Flare: Blockchain & AI synergy

1. Intro

Over the past few months, we have discussed in this blog the main protocols of the Flare Network, their role in data provision, Proof-of-Stake (PoS) migration, unlocking the value of non-smart contract tokens, and facilitating trustless cross-chain bridges. Achieving these goals is crucial to propelling this platform to the next level and making it amenable to novel applications like Artificial Intelligence and Machine Learning. The Flare Network’s developers have prioritized establishing a robust foundation for future applications that will open up new, previously untapped possibilities. Optimizing, refining, battletesting, and implementing native protocols are essential for introducing new cutting-edge use cases.

Flare’s team is developing a futureproof solution to unlock “A New Digital Economy for Data”. As we know, data plays an enormous role in today’s world. We leave digital footprints everywhere we go, every day. However, these footprints are often used in inefficient ways or exploited by third parties for their own purposes. Nevertheless, the amount of data we produce will certainly increase even more in a world where Web3 and IoT becomes a daily reality.

Number of Internet of Things (IoT) connected devices worldwide from 2019 to 2023, with forecasts from 2022 to 2030

Source: statista.com

Blockchain technology offers a secure and transparent way to store data and track transactions, eliminating the need for intermediaries. Machine learning (ML), a subset of artificial intelligence (AI), allows systems to learn from data and improve their performance. Combining these data-driven technologies can enhance data privacy, accuracy, and automation.

Data is poised to become the new oil in the future economy, where digital solutions will play a pivotal role in the system, fueled by a reliable and scalable data infrastructure, processed and analyzed by Machine Learning and Artificial Intelligence.

“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so data must be broken down, analyzed for it to have value.” — Clive Humby, 2006

Source: The Economist — David Parkins — May 6th 2017

This article will explain how machine learning and artificial intelligence can make the most of the data provided by the Flare Network. It will discuss how this combination can be used in a variety of applications and explore the potential benefits it offers.

2. Flare’s future usecases

Flare Network expands the boundaries of blockchain possibilities by providing developers with a data-rich playground for building next-generation decentralized applications (DApps) with innovative trustless bridging models. One such solution is the recently announced by Flare Labs , it’s called FAssets system.

The #FAssets system : Earn yield in dapps on #Flare or bridge to other ecosystems using #LayerCake, insured-in-transit bridging and cross-network composability protocol. Source: https://flare.network/layercake

For those unfamiliar with the FAssets concept, I will provide a brief overview. It is an innovative and complex system that seamlessly integrates tokens without smart contract functionality, such as XRP, BTC or DOGE, into the Flare ecosystem. This groundbreaking technology enables these tokens to operate within the secure smart contract environment of the Flare network, facilitating seamless interactions and simplifying their transfer to other EVM blockchains (via the LayerCake protocol). Unlike other wrapped asset systems, FAssets are trustless, meaning you no longer need to rely on a centralized intermediary to utilize your tokens with smart contracts. This is just one of many other advantages. Flare Labs’ solution empowers users to fully leverage the potential of their non-smart contract tokens and integrate them into decentralized applications (DeFi or NFTs), which are currently the primary cryptocurrency use cases.

The FAssets system is only one of the many potential future applications. The other use cases of the Flare Network can be divided into the following categories:

  • Bridging & Data Relay — Flare’s State Connector protocol proofs revolutionize cross-chain interoperability, ensuring secure and reliable data relay between blockchains. This enables developers to build applications that seamlessly integrate assets and data from multiple blockchain ecosystems, unlocking a wide range of new possibilities.
  • DeFi — Flare’s unique security model and data integrity enhancements open up new frontiers for DeFi applications. Developers can leverage Flare’s cheaper, higher-quality data feeds to build more robust and efficient DeFi protocols, attracting a broader range of users and expanding the reach of decentralized finance.
  • Real World Assets — Flare’s trustless traceability capabilities enable the creation of secure and transparent asset registries for real-world assets, such as securities, commodities, and collectibles. This empowers businesses and individuals to manage ownership and provenance with confidence, revolutionizing the way we track, trade, and value assets.
  • DAOs — Flare’s dynamic smart contracts can be used to build DAO structures that automatically respond to external events, such as price fluctuations, market conditions, or community votes. This automated decision-making capability introduces a new level of efficiency and scalability to DAO governance, enabling organizations to make informed decisions in real time.
  • NFTs — Flare’s versatility extends to NFTs, allowing developers to create NFT contracts that can be triggered or updated by external events. This opens up new possibilities for dynamic NFTs that react to changes in the real world or respond to specific user actions.
  • Cross-chain Entertainment — Flare’s ability to connect different blockchains and verify ownership of IP assets empowers the cross-chain entertainment industry. Developers can create platforms that seamlessly integrate web2 and web3 assets, enabling users to transfer and monetize their digital collectibles across multiple ecosystems.
  • Identity — Flare’s data integrity and decentralized nature make it an ideal foundation for defining digital identity. Developers can build applications that use Flare data to verify user identities, securely store personal information, and enable seamless authentication across different platforms.
  • Cross-border Payment Proofs — Flare’s cross-chain capabilities enable the creation of a global payment system that utilizes secure and transparent transaction proofs. This streamlines international payments, reduces fraud, and provides users with real-time confirmation of transactions.
  • Machine Learning — Flare’s secure and tamper-proof data environment provides a reliable platform for supporting and incentivizing the model training economy. Developers can create marketplaces where machine learning models can be trained and shared, fostering collaboration and innovation in the AI field.

