Web3 Technologies Show the Promise of Achieving the Original Vision Behind the World Wide Web

Ishan Pandey: Hi Kamal Ved, welcome to our series “Behind the Startup.” Please tell us about your journey and the motivation behind Fetch.ai?

Kamal Ved : I am a big fan of macroeconomics. If I apply macroeconomics growth theory to the impact of Web3 and AI innovations, I see the potential as an unprecedented increase in technological progress which in macroeconomics is referred to as Total Factor Productivity (TFP). And the beauty of an increased TFP is that you can achieve economic growth without having to increase capital and labour inputs. The motivation to create such a technology-led impact is what drives us at Fetch.ai where we are innovating and developing Web3 and AI-related products.

Ishan Pandey: What is an AI-based permissionless, decentralized machine-learning network and how will it help the crypto economy?

Kamal Ved : It is democratized access to data and AI (i.e. building ML models), where anyone can publish data and consume it with corresponding crypto incentives. The permissionless nature opens up access to data and AI to many who would otherwise not have this access.

Ishan Pandey: What does the Fetch-ai Network's current architecture look like? What kind of apps are presently running?

Kamal Ved: Fetch-ai Network is one of the Cosmos hubs within the Cosmos ecosystem that leverages the Cosmos SDK. We have DApps related to AI, DeFi automation, DeFi lending, DeFi derivatives, social media, sustainable mobility, supply chain and various other enterprise applications.

Ishan Pandey: Is the privacy of user data susceptible in decentralized networks, and if so, how do you protect it?

Kamal Ved: Fetch.ai uses agent technologies that can not only interact using the blockchain but also interact P2P with other agents. Agents can act autonomously and privately by making decisions based on the data from their peer agents while not revealing this information to its owner. Besides agent-based privacy, we also developed Dabbaflow product that allows the private sharing of data such as files by leveraging proxy re-encryption to hide information from the intermediate nodes that route this information.

We are also working on decentralized identity implementations that use zk-SNARKs to assert and verify a claim without revealing any additional information related to this identity.

Ishan Pandey: What are some of the challenges you anticipate in the adoption of your network?

Kamal Ved: Since all the technologies we use are from the deep tech domain, such as blockchain, cryptography and AI, there are many usability challenges that are still being worked on. For now, these usability challenges are limiting adoption to the innovators and early adopters.

Additionally, the space has spawned new models to raise money which has made capital easily accessible with lower due diligence. This has led to many bad actors scamming unsuspecting investors, which has given a bad rep to the space and an uncertain regulatory environment.

Ishan Pandey: What are your views on the future of Web3, AI and the current global economy?

Kamal Ved: Web3 technologies show the promise of achieving the original vision behind the world wide web to create true peer-to-peer commerce without centralized rent seekers. When you couple this with exponential growth in data, partially from Moore’s law and from the high availability of immutable data and code due to blockchain technology, you get perfect conditions for AI to become pervasive in our everyday life. Both Web3 and AI transcend geographical boundaries leading to an acceleration of globalization.

Ishan Pandey: Do you think there is a requirement to regulate Machine learning-based AI and Web3? If yes, how would regulations help the industry?

Kamal Ved: We are still in the early days of AI and Web3 technology evolution. As I mentioned earlier, on the Web3 side, we see bad actors capitalizing on investment influx from the unfettered exuberance of higher TFP. Similarly, we are still learning to develop unbiased AI models, which means there could be unintended consequences without proper legal oversight. In my opinion, these are two broad areas where the regulation could help.

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