Ibm Delivers New Quantum Package
Postedabout 2 months agoActiveabout 2 months ago
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IBM has released a new quantum package, likely expanding its quantum computing capabilities, but the lack of comments and details makes it hard to gauge the community's reaction.
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Nov 13, 2025 at 4:24 AM EST
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In 2019, Google claimed quantum supremacy [1]. I'm truly confused about what quantum computing can do today, or what it's likely to be able to do in the next decade.
[1] https://www.nasa.gov/technology/computing/google-and-nasa-ac...
The most similar comparison is AI stuff, except even that has found some practical applications. Unlike AI, there isn't really much practicality for quantum computers right now beyond bumping up your h-index
Well, maybe there is one. As a joke with some friends after a particularly bad string of natural 1's in D&D, I used IBM's free tier (IIRC it's 10 minutes per month) and wrote a dice roller to achieve maximum randomness.
Sorry for that, but seriously, I'd treat this kind of claim like any other putative breakthrough (room-temperature superconductors spring to mind), until it's independently verified it's worthless. The punishment for crying wolf is minimal and by the time you're shown to be bullshitting the headlines have moved on.
The other method, of course, is to just obsessively check Scott Aaronson's blog.
The main issue is that these algorithms where today's early quantum computers have an advantage were specifically designed to be demonstration problems. All of the tasks that people previously wanted a quantum computer to do are still impractical with today's hardware.
[1] https://www.quantamagazine.org/google-and-ibm-clash-over-qua...
The computer *did not* produce the same results each time, and often the results were wrong. The service provider's support staff didn't help -- their response was effectively "oh shucks."
We discontinued considering quantum computing after that. Not suitable for our use-case.
Maybe quantum computing would be applicable if you were trying to crack encryption, wherein getting the right result once is helpful regardless of how many wrong answers you get in the process.
They're especially good for oracle-type problems, where you can verify an answer much faster than you can find them. NP problems are an especially prominent example of that. If it's wrong, you try again.
In theory it might take a very long time to find the answer. But even if you've only got 25% accuracy, the odds of you being wrong 10 times in a row are only 6%. Being wrong 100 times in a row is a number so small it requires scientific notation (10^-13). It's worth it to be able to solve an otherwise exponential problem.
[0] https://www.youtube.com/watch?v=rBfK-l-qSNk
Though it looks like he recently switched to working at Google AI...
https://scholar.google.com/citations?user=NaxMJzQAAAAJ&hl=en