Very nice summary.
Hence reading through the comments ebbs and flows, I can’t help but to ask whether “standardizing” incumbent IoT data and providing “authenticity” would be the appropriate approach to automate data collection and preprocessing for AI applications. Forcefully making end users or consumers abide by a specific blockchains Smart contract might as well de-incentivize adoption of blockchain technology on the IoT layer of data collection.
In my opinion, blockchain can provide data authenticity and basic preprocessing via the Smart contract and that would be a huge advantage for streamlining the end to end of an AI applications development. Along side with block chain providing a more secure decentralized but also centralized data infrastructure, at the end of the day, providers of such blockchain infrastructure are still there to make money. Denying a means to obtain data and enforcing a more complex interfacing by the end user would be the life and death of said budding blockchain maintainers.
Then there is the issue of what it truly means to be “on chain”. With such large volumes of inflow, inevitably, there needs to be a form of a single source of truth. To my knowledge, a purely on chain approach to that “single source of truth” is yet to be available. I know of several Graph based technologies that may facilitate such “single source of truths” but even then, there are still drawbacks and compromises.
I also do concur that there needs to be further improvement on the existing network layer architectures. Lightning network for bitcoin, cardano being quite dismissive on doing anything more than networking on chain, and IOTA tangle being an aspiring resolution to the “on chain” data scalability issue.
I have this presentation for a past partnership proposal I tried to pitch to a blockchain company on the integration of Data science and Blockchain for aspiring Paas companies.
Please do tell me your thoughts about it.
-Tony