I'm no ai maximalist, quite the opposite in fact, and I have a great deal of sympathy for the author as a person from a similar trade. However perhaps he is being overly emotional in his response. Purists have been decrying the defilement of the trade for millennia - "but this time it's different!" no. you think the purest form of math is the one you were born into because you didn't know any other way. people were doing math before the abacus and will continue to do so afterwards. here a hot take even: there's no finite amount of math, if you really cared about math you would be excited about all the math you could uncover. the computer solving the jacobian conjecture isn't fulfilling enough for you? maybe start thinking about what this discovery implies then!
Besides, doing pure math as a vocation was and still is an incredibly niche and privileged profession that 1-O(e^-n) of the population had access to anyways. If anything we will need more mathematicians, more engineers and more physicists to keep up with the increased throughput. Maybe journals will finally start EMPLOYING (gasp!) some referees instead of relying on free labor from broke graduate students even!
I'm rather tired of this ai apologism bit where every downside is explained away as "it would've happened anyways". AI destroying people's brains and causing paychosis? They would've gone psychotic anyways! AI causing company culture problems? The company was toxic anyways!
Instruments are not inculpable as you think they are.
I dont know where that “Those who cannot do, teach” bullshit came from but it's absolute nonsense someone made up to dunk on teachers.
It doesnt even make sense in your post because "programming" isn't "doing computer science". You're not better than a teacher in any notion because you asked chatgpt to generate some slop.
This whole article is just a nothingburger. Saying something is applied topology is only one step more advanced than saying something is maths - duh. These mathematical abstractions are incredibly general and and you can pretty much draw up anything in terms of anything, the challenging part is being able to turn around and use the model/abstraction to say things about the thing you're abstracting. I don't think scholars have been very successful in that regard, less so this article.
Yeah deep learning is applied topology, it's also applied geometry, and probably applied algebra and I wouldn't be surprised if it was also applied number theory.
I'm sorry if this is nitpicky but your comment is hilarious to me - doubling something is doubling something, "changing the order of magnitude" would entail multiplication by 10.
Not only you're responding with an ad-hominem, which is blatantly bad enough; but you're doing it against Benjamin Franklin? One of the most influential thinkers of his time who has contributed to the liberty of way more people than you ever will?
Did you really think "they just call them grandma/pa" was a good argument against people not knowing their grandparents' names? What do you think people in other parts of the world call their grandparents?
Nowhere in the text you quoted (nor in the article body) it is said that simulation of this device can not be done. Had you read the paper you'd see that it _is_ about simulating this device. From the introduction: "After students are introduced to several projects in quantum computer simulation, they write code to simulate the operation of Mermin’s quantum device."
This is immaterial, however. It is a well known fact that BQP is in PSPACE and Clifford circuits (a subclass of quantum circuits) can not only be simulated classically, but done so efficiently. It is not controversial.
> there are known physical phenomena, such as quantum entanglement
QC researcher here, strictly speaking, this is false. Clifford circuits can be efficiently simulated classically and they exhibit entanglement. The bottom line is we're not entirely sure where the (purported) quantum speedups come from. It might have something to do with entanglement, but it's not enough by itself.
Re: about mermin's device, im not sure why you think it can not be simulated classically when all of the dynamics involved can be explained by 4x4 complex matrices.
I am not an expert on this but my suspicion is that human ear is not a linear time invariant system and thus it does not make sense to place a hard cutoff at some frequency over which you can not hear. The response might change wrt to the spectral content of the overall sound.
Quantum Computing is a topic that makes it to the front page from time to time and garners a lot of attention. I find this breakdown of short-term prospects of from QC very concise and readable.
You're talking in very vague terms here, what does """interesting""" mean?
Let me give you some numbers. Factorising RSA is order 10^6 logical qubits (and I'm being charitable here), simulating FoMoCo is around 10^7. The state of the art error correction is around (again, charitably) 10^3 physical qubits per logical qubit at the moment, that gives us 10^9-10^10 qubits necessary for the simplest quantum application. We're at order 100 right now.
Peter Shot thinks that error correction can go down to 100 physical-per-logical, that's an order of magnitude shaved off there, but the algorithm itself is pretty basic, i don't see it getting any better there. Simulation algorithms have much better odds in seeing improvements as I think the gates used there are rather non-standard and have avenues for better gate compilation techniques.
Quantum Computing/Information researcher here. This article is largely garbage, the original (~2 month old) paper is surprisingly readable [0] and I suggest you to check it out. Here's my $0.02: The efforts of the Google team is commendable in that they're trying to squeeze as much out of their noisy systems as possible until error correction is here (they need to, to justify their existence after all) and they are aware of the shortcomings of the paradigm. But personally I don't see anything useful coming out until error correction and number of qubits are improved many orders of magnitude to have fault tolerant QC. The jury is still out on their utility once realized; Shor's algorithm is an obvious one followed by quantum simulation algorithms that might benefit chemistry and fundamental physics, but it's not as big of a silver bullet as we thought before for simulation. Maybe someone can tell me what fast prime factorization is good for besides breaking encryption.
Also IBM released a paper[1] recently making similar claims ("quantum advantage without complete error correction") which got obliterated by 2 back to back papers [2,3] that did what they did for much cheaper on a classical computer.
If a real person (not a bot) can tweet more than a 100 tweets per hour (i.e. 1 tweet every 36 seconds on avg) I would call them mentally ill, not power users.