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Intro

Hedera Hashgraph is a cutting-edge distributed ledger technology that redefines transaction processing through its innovative consensus algorithm known as Hashgraph. Designed with enterprise needs in mind, Hedera Hashgraph provides infrastructure that supports high-speed, secure, and cheap transactions, setting it apart from many traditional Layer 1 (L1) blockchains in the cryptocurrency space.

Hedera’s key technology, the Hashgraph consensus algorithm, is a proprietary technology that significantly enhances transaction speed and allows for the processing of thousands of transactions per second. With this capability unlocked, Hedera is able to offer a comprehensive suite of services that cater to developers seeking to build decentralized applications (dApps) ready for enterprise-level adoption. The platform's compatibility with smart contracts, facilitated through an optimized version of the Ethereum Virtual Machine (EVM), is a cornerstone of its functionality. This feature, part of the Hedera Smart Contract Service, enables intricate programmable logic embedded within transactions on the Hedera network.

Further extending its capabilities, Hedera incorporates a native tokenization service, which allows for the issuance and management of digital assets and cryptocurrencies directly on its network. Coupled with support for Non-Fungible Tokens (NFTs), these features make Hedera a versatile platform for developers aiming to innovate within the digital economy. Additionally, the Hedera Consensus Service offers a high-throughput mechanism for data writing and verification. This service is vital for applications requiring rapid and reliable data transactions, bolstering Hedera's appeal to sectors like decentralized finance (DeFi), where timely and accurate data processing is critical.

Technology

Hashgraph

Hedera is an open-source, public ledger that employs the Hashgraph consensus mechanism, which operates without a designated leader. This mechanism, known as "gossip-about-gossip" virtual voting, enables rapid and efficient communication across the network.

The term "gossip-about-gossip" refers to each node's method of relaying information to two other nodes selected at random, thereby propagating data exponentially across the network. This process ensures that all nodes receive all necessary information to reach consensus without the need for additional synchronization messages. The median time of message receipt across the network is then used to determine the order of transactions.

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Virtual voting is integral to Hedera’s leaderless structure, facilitating both high throughput and fairness in transaction ordering. This system does not merely record transactions linearly but rather integrates them into a directed acyclic graph known as the Hashgraph. This structure is crucial for achieving absolute finality in transactions, a core requirement in high-stakes environments such as financial applications.

EVM and Solidity

The Hedera Network provides a suite of advanced services collectively known as Hedera Network Services, designed to support the development of decentralized applications. These services include an optimized version of the Besu Ethereum Virtual Machine (EVM), known as the Hedera Smart Contract Service, which facilitates the creation and management of smart contracts.

A large portion of Hedera’s value derives from its dApp ecosystem and the ability to attract developers to build atop Hedera. To support this endeavor, Hedera offers three core services: Solidity-based smart contracts, consensus services, and token services. Solidity, a programming language originally designed for Ethereum smart contracts, is integrated within Hedera, allowing developers to apply their existing skills and tools to construct dApps on the Hedera platform. 

Solidity, the go-to language for developing on the Ethereum blockchain, is purpose-built for crafting smart contracts. It draws syntactical inspiration from JavaScript and C++, offering a contract-oriented approach tailored to the unique demands of smart contract development. It offers developers the tools and features needed to craft complex decentralized applications, including inheritance, libraries, and user-defined types. After writing the smart contract in Solidity, it's compiled and deployed to the Ethereum network, where it gets a permanent address.

The smart contract feature on Hedera provides a mechanism for executing contracts autonomously with contract terms embedded directly in the code, enhancing transparency, security, and operational efficiency.

Hedera Token Service

In addition to this, Hedera offers a native tokenization service, the Hedera Token Service, which enables users to create and manage their own digital tokens. Furthermore, the Hedera Consensus Service is available for high-throughput data writing and verification, ensuring the integrity and speed of transactions across the network. By utilizing the hashgraph consensus algorithm, Hedera can process transactions more rapidly and with higher finality than traditional blockchain technologies. This makes it a suitable platform for diverse applications, including but not limited to finance, gaming, supply chain management, and more.

These integrated services provide developers with a robust toolkit to build, deploy, and manage decentralized applications efficiently. Each service is tailored to enhance the functionality and scalability of applications on the Hedera Network, making it an ideal platform for enterprises and developers looking to leverage blockchain technology for innovative and secure solutions.

