Autonomous Economic Agents in Web3, with Humayun Sheikh of Fetch.ai

TL;DR

Fetch.ai enables AI tasks to be executed in a distributed, decentralized way through autonomous economic agents that can make decisions and exchange value. Its stack combines these agents with Colearn for collective learning and an execution layer for carrying out tasks economically, helping individuals and small businesses automate work without building large centralized systems. Read on to see how agents, blockchains, marketplaces, and a taxi-search example fit together.

Transcript

okay so today I'm really happy to welcome on the show hamayan Shake uh co-founder and CEO of fetch. Welcome hi hey um good to be here Jamie good to see you so we were just catching up offline I haven't seen your new house you haven't seen my new house and you're renewing your wedding V in the summer so we're going to get together hopefully at some ... Read More

Key Insights

• 👻 Fetch.ai aims to decentralize AI execution and remove intermediaries, allowing more entities to participate in the AI boom and benefit from automation.
• ❓ The technology stack consists of autonomous economic agents, collective learning through colearn, and an execution layer for economic task execution.
• 🖐️ Marketplaces play a crucial role in enabling economic value exchange between agents, optimizing processes, and creating personalized and efficient user experiences.
• 👾 The partnership with Bosch demonstrates the growing interest in decentralized AI solutions and the need for interoperability and collaboration in the space.
• 😒 The paradigm shift towards decentralized AI and the use of sovereign agents has the potential to revolutionize industries such as search, e-commerce, and transportation.
• 🤗 Fetch.ai's approach aligns with the vision of a more open and user-centric internet, allowing individuals to have greater control over their data and interactions.
• 👶 The integration of decentralized AI with existing infrastructure, such as oracles and web2 services, is crucial for the adoption and scalability of these new systems.

Questions & Answers

Q: What are autonomous economic agents in Fetch.ai?

Autonomous economic agents are service-based software agents that act for individuals, businesses, or tasks. They can autonomously make delegated decisions, execute tasks, and operate in a decentralized, distributed system.

Q: How are autonomous economic agents different from traditional software agents?

Traditional software agents have long been used in settings such as games to execute actions, learn, and train. Fetch.ai extends that concept by giving agents economic agency and the ability to operate across a decentralized system instead of remaining on one centralized platform.

Q: What does the “economic” part of an autonomous economic agent mean?

An agent’s activity has economic value that may be visible or invisible, direct or indirect. The agent can create efficiencies and reduce costs by making autonomous decisions and executing tasks for a person or company.

Q: How does Fetch.ai decentralize AI execution?

Fetch.ai unbundles AI into constituent parts so tasks can be handled in a more distributed and decentralized way. Its stack includes autonomous economic agents, Colearn for collective learning, and an execution layer for carrying out tasks in an economic sense.

Q: Why does Fetch.ai want to remove intermediaries from AI?

Large centralized web platforms benefit from economies of scale and the datasets used to train their AI models. Fetch.ai aims to let more individuals, small businesses, and other entities participate in automation and in the value created by AI.

Q: How are autonomous economic agents similar to microservices?

Both approaches break a large monolithic system into smaller service-based components. Unlike centralized microservices that must remain on one platform, autonomous economic agents add economic agency and can operate in a decentralized, distributed manner.

Q: How do blockchains enable economic activity between agents?

Blockchains provide ledgers of account that support value exchange between agents. This makes it possible for interactions among autonomous agents to have an economic dimension.

Q: How could an autonomous economic agent help someone find a taxi?

A person could give an agent a requirement such as finding a taxi. The agent would turn that request into a search and locate the other side of the transaction, illustrating how even a narrow task can still be useful.

Summary & Key Takeaways

• Fetch.ai is building a software stack that unbundles AI into its constituent parts, enabling more distributed and decentralized execution of AI tasks.

• The goal is to remove intermediaries and AI monopolies, allowing individuals and small businesses to automate tasks and participate in the value created by AI.

• The technology stack consists of autonomous economic agents, colearn for collective learning, and an execution layer for executing tasks in an economic sense.