3. AI/Machine Learning and Flare Network

Two technologies, namely Machine Learning (ML) and Artificial Intelligence (AI), alongside with Blockchain, are among the fastest-growing technologies worldwide. In recent years, they have profoundly impacted various aspects of life, ranging from business and finance to healthcare and education. According to a study by McKinsey, Artificial Intelligence and Machine Learning are projected to generate an additional $13 trillion of annual value by the year 2030. While Machine Learning already creates significant value within the software industry, I believe that even greater potential exists beyond this sphere, in sectors such as retail, travel, transportation, automotive, manufacturing, and so on. All of these sectors require reliable secure and scalable data, which Flare Network can provide. By enabling these sectors to leverage Flare Network’s data acquisition protocols, there is a vast potential to unlock a significant amount of value and elevate them to an entirely new level.

Source: https://www.mckinsey.com

Flare Network is the only smart contract platform optimized for decentralized data acquisition. It establishes itself as a “BLOCKCHAIN FOR DATA” that makes data available as a public good, essentially free of charge to the end-user. When combined with AI, Flare Network presents tremendous potential and a powerful tool for developing diverse use cases, enabling data to be used more efficiently and facilitating seamless interoperability between the networks.

The convergence of ML/AI and blockchain technology stands as a game-changer that is transforming many industries. Machine Learning drives a paradigm shift in data demands. AI, with its remarkable ability to navigate through vast amounts of data, enables their rapid analysis and utilization in previously unimaginable ways. By merging AI with blockchain’s strengths, we create a tool with endless potential.

Flare Network’s unique combination of security and data integrity positions it as an exceptional platform for nurturing and propelling the evolution of the Machine Learning and AI industry.

Security is crucial because the data used to train machine learning (ML) models is often confidential or sensitive. Flare Network offers a robust security framework for protecting data provided due to its mechanisms being integrated into the first layer of its blockchain architecture.

Data integrity is also crucial, as ML models must be trained on data that is accurate and consistent. Flare Network ensures data integrity by providing a data provisioning mechanism that consolidates data from decentralized entities, rewarding those who contribute the most precise feeds.

Flare’s tamper-proof data environment provides a solid bedrock for fostering high-quality ML models. Its cross-chain capabilities enable seamless and trustless exchange of data and models, immune to manipulation or corruption. This is essential for constructing robust and reliable applications. Developers can leverage Flare to foster decentralized marketplaces for the exchange and monetization of ML models.

Flare’s cross-chain interoperability unlocks vast potential for machine learning (ML) applications. By facilitating the seamless exchange of data and models across different blockchains, Flare enables the development of robust federated learning systems. Federated learning is a type of machine learning in which data is divided among multiple entities. Each entity keeps its data private, but it can share it with other entities for the purpose of training a model. These systems allow multiple parties to collaborate on training ML models without jeopardizing individual data privacy.

4. How AI can leverage data provided by the Flare Network

Let’s explore the potential and benefits of using data provided by Flare’s native protocols (FTSO and State Connector) by artificial intelligence (AI) in several sectors.

a) AI & Blockchian powered Transportation:

Flare Networks’ data provides valuable insights to enhance safety, optimize route planning, and minimize environmental impact. Predictive maintenance tools assist logistics companies in preventing equipment breakdowns and downtime. By utilizing this combination of reliable data and AI, logistics companies can effectively monitor traffic patterns, identify hazards, and guide drivers to safer routes. Additionally, this data can be employed to optimize transportation routes based on traffic conditions, weather, and fuel prices. By leveraging this valuable information, logistics companies can achieve cost savings, improved efficiency, and contribute to a more sustainable transportation system.

b) AI & Blockchian powered Manufacturing:

Data provided by Flare Networks can be utilized to enhance the efficiency, productivity, cost-effectiveness, and safety of manufacturing operations. For instance, Flare data can be harnessed to develop a machine learning model that forecasts machine failures. This model can be employed by businesses to schedule machine maintenance and mitigate unplanned downtime. By utilizing reliable data and AI in product design, manufacturing companies can devise products that are more efficient and effective. Flare data can also be employed to identify bottlenecks and inefficiencies in the manufacturing process. These insights can then be leveraged to optimize production processes, leading to improved productivity and reduced costs.

