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upyourego OP t1_ivtwrbz wrote

Jay Gambetta, IBM Fellow and vice president of IBM Quantum said 2023 is a major inflection point for quantum computing, the starting point when the quantum-centric supercomputer is first realised and scaling is enabled. He said that it does so by “combining quantum communication and computation to increase computational capacity”.

British startup Universal Quantum is taking a similar approach, developing multi-chip quantum computers for more rapid scaleup.

But it is still some time before we reach any real supremacy as a study by the University of Sussex found we'd need 13 million qubits to crack 256 bit encryption in a day.

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ShortForNothing t1_ivue4hh wrote

I understand that to be an industry leader you kind of need to go in hard and early, but is QC still a solution without a problem? Or perhaps, the computing power hasn't reached "useful" level yet? This is in no way trying to downplay the potential future applications, but the article doesn't touch on what applications IBM is banking on here that would make them want to go all-in. Maybe there aren't any anticipated uses they are looking at and are still in the exploratory stage; I'm simply curious.

Watson seems to come to mind as a Solution in search of a Problem that IBM thought was going to be the focus and ended up being massively scaled back (granted, Watson is finding niche use and success, but it's not the breakthrough success IBM hyped up).

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IceColdPorkSoda t1_ivugg4p wrote

The ability to accurately model proteins without X-ray crystallography would be massive for the pharmaceutical industry. Being able to model a whole cell would be another lightyear leap. For drug development it would be absolutely revolutionary.

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upyourego OP t1_ivufevu wrote

At a briefing with IBM I was told they have a large number of finance and pharmaceutical customers due to the ability quantum will have to carry out rapid calculations. They’ve also recently signed a deal with Vodafone for network analysis using quantum computing.

Obviously the real benefit isn’t here yet - it will take more qubits (hundreds of thousands) and better fidelity and error correction - but there are existing use cases. Some of these are algorithms for fraud detection running on IBM hardware.

Apparently there are significant wait times to use quantum hardware available via AWS

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UniversalMomentum t1_ivusp47 wrote

Quantum enhanced machine learning might give machine learning more depth and adaptability across many fields.

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