regulation and rule of law does not truly exist in the face of Monopolies.
This is even more true in a geopolitical climate that involves an East-West rivalry that everyone know is mostly just the current empire of the United States against the heir apparent, China. Because National Security sees Quantum technology as part of their expanding budgets, M&A and centralization of IP and talent will rapidly emerge in this Cold-war BigTech situation. All of this will benefit Google and its efforts in Quantum.
The Rigetti, IonQ and other startups that attempt to scale will finally be acquired in an increasing difficult VC environment with higher interest rates and more limited access to capital to stimulate growth and scalability. China for its part will also facilitate dozens if not hundreds of startups in the space in the next two decades. China has already prioritized quantum communications and A.I. in its long-term vision of how its technology and economy scales globally in the 21st century.
The strategy of the U.S. Defense sector and Government will be to allow Cloud giants to become dominant QML and Quantum computing gateways. Part of this will be due to politics, national defense and how Silicon Valley lobbyists impact how they are treated in overall declining ecosystem of American innovation. There will always be pundits and PR types who say America is the leader in innovation, but that simply isn’t’ true any longer.
QML Will Lead to Exponentially Better A.I., Eventually
In “Quantum Advantage in Learning from Experiments”, a collaboration with researchers at Caltech, Harvard, Berkeley, and Microsoft published in Science, the academics showed that a quantum learning agent can perform exponentially better than a classical learning agent at many tasks.
Google is best positioned to invest in the right R&D and attract just the right kind of talent to best position itself as the leader in A.I. at the intersection of QML and Quantum computing architectures. The problem is, in this age of hype there’s some degree of uncertainty about how the nascent field will scale.
The Google Quantum AI team, commenting on the study in a recent blog, wrote that such tasks could fall under the abilities of today’s quantum computers, or near-term devices. Just as A.I. collaboration is at an all-time high in academics, so too collaboration by academics in Quantum computing and QML will scale very quickly.
I think the Quantum Observer might agree with this, I do not know.
While I like Azure Quantum, I just don’t think they are as well positioned to invest the needed $$$ to scale the applied research as well as Google is. Google will have more PhDs on this than either Microsoft or Amazon and maybe more than both of them combined eventually.
Alphabet’s stock split is coming.
Investing in startups like IonQ, Rigetti or D-Wave is truly a gamble, since the SPAC route is so dangerous and the VC world is so irrevocably changed and different in the coming years of higher interest rates. I actually do write a Newsletter on investing and I’m a fanatic watcher of the stock market. Full disclosure, I don’t own any Google stock or any of the other three as well.
Google’s PR is very aggressive, but when viewed from a macro business perspective, we find Google is best positioned to leverage and commercial Quantum machine learning as a whole if given enough time to mature. There’s no escaping this conclusion, but if you have a different point of view I’d love to hear it.
Time crystals, Quantum Advantage, Quantum Supremacy are just words. The future of A.I. will embed quantum computing and whatever can manifest via QML will be interesting to watch. At the end of the day this is why I created this Newsletter. If you want me to be able to keep writing, please consider supporting the channel.
I am just one person managing x number of Newsletters about the future. I’m a self-titled “futurist in residence” on Substack. But currently, it’s not enough to even pay the rent. But for the price of a cheap meal, you could help.
Thanks for reading this Op-Ed.
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