The HBAR Token

Hedera Hashgraph's business model is strategically crafted to appeal to developers and enterprise clients by providing a robust, secure, and scalable platform. Central to Hedera's economic architecture is the HBAR token, which plays a multifaceted role within the network. It serves as the medium of exchange for transaction fees and other network services, facilitating the network's operational dynamics. Developers benefit from this ecosystem by potentially generating revenue through transaction fees charged to their apps and earning royalties through the Hedera Token Service.

Enterprise clients, on the other hand, find value in the Hedera network by using it to build and deploy decentralized applications that streamline business processes and enhance operational efficiencies. These applications, built on Hedera’s decentralized and secure infrastructure, offer enterprises a way to reduce costs and improve security compared to traditional centralized solutions, thereby achieving better overall efficiency and reliability in their operations.

Revenue generation for the Hedera network primarily comes from transaction fees associated with network services like transaction validation and smart contract execution. Additionally, revenue streams are bolstered by fees from the Hedera Token Service, which enables developers to issue and manage their own tokens on the network, adding a layer of financial utility and incentive.

Differentiators and Competitive Advantage

Hedera Hashgraph distinguishes itself in the competitive landscape of distributed ledger technologies by offering a platform that is not only performant and secure but also highly scalable, catering particularly to the needs of enterprise clients. This robust platform provides developers with an extensive toolkit and infrastructure necessary for creating and deploying complex dApps at Web2 scale.

Another standout feature of Hedera is the speed of its transactions and the irrevocability of its consensus outcomes. This guarantees that once a transaction is recorded, it cannot be altered, which is crucial for maintaining security and trust, particularly in financial applications. Hedera also ensures fair transaction ordering, which is maintained consistently across all network nodes, thereby preventing any node from disproportionately influencing the consensus process.

Moreover, Hedera offers predictable costs, protecting users from the often volatile transaction fees seen in other blockchain environments. Its capability to handle high volumes of transactions with minimal delay makes it a scalable solution for large-scale enterprise applications, particularly where rapid transaction processing is crucial, such as in payment processing or asset trading. This efficiency addresses common challenges like congestion and scalability issues faced by traditional blockchains, positioning Hedera as a superior choice for those requiring robust and high-performance blockchain solutions.

Hedera is not only just a technological entity but also a community-centered project overseen by the Hedera Governing Council, which includes up to 39 prestigious global organizations such as Google, Dell, IBM, and Boeing. This council ensures transparent and structured governance by involving community feedback through Hedera Improvement Proposals (HIPs). Members of the council operate network nodes, authorize transactions, and enact decisions made by the council. To manage various facets of the network effectively, the council operates through specialized committees. These committees, comprising representatives from member organizations along with Hedera staff and guest experts, focus on areas like council membership, corporate adoption, technical direction, financial management, compliance with legal and regulatory standards, and marketing initiatives.

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The combination of all these technological innovations under one protocol positions Hedera to capture certain niches that other L1s cannot practically, economically, or technologically accommodate. One such area is at the intersection of crypto and artificial intelligence (AI).

Crypto x AI

Artificial intelligence (AI) is a field of computer science that focuses on creating machines that can perform tasks that would typically require human intelligence. In the context of cryptocurrency, AI plays a crucial role in enhancing security, automating processes, and improving user experiences.

AI, with its advanced algorithms and predictive analysis capabilities, can offer sophisticated solutions for the challenges currently faced by cryptocurrency. Here are some ways AI can enhance cryptocurrency:

• Trusted Repository: Blockchain's immutability ensures that AI models and datasets stored on the network remain unchanged, creating trust in the integrity of the data.
• Data Sharing: With blockchain, AI researchers can securely share datasets without exposing them to unauthorized parties, maintaining privacy while facilitating collaboration.
• Model Training: By leveraging decentralized computing resources through blockchain, AI developers can distribute model training tasks across multiple nodes, speeding up the process.
• Incentivization: Token-based economies powered by cryptocurrencies incentivize participation in AI networks, rewarding individuals who contribute data, computational power, or algorithm improvements.
• Scalability: The convergence of AI with blockchain also addresses scalability and accessibility issues that are prevalent in traditional cloud-based AI services, which are often expensive and restrictive. Crypto-economic models, such as those employed by platforms like Gensyn, use tokens or other forms of cryptocurrency rewards to incentivize the contribution of computational resources by a wide array of participants. This approach reduces the costs associated with AI development and lowers the barriers to entry, fostering a diverse and dynamic ecosystem of AI innovation. By distributing computational tasks across a global network, decentralized AI can scale more effectively, meeting the increasing demand for AI services without the constraints imposed by centralized systems. This distributed model not only supports the development of more resilient and varied AI models but also taps into a broader spectrum of data sources and computational strategies, potentially culminating in less biased and more representative innovations.

