aperture

acy 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 other 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. The use of the Lightning Network combined with a proposed 402 response code is an interesting concept for addressing some of these challenges: https://github.com/lightninglabs/aperture It could provide a decentralized and efficient way to facilitate payments for dataset access, training, and inferencing to incentivize data sharing and model usage.

ng 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. The Lightning Network can facilitate direct transactions between participants, regardless of the stability or availability of the underlying blockchain network. The Lightning Network operates by creating off-chain payment channels between users, allowing them to transact without needing to wait for on-chain confirmations. These off-chain transactions are fast and can be conducted privately between participants. The Lightning Network's design enables micropayments and facilitates instant settlement, making it suitable for various use cases, including direct transactions between model hosting companies or any other parties involved in AI services.