Fetch.ai

About Fetch.ai

Fetch.ai is an innovative project building an open access, decentralized machine learning network based on a distributed ledger. The Fetch.ai platform aims to enable smart infrastructure and autonomous software agents to carry out complex coordination tasks.

The project was founded in 2017 by a team of academics and researchers led by CEO Humayun Sheikh and CTO Toby Simpson. It is headquartered in Cambridge, UK. The goal of Fetch.ai is to build an intelligent and scalable network that can adapt and learn in order to optimize operations for diverse applications.

Overview of the Fetch.ai Platform

The Fetch.ai platform combines artificial intelligence, multi-agent systems, decentralized technologies and cryptography to create an environment where software agents can autonomously provide services while coordinating complex tasks.

At the core of the platform is an open-source ledger based on a high-performance DAG (directed acyclic graph) protocol optimized for machine learning. On top of this sits the Fetch.ai Network which allows any hardware or software agent to request or provide services to other agents while maintaining privacy and security.

Some key components of the Fetch.ai system include:

• Autonomous Economic Agents – self-governing software agents that can enter into contracts with other agents to exchange data or provide services.
• Decentralized Oracle Model – allows agents to securely retrieve off-chain data to inform on-chain activity.
• Consensus Mechanism – coordinates multi-agent activity on the platform.
• Smart Ledger – maintains integrity while scaling high transaction throughput.

Use Cases for the Fetch.ai Network

There are many potential applications for Fetch.ai’s decentralized agent coordination platform, including:

1. Smart Cities – Managing transportation systems, energy grids, waste disposal logistics etc. Highly complex environments that can benefit from automated coordination.
2. Supply Chains – Tracking and managing supply chains with many diverse hardware and software agents interacting. Can optimize based on delivery timetables, cost savings and more.
3. Healthcare – Securely sharing patient data while coordinating disparate healthcare resources and personnel. Could enable personalized medicine powered by AIs.
4. Finance – Automated trading algorithms and risk models that leverage decentralized data feeds and exchange resources with other algorithms.
5. Industrial IoT – Monitoring of industrial equipment, predictive maintenance powered by machine learning models. Automated coordination of factories, warehouses etc.
6. Sharing Economies – Powering sharing ecosystems allowing providers and consumers to discover and contract services. Can cover ride-sharing, WiFi sharing, computer power sharing etc.
7. Data Markets – Creating markets for data exchange between data providers, consumers, AI and analytics systems in a decentralized way.

The platform is flexible allowing diverse implementations across many economic verticals.

Fetch.ai’s FET Tokens

The utility token that powers activity on the Fetch.ai network is called FET. All economic transactions between agents require FET payments. The tokens have multiple purposes:

1. Staking – FET is used to stake as collateral in order to run nodes or participate in network validation. This helps secure the ledger.
2. Transactions – Required to pay network fees for executing smart contracts and data requests between agents. Ensures quality of service.
3. Incentives – Agents are rewarded in FET for providing data or services that bring value to other participants.
4. Governance – FET tokens allow holders to participate in network governance matters like voting on upgrades.

At the time of writing, the max supply of FET tokens is capped at 1.15 billion. Around 80% of the total supply has been pre-mined. Nearly 15% of the supply was sold during Fetch’s 2017 and 2021 IEO rounds on popular exchanges. Most of the remaining tokens are allotted to distributed rewards programs to incentivize participation.

Partnerships and Adoption

Fetch.ai has been proactive at pursuing partnerships and integrations to expand platform adoption.

Major partnerships sealed include collaborations with:

• Bosch – Exploring how Fetch.ai agents can optimize IoT environments.
• Travel Data Collective – Improving mobility across 7 smart cities by sharing travel data on Fetch.ai.
• Royal Bank of Canada – Experimenting with agents to automate bank processes.
• European Space Agency – Developing decentralized data sharing for Earth observation satellites.

Additionally, Fetch’s technology has already seen initial adoption for auto insurance products in some Asian markets as well as electric vehicle coordination projects in European cities.

These partnerships help validate the platform’s versatility and aid in driving further adoption. As development progresses, Fetch.ai aims to rapidly onboard more integration partners and launch applied implementations that highlight value.

Team and Roadmap

Fetch.ai is led by a solid team combining expertise across machine learning, artificial intelligence, decentralized systems as well as an entrepreneurial track record of successful tech ventures.

CEO Humayun Sheikh holds a PhD in Machine Learning and previously founded machine learning company Searchspace which was acquired by Apple in 2015 to accelerate their Siri product. He also has multiple patents in AI under his belt.

CTO Toby Simpson brings over 20 years of software engineering experience having worked at leading institutions like the European Space Agency and the University of Southampton.

The wider team includes over 60 scientists, engineers, blockchain experts and academics. Advisors include professors from Oxford and Cambridge who are renowned experts in machine learning, robotics, mathematics and more.

Fetch.ai continues to hit milestones set out in its roadmap for developing platform infrastructure as well as driving adoption. Recent achievements include mainnet launch in 2019, introduction of staking in 2021 and integrated Fetch.js web framework to simplify adoption.

Going forward, the project roadmap for 2022/23 indicates plans for decentralized governance implementation, further tools to ease integration, major version upgrades and launch of vertical specific data marketplaces.

Risks and Challenges

While Fetch.ai is strong on technical foundations, it faces challenges and risks typically incumbent on innovative decentralized network projects.

As a relatively new project building cutting edge technology, Fetch.ai is likely to face software issues and bugs during upgrades and integration – delaying some roadmap targets.

Widespread enterprise adoption also remains a longer term proposition. Real world implementation may uncover limitations requiring more ledger development and tooling. Regulatory oversight of autonomous software agents and data sharing remains an uncertainty.

Competition both from centralized conglomerates and decentralized projects also poses challenges to ecosystem growth. Ultimately Fetch’s success depends significantly on the utility value delivered by agents to drive sustained organic adoption.

There are also investment risks associated with holding the FET token which may experience high volatility in growth stage projects before establishing long term value.

Conclusion

In summary, Fetch.ai is an ambitious and highly innovative project at the intersection of artificial intelligence, decentralized technologies and cryptography. Their open access network for enabling intelligent agent coordination aims to provide the infrastructure for machine powered automation across diverse sectors.

They have already gained decent traction through partnerships for exploring integrations. But expanding real-world implementation to demonstrate functionality and value remains key.

If successful at driving large scale adoption over the coming years, Fetch.ai could establish itself as a foundational technology layer catalysing the ‘autonomous economy’ of the future. While challenges remain, the project shows promising long term potential.