Quadratic memory reductions for Zero-knowledge Proofs
21–25 of 25 posts
Re: Quadratic memory reductions for Zero-knowledge Proofs
#22This entity is sentient enough not to publish on arxiv medrxiv or biorxiv, where they will surely be red-flagged for self citations and single-authorship Their most believable and unsensational works are in generative histopathology http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e23500 https://doi.org/10.1200/jco.2023.41.16_suppl.e13592 Meeting abstracts (you can think of them as posters or talks given by interns) >…
> they will surely be red-flagged for self citations and single-authorship Where is the problem with single-authorship?
Re: Quadratic memory reductions for Zero-knowledge Proofs
#23I've been thinking about ZKP's a lot recently. Using them we could perhaps build interesting and useful decentralised social media protocols. You could create a union at your workplace where you make agreements with everyone but you only communicate directly with your closest colleagues. You could create anonymous groups of doctors in a certain region that listen to reggae three times a week that think it would be wo…
The problem is the same problem with crypto dao projects - cryptographic certainties only apply to mathematical structures; you can't validate that someone actually holds a quality until you can embed that digitally. That turns out to be very hard to do for most things.
As I understand it, you can do arbitrary computations on https responses and prove that you didn't tamper with the response or the computation.
Re: Quadratic memory reductions for Zero-knowledge Proofs
#24Is this real or AI?
The person seems real, unless he faked his TedX talk 2 years ago https://www.youtube.com/watch?v=Et5HC8SR0BA or 2700 followers on LI https://www.linkedin.com/in/logan-nye/ along with the company, a cofounder etc. The volume and breadth of publications is unreal. e.g. Quantum Extensions to the Einstein Field Equations - 10 citations https://www.scirp.org/pdf/jhepgc2024104_362181145.pdf
He's a real person. His TedX talk is about applying AI medicine. Now medicine has so far been one of the least useful ways of applying LLMs/AI but even in areas where its been effective, it's problem is no one is that much of expert 'cause the AI is doing the "thinking" (prompt-"engineering" isn't nothing, it just isn't that hard to pick-up and has to be constantly changing and simplifying as the models improve).
And the thing about his "amazing" output is that it has all the ear-marks of someone who lightly editing "brilliant" LLM hallucinations. Just the case of Quantum Extensions to the Einstein Field Equations; this is either going to be big advance with thousands of citations or it will bogus (and paid placement - that's negative credibility, less credible than just an bare ArchiveX upload).
So, sure he's real. His claims, on the other hand...
Edit: And the thing about the stream of "genius" ideas is that LLMs seem to be inspiring many people with the approach of bouncing ideas off the chat-thing, having the chat-thing fill the ideas with seemingly plausible phrases and math (most of which makes sense) and reach the point where they seem to have created an earth shattering advance - especially in fields they didn't know in any depth. Notably, cranks have been common in many fields already but this allows cranks to proceed without the former markers of crankdom. And that presents some challenges to a variety of fields.
Re: Quadratic memory reductions for Zero-knowledge Proofs
#25Earlier quoted context omitted.
The person seems real, unless he faked his TedX talk 2 years ago https://www.youtube.com/watch?v=Et5HC8SR0BA or 2700 followers on LI https://www.linkedin.com/in/logan-nye/ along with the company, a cofounder etc. The volume and breadth of publications is unreal. e.g. Quantum Extensions to the Einstein Field Equations - 10 citations https://www.scirp.org/pdf/jhepgc2024104_362181145.pdf
Your links give a plausible picture but apparently not in the terms you're thinking. He's a real person. His TedX talk is about applying AI medicine. Now medicine has so far been one of the least useful ways of applying LLMs/AI but even in areas where its been effective, it's problem is no one is that much of expert 'cause the AI is doing the "thinking" (prompt-"engineering" isn't nothing, it just isn't that hard to…