Tang's recent work on quantum-inspired classical algorithms has sparked a whole subfield focused on identifying which quantum speedups are truly unique versus those that can be replicated classically.
Quantum computing occupies the same space that Nanotechnology used to hold, and AGI is trying to claim; something so profoundly game-changing that it'll rewrite the rules of society itself.
Venture capitalists love this type of story, because its sells the most funding in future rounds.
I wish more people would celebrate Tang's works as a genuine breakthrough, rather than a pin that's bursting the bubble of quantum computing hype.
Relevant reading: "Replication of Quantum Factorisation Records with an
8-bit Home Computer, an Abacus, and a Dog" by Peter Gutmann and Stephan Neuhaus [0].
Shows in a humorous way how the vast majority of quantum computing "records" are utter nonsense based on simplifying the factorization so far, that it turns into a problem on the difficulty level of "factorize 9" - _before_ running the experiment.
Journalists however tend to lack the knowledge to accurately represent that, resulting in nonsensical record claims.
Very hot take but this result made me believe that BQP and P might be equivalent computational classes (in other words, quantum computers might not offer any computational complexity speedups at all). I found out about this result in college and implemented the algorithm described in the paper for a class project, though I don't remember the code working very well haha
When you read it, keep in mind it's from 2018. Otherwise it looks as if Tang was 7 or so when he started to work on the problem. In reality, he already was 17 (*).
A recommendation is in the domain of subjectivity, meaning that there is no consensus on the correctness... so, even if the algorithm is faster, its usefulness shouldn't be superior to a random pick based on some matching criteria... which is already as fast as it can be
You're mixing up two things here. It doesn't really matter if the recommendation algorithm is good or not.
The advancement isn't that we now have a better recommendation algorithm, it's that we thought that there was a problem that was impossible to solve with current computers and was being used as example of a problem that only quantum computing could solve and we've now learned that that isn't the case.
It's a theoretical result. There was a problem believed to take exponential time on a classical computer but polynomial time on a quantum computer. It turns out to be solvable in polynomial time on both types of computer, removing the quantum exponential speedup. Whether one polynomial was bigger or smaller than the other wasn't of much interest, as I understand it. The surprise was just that both are polynomials.
Readit News
https://ewintang.com/assets/tang_thesis.pdf
https://www.quantamagazine.org/what-is-the-true-promise-of-q...
Edit: in light of a couple comments here I would like to say the podcast interview with Tang was this year. (May 3, 2025)
Venture capitalists love this type of story, because its sells the most funding in future rounds.
I wish more people would celebrate Tang's works as a genuine breakthrough, rather than a pin that's bursting the bubble of quantum computing hype.
Shows in a humorous way how the vast majority of quantum computing "records" are utter nonsense based on simplifying the factorization so far, that it turns into a problem on the difficulty level of "factorize 9" - _before_ running the experiment.
Journalists however tend to lack the knowledge to accurately represent that, resulting in nonsensical record claims.
[0]: https://eprint.iacr.org/2025/1237.pdf
Major Quantum Computing Advance Made Obsolete by Teenager (2018) - https://news.ycombinator.com/item?id=28413023 - Sept 2021 (44 comments)
Teenager Finds Classical Alternative to Quantum Recommendation Algorithm - https://news.ycombinator.com/item?id=17654220 - July 2018 (216 comments)
Customers who liked this Recommendation Engine may also like its Dequantization - https://news.ycombinator.com/item?id=17519001 - July 2018 (30 comments)
(Thanks to all who mentioned the year - we've since added to the title above.)
(*) yes, I know that it still very precocious.
The advancement isn't that we now have a better recommendation algorithm, it's that we thought that there was a problem that was impossible to solve with current computers and was being used as example of a problem that only quantum computing could solve and we've now learned that that isn't the case.
this is a recommendation right? hard to understand your point here
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