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Aperture Alternatives
Similar projects and alternatives to aperture
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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ezkl
ezkl is an engine for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). Use it from Python, Javascript, or the command line.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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BitName
a permissionless decentralized trans-identical system with anonymity and user choice at its core
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better aperture alternative or higher similarity.
aperture reviews and mentions
Posts with mentions or reviews of aperture.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-01.
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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
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A note from our sponsor - SaaSHub
www.saashub.com | 27 Apr 2024
Stats
Basic aperture repo stats
25
227
7.7
8 days ago
lightninglabs/aperture is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of aperture is Go.
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