AI is making its way into our lives faster than ever before. Crypto is no exception, and below, you can check out the most important points of intersection where these two highly important entities meet.
4 important crypto-AI intersections
The “AirBnB for Graphics Cards” Model
The increasing use of AI and machine learning (ML) has led to a surge in demand for high-speed graphics cards, such as the Nvidia A100.
Consequently, a new market has emerged, similar to an “AirBnB for graphics cards,” enabling individuals and companies to lease out their unused GPU resources to support the requirements of AI researchers and developers.
Exploring the idea of an “AirBnB for graphics cards” comes with several significant technical challenges to consider:
It’s important to note that not all graphics cards are capable of handling every workload. It may sometimes be necessary to adapt training processes to account for increased latency. Additionally, the issue of verification can pose a challenge.
Token-Incentivized Reinforcement Learning from Human Feedback (RLHF)
It is unlikely that token incentivization will be effective for all applications of Reinforcement Learning from Human Feedback (RLHF).
The important consideration is identifying the appropriate frameworks for determining when token incentivization is appropriate for RLHF, and when cash payments such as USDC should be utilized instead.
Here are some important industries where the token-incentivized RHLF model could become applicable: medicine, engineering, architecture, law, finance and economics, scientific research, training and education, sustainability and environmental sciences, and more.
Zero-Knowledge Machine Learning (zkML)
Although blockchains are not aware of real-world events, it can be advantageous for them to be informed about occurrences outside their network.
This way, they can automatically transfer value based on the current state of affairs.
Authenticity in the Age of Deep Fakes
In today’s world where deep fakes are becoming more advanced, ensuring authenticity and trust in digital media is crucial.
One possible solution is to utilize public key cryptography, which enables creators to verify the authenticity of their content by signing it with their public key and putting their reputation at stake.
These are the most important issues to consider when mixing crypto with AI.
