cuckoo
aperture
cuckoo | aperture | |
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8 | 25 | |
813 | 229 | |
- | 2.2% | |
4.3 | 8.0 | |
6 months ago | 14 days ago | |
C++ | Go | |
GNU General Public License v3.0 or later | MIT License |
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cuckoo
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mCaptcha: Open-source proof-of-work captcha for websites
Asymmetric PoW algorithms, such as Cuckoo Cycle [1] or the poorly named Equihash [2] (which is not a hash function) do not lend themselves to password hashing, since a given instance can have 0 or 1 or many solutions.
[1] https://github.com/tromp/cuckoo
[2] https://en.wikipedia.org/wiki/Equihash
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Crypto: My Part in Its Downfall
The full technical report describing the LOCKSS forerunner to bitcoin may be downloaded at [1]. Interestingly, LOCKSS used a memory bound Proof-of-Work, where both prover and verifier perform a random walk in a 1GB table. But the prover had to do this many times, to obtain some final hash with many leading zeroes. This was before the invention of asymmetric PoW systems like Cuckoo Cycle [2] where the PoW can be verified with no memory use.
[1] https://www.researchgate.net/publication/31869581_Preserving...
[2] https://github.com/tromp/cuckoo
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Is it possible a PoW that runs arbitrary algorithms?
A non-hashcash-style PoW scheme is Cuck(at)ooCycle.
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POW Captcha: a lightweight, self-hosted proof-of-work captcha
The use of scrypt as underlying hash function is a rather poor choice though, as scrypt's memory hardness makes PoW verification unnecessarily expensive.
It's perfectly possible to make a memory hard PoW that's instantly verifiable, by using something other than hashcash. Examples include Cuckoo Cycle [1], and Equihash [2].
[1] https://github.com/tromp/cuckoo
[2] https://en.wikipedia.org/wiki/Equihash
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Memory-bound trapdoor proof of work
Non-Solution #8: Cuckoo Cycle https://github.com/tromp/cuckoo Why: At least a few people have looked at it, and any attacker is far more likely to directly attack the blockchain itself, than my server (which doesn't get involved with the blockchain) Why not: The "mathematical specification" https://github.com/tromp/cuckoo/blob/master/doc/mathspec is woefully inadequate, their "C spec" focuses more on ASCII art than actual readability https://github.com/tromp/cuckoo/blob/master/doc/spec and as https://handshake.org/files/handshake.txt points out, cannot be easily adjusted in difficulty. Also, I would need to implement it from scratch, but I guess I'll have to do that anyway.
- IBM Creates First 2nm Chip
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Ask HN: What Kind of Threat Does Quantum Computing Pose to Bitcoin?
The hashcash proof-of-work scheme that bitcoin uses is vulnerable to Grover's quantum search algorithm, that can find a solution in the 2^76 search space for the current target difficulty in roughly sqrt(2^76) = 2^38 quantum hashing steps, for a 2^38 factor speedup.
Other proof-of-work schemes (e.g. finding cycles in graphs [1]) are not vulnerable to quantum speedup.
[1] https://github.com/tromp/cuckoo
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Theoretically, how much hashing power could a 'quantum computer' generate? And is any superpower close to having one yet, that we know of?
[1] https://github.com/tromp/cuckoo
aperture
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Decentralized Artificial Intelligence
It's valuable to examine the challenges in machine learning without assuming decentralization as a solution:
> High Cost and Resource Requirements
For training and local inferencing use, quantization may help. Problem becomes local via quantization vs. remote full tensor use. Solution may involve distributed inferencing. Techniques like model distillation can help create smaller, more efficient models for inferencing.
> Data Privacy
For training, some private datasets may be needed. For local inferencing use, determining what needs to be inferenced locally vs. what needs to be run remotely may be useful. Problem becomes privacy scope mapped onto a marketplace to mitigate high cost and resource requirements. Techniques like model explainability (versioning) and robustness testing can help build trust in AI systems.
Complying with data privacy regulations and ensuring that AI systems adhere to legal and ethical standards can be a challenge, especially in international contexts.
> Incentives
Instead of assuming the solution when considering the problem, we assume there is an incentive to either simply train a model or use one. Problem becomes financial rewards, data access agreements, or even altruistic motivations.
> Stale Data and Reproducibility
Both the code and datasets for training the model need to be updated. Inferencing needs RAG, so the augmented reference data needs to be updated as well. Anything updated might need some type of revision control, especially if that data (or code) results in poor output. Labeling data and knowledge transfer are another problems that needs revision control.