c) AI / Blockchian powered Agriculture:

The use of a combination of data provided by the Flare Network and AI in agriculture can contribute to enhancing the efficiency of crop yields and and improve safety. Crop yield forecasts can assist farmers make informed decisions regarding planting, harvesting, and irrigation. PPest and disease identification can help farmers protect their crops.

d) AI / Blockchian powered Commerce

AI and blockchain data can be leveraged to enhance customer experiences, drive sales, and personalize offerings across the commerce sector. For instance, reliable and trustworthy data delivered by the Flare Network can be harnessed to develop a Machine Learning model that can propose products and services most likely to captivate a given customer. This model can be employed by online stores and other commerce businesses to escalate conversion rates.

e) AI / Blockchian powered Financial Industry:

In the financial sector, data from the Flare network can be used to improve the accuracy of financial forecasts, the accuracy of searching for information about financial transactions, and the creation of new financial products and services. For example, Flare data can be used to create a machine learning model that can predict a customer’s credit risk. This model can be used by banks to make more informed lending decisions.

f) AI / Blockchian powered Healthcare:

Reliable and secure data provided by the Flare Network can be utilized to develop a machine learning model capable of identifying the early indications of diseases (such as Alzheimer’s) or develop new drugs that are more effective and have fewer side effects. The synergistic combination of blockchain and AI holds the potential to enhance diagnosis, treatment, and personalized healthcare. For instance, tracking patient genetics, lifestyle, and environmental factors can assist in providing patients with the most appropriate treatment. Additionally, storing and accessing data enables the rapid, secure, and private development of enhanced solutions and services.

Here are just a few examples of how reliable, accurate, and uncorrupted data can be used by artificial intelligence. The world generated 44 zettabytes of data in 2023. That’s equivalent to 44 trillion gigabytes or 44 billion terabytes. The amount of data generated is being driven by the rise of digitization and the proliferation of the Internet of Things (IoT). IoT devices, such as smartphones, computers, sensors, and wearables, generate massive amounts of data about our behaviors, location, and environment.

These data have the potential to transform many industries and sectors of the economy. They can be used to improve disease diagnosis and treatment, create new products and services, and even improve public safety. It’s an enormous amount of data that is growing at an exponential rate. In a world where data are being generated every day in unimaginable amounts, we can only imagine how great this potential is and how much the use of this data could change in the future with the use of blockchain and AI technology.

5. Outro

Artificial intelligence, Machine Learning, and Blockchain technology are three disruptive technologies with the potential to revolutionize a wide range of industries.

Flare Network provides a secure and reliable platform for developing and storing AI models. The network’s ability to transfer data and models between different blockchains enables collaboration and innovation in the field of AI.

The synergistic effect of combining ML and data provided by the Flare Network can be used to improve efficiency, security, and profitability in various sectors, such as transportation, manufacturing, agriculture, commerce, financial services, and healthcare.

AI can automate tasks, make decisions, and analyze data, while Flare Network blockchain ensures the security and transparency of data, as well as scalability and interoperability. As these technologies continue to evolve, their synergy will only deepen. AI can be used to enhance efficiency, security, and accuracy, while blockchain technology can be used to store and secure AI data.

Flare Network is a powerful platform for advancing the ML and AI industry thanks to its secure data environment, decentralized nature, and cross-chain interoperability. By providing a reliable data environment and collaborative opportunities for training, sharing, and monetizing ML models, this technology facilitates a new era of innovation and progress in AI.

*As the amount of data generated by IoT devices continues to grow exponentially, the potential applications for ML and Flare Network data will only expand.

Flare Network has the potential to become a key platform for machine learning and AI, as it offers a range of unique capabilities that can be used to improve the performance and scalability of these technologies. Whether Flare Network will indeed become a key platform for these use cases depends on various factors, including technological development, user adoption, and competition from other platforms. However, Flare’s potential is substantial, and the platform has the potential to play a major role in the development of Machine Learning and AI.

The future looks promising for both of these transformative technologies, as well as for the stake holders of the Flare network.

To fully grasp the potential of the Flare Network foundamentals please start here: https://medium.com/@focusfcx/flare-network-explain-it-to-me-like-i-am-5-years-old-ab1ba3593810

FAssets system — a recently announced solution for unlocking the value of non-smart contract tokens — was described in this article: https://medium.com/@focusfcx/why-is-it-taking-so-long-the-fassets-system-is-finally-incoming-66ab685b2f6e



Leave a Reply

Your email address will not be published. Required fields are marked *