Does Web3 Spell the End of AI Investing?
When people talk about Web3, I can’t help but notice an overarching theme of “extreme decentralization.” Since AI (artificial intelligence) has been so front-and-center in an era of centralized data and models, it’s not too surprising why people would skip ahead a few chapters and automatically assume that AI won’t have a prominent place in this new open-source digital ecosystem.
You’re probably already familiar with Web3, but in case you need a little refresher course, let me offer a quick synopsis.
What Is Web3?
Broadly speaking, Web3 is a theory about the next generation of the internet, and it will be built as a decentralized network, using technologies like blockchain and smart contracts. Now, there are many aspects of this digital infrastructure that we could cover, but for the sake of this discussion, let’s focus on three key takeaways:
- Web3 will be decentralized. Data and content will be built, operated, and owned by its users, not corporations, who will be running their own peer-to-peer networks.
- Web3 will be permissionless. There won’t be any control systems or “gatekeepers” in place to censor, block, or remove users from participating in the network.
- Web3 will be trustless. Any interactions or transactions will take place between two parties without requiring that they trust each other (or even know each other!). Third party platforms will no longer be necessary to establish mutual trust, as they are in web2.
For a broader explanation on Web3, check out this article from the Harvard Business Review. I also recommend reading this WIRED interview with Gavin Wood, the man who coined the term.
The Centralization of AI
Now let’s get back to the concept of centralization — particularly how it relates to AI. Most people have their own reasons for why they believe centralization is a problem — one being that it leaves little room for collaboration, and therefore, data becomes siloed.
But I’d argue that a bigger issue with centralized AI is the amount of money and effort it requires.
Consider that the innovative and emerging use cases for AI come from models that are trained in insanely massive datasets and comprise billions and billions of features. How you acquire, process, and distill down that much information — using the current thinking around data infrastructure and privacy — is if all of that data is centralized, collocated, and owned by the same entity/company.
Under this current infrastructure, the only way to utilize AI at its highest level dramatically shrinks the aperture of who can contribute to its usage and development.
This is where I see the main issue of centralized AI. Centralization (and its dollar cost) is choking off innovation. And as a result, AI is far from where it should be.
Here’s where I think most investors get stumped when they talk about Web3. As AI has largely thrived in centralization, their concern becomes how it will perform in a decentralized network.
This brings us back to the main question on the floor.
Is Web3 the End of AI Investing?
My response is…not likely. AI doesn’t have to be centralized in order to be effective. In fact, Web3 offers a unique opportunity for datasets.
One in particular is that the development of public blockchains will generate a preponderance of information that’s available to those who have access to that chain. The information will be public, verified by consensus, and complete going back to the start of the chain.
It goes without saying, but the more perfect the information, the better AI can perform. Therefore, I see AI playing a big role in Web3, simply for the fact that, if all goes to plan, we’ll have perfect information available in a public security domain, as well as in a format that is easier for computers to consume.
I also believe that some of the same data problems that exist in Web2 will continue in Web3, and therefore, there are new opportunities to bring the best data product learnings forward to the decentralized web — with minimal evolution.
Think about how decentralization can help companies that are currently leveraging data and transactional tracking. Heights Labs, for instance, monitors cash flows and transactions to help businesses identify money laundering and other financial crimes across the globe. Chainanalytics offers forecasting tools to aid companies in supply chain planning. Similarly, brands like Dune Analytics leverage on-chain crypto data, making it accessible and consumable to users via their digital dashboards. All three companies offer baseline business analytics. The information they need in order to provide these services is available, but it’s also hard to get to.
Investing in data products that could ultimately analyze and relay the information that’s available in Web3 may present a unique advantage for these companies and improve their capabilities. In turn, the need for this new technology provides an opportunity for data investors to intersect with Web3, as well.
Understanding How AI Will Intersect with Web3
I’ve given you a small taste of how AI and Web3 could intersect. In part 2 of this 3-part series, we’ll discuss a few other ways AI can thrive in a decentralized network.
