Blockchain emerged as a powerful response to political and organizational problems, rather than purely technical ones, but soon its technological potential had attracted the best minds in computer science. Together (and possibly more than) with Artificial Intelligence, Blockchain may revolutionize the Internet, but a question remains:
Could blockchain support the creation of better AI?
Pioneers in the field have been exploring various ideas, ranging from a decentralized way to create AI to networks of bots and fully autonomous organizations run by AI.
Putting it altogether, you can imagine a fully decentralized AI marketplace where people provide their data, developers compete to provide the best machine learning models, and the whole system works as a self-reinforcing network that attracts more and more participants and creates gradually better AI.
Machine learning models trained on data from blockchain-based marketplace might have the potential to create the world’s most powerful artificial intelligences. They combine two powerful features: private machine learning, which allows for training to be done on sensitive private data without revealing it, and blockchain-based incentives, which attracts the best data and models to make them smarter. The result is open marketplaces where anyone can sell their data while keeping it private.
Constructing these systems is challenging, but simple initial versions look like they are starting to become feasible, like the Bottos AI ecosystem, that may help us transition out of the current era of web 2.0 centralized data monopolies into a Web 3.0 era of open competition for data and algorithms, where both are directly transformed into value. In fact, data and model providers will be able to see they are getting the fair value of what they’ve shared since all computation is verifiable, making them far more likely to participate.
Incentives to attract data are the most potent part of the system as data tends to be the limiting factor for most machine learning applications. A properly engineered incentive structure for data would pull the best data and would be nearly impossible to shut down a system where data is coming from thousands or millions of sources.
Also, by creating open competition between models/algorithms in places where it previously didn’t exist, the development of artificial intelligence will skyrocket.
Multi-sided network effects from users, data providers, and data scientists make the system self-reinforcing. The better it performs, the more capital it attracts, which means more potential payouts, that will pull more data providers and data scientists who, in turn, contribute to make the system smarter.
In addition to the points given above, a major advantage is privacy. It allows people to submit data that otherwise would be too sensible to share and prevents the economic value of the data and models from leaking. If left unencrypted in the open, the data and models will be copied for free and used by others who have not contributed any work, giving rise to the so called “free rider” problem.
A partial solution to it is to privately sell data, even though buyers may resell or release it, thus forcing its value to decay with time. However, this approach restricts us to short duration use cases and still creates typical privacy concerns. As a result, the more complicated but powerful approach is to use a form of secure computation.
Beside all, it is clear that even though AI and blockchain may seem pretty distant technologies, in the near future they will end up working together and mainstream use is much closer than you may think. That’s why Bottos is working in towards that direction by not only creating an AI ecosystem based on blockchain, but building up a multi-layered infrastructure that will increase the growth and development of AI algorithms and models more than tenfold as for today. While not exclusively limited to AI, Bottos will nevertheless give a major shake to the industry and to the research and development in general, in the safest and cheapest way possible.
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