> Interoperability
We can assume a marketplace for a ML train/inference platform is needed. We have HuggingFace, for example. The problem here is likely based on the tendency for datasets to be private, such as in the case of Llama 2. Models contain the "essence" of the dataset, but we still need RAG to ground the responses.
There does exist one technology that may assist in solving most of these issues without assuming full decentralization, and that is the Lightning Network combined with the yet to be implemented 402 response code: https://github.com/lightninglabs/aperture
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Bitcoin is “logical currency choice for AI”
You are right, it's not a strawman argument. It's an ad hominem argument. I get them confused.
While this guy may be shady as they come, and I'm not a big fan personally, the idea of combining Lightning and 402 responses is very interesting, and one I've been thinking about since Joseph and Tadge wrote the Lightning paper.
There is a means to do this today: https://github.com/lightninglabs/aperture
Consider that these entities may become self-managing at some point in the near future. If they need to pay for calls to other models, crypto-payments can be useful because they include identity and payment in one function.
As far as the vendors go, I would agree that some of them don't care about the ethical considerations and they remain focused on grabbing marketshare. That said, it's likely there we be a multitude of models running and trying to get them all talking to each other and paying for the compute required for inferencing is going to be a pain.
While it is true that there have been scams and fraudulent activities in the cryptocurrency space, it is unfair to label all blockchains as scams. Many blockchain projects have legitimate use cases and are backed by reputable organizations.
The Lightning Network is not a cryptocurrency itself but rather a layer-two scaling solution built on top of existing blockchain networks, most notably Bitcoin. It is designed to facilitate faster and cheaper transactions by creating off-chain payment channels between participants, which has risk limited to the initial payment and subsequent updates to the contract. These payment channels allow for quicker and more cost-effective transactions, while the final settlement is recorded on the underlying blockchain.
In the case of the Lightning Network, Bitcoin is the underlying cryptocurrency used for value transfer and security, while the Lightning Network enables faster and more scalable transactions by leveraging the trustless nature of the blockchain.
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National Geographic lays off its last remaining staff writers
https://github.com/lightninglabs/aperture
I’m not sure if lsat.tech is having issues, looks like the protocol was recently renamed L402:
- 402: Aperture's Payment Required Revolutionizing Machine Learning Payments
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Digital collectibles / NFTs on Instagram are winding down
Crypto is useful. A very long time ago there was a conversation about killer use cases. People on the ethereum side of the room thought programmable chains were it. People on the Bitcoin side said it was micropayments and script based post dating.
I said that it was likely paying for compute resources that would be a killer use case. Implementing 402s would be that manifest: https://github.com/lightninglabs/aperture
Now we’re moving deep into the AI markets, this will be a thing, combining both.
That said, con artists will still try to hustle others.
- Stop Bitching About Ads and Push Browsers to Implement Aperture
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Cloudflare mitigates record-breaking 71M request-per-second DDoS attack
> what's stopping anyone from bridging a non-CN/RU Intranet to CN/RU-Intranet.
If someone were considering this, here's a means to do it with 402s: https://github.com/lightninglabs/aperture
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Private Keys for decentralized secure ID?
Check out LNURL-auth or perhaps LSATs
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Fees on Lightning Network Payments
https://lsat.tech/ with this authentication specification you can gate your content with lightning payments
- Aperture is a HTTP 402 reverse proxy
What are some alternatives?
nodeeditor - Qt Node Editor. Dataflow programming framework
beaker - An experimental peer-to-peer Web browser
osqp - The Operator Splitting QP Solver
lntip - tip discord users with Bitcoin through the Lightning Network
vroom - Vehicle Routing Open-source Optimization Machine
idmas - Identity Management System based on BIP0032; runs in Tails Live OS
2captcha-php - PHP package for easy integration with the API of 2captcha captcha solving service to bypass recaptcha, hcaptcha, funcaptcha, geetest and solve any other captchas.
etleneum - the centralized smart contract platform
LDOGE - LITEDOGE - Proof of Stake: 2.0 Proof, of work: Scrypt
now-boltwall - Vercel lambda deployment for a Nodejs Lightning-powered Paywall
Atomic - denis bider's Atomic library (C++, for Windows)
BitName - a permissionless decentralized trans-identical system with anonymity and user choice at its core