Primary Crypto x AI Intersection Points

Large Language Models (LLMs)

One of the key components of AI is large language models (LLMs). These models enable machines to understand and generate human-like text by processing vast amounts of data. In the cryptocurrency space, LLMs have various applications, including:

• Automating complex tasks such as smart contract creation
• Improving natural language processing for better user interfaces in crypto platforms

The development and operation of large language models (LLMs) involve a two-phase process akin to human learning. Initially, these models undergo a pre-training stage where they are exposed to vast amounts of unlabeled text. This helps them learn linguistic patterns and relationships essential for understanding language structure, such as grammar and semantics. 

Following pre-training, LLMs enter the fine-tuning or inference stage. In this phase, they are specifically trained on task-relevant data, refining their capabilities to produce more accurate outputs. This process resembles a seasoned professional who applies learned skills to perform specific tasks more efficiently.

However, training LLMs raises significant ethical and practical concerns. These models' intensive computational demands are primarily met by GPUs, which are critical during both training and inference stages. As AI technologies proliferate, the need for computational resources continues to grow.

Moreover, the monopolization of AI development by a few large companies poses risks of power centralization. This could lead to restrictive practices such as high fees or regulatory manipulations, which are becoming more apparent with the increase in demand for AI technologies. Additionally, as machine learning becomes more integrated into various sectors, including healthcare and social media, the control over these technologies often remains with private companies, raising concerns over data privacy and the transparency of the algorithms used.

In response to these challenges, the integration of AI with blockchain technology offers a promising solution. This combination could lead to transformative changes by enhancing transparency, security, and decentralization in AI operations. Blockchain could serve as a secure method for storing and sharing AI data, ensuring its integrity and fostering trust among users.

Machine Learning

Machine learning (ML) models are computational frameworks that execute tasks without being directly programmed to do so, effectively acting as the intellect of an AI system. The operation of ML models is streamlined into a systematic pipeline that encompasses data collection, training, and inference, which are pivotal for the model's ability to learn and perform tasks.

Within the ML domain, there are primarily three modalities of learning: supervised, unsupervised, and reinforcement learning. Each has a unique approach to data interpretation and learning strategy.

• Supervised Learning: This learning paradigm operates under the guidance of a "teacher" who provides examples from which the model learns. For instance, a model trained to identify dogs from images would receive a dataset labeled with pictures of dogs. The model's objective is to learn the distinguishing features of dogs to accurately classify them among various animals.
• Unsupervised Learning: Unlike supervised learning, unsupervised learning does not rely on labeled datasets. Models, such as Large Language Models (LLMs) like GPT-4 and LLaMa, learn to identify patterns and relationships within the data autonomously. This form of learning is pivotal for understanding complex datasets without predefined categories or labels.
• Reinforcement Learning: This approach is characterized by a trial-and-error learning process, where the model learns to make decisions by receiving feedback from its environment. It's particularly effective in sequential decision-making tasks, including robotic control and strategic games like chess or Go, where the model improves its performance based on the outcomes of its actions.

Understanding the intricacies of ML models and their applications provides a comprehensive view of the AI landscape, highlighting the transformative potential of AI across various sectors. As technology advances, the distinction between the different types of learning and their practical applications becomes increasingly crucial for professionals navigating the field of artificial intelligence.

Neural Networks

Another important aspect of AI is neural networks. These networks are inspired by the structure and function of the human brain and are used in deep learning algorithms. In the context of cryptocurrency, neural networks have been employed for:

• Enhancing security features within blockchain technology by detecting fraudulent patterns and potential security breaches
• Enabling pattern recognition and decision-making with higher accuracy

New Risks Within Crypto x AI 

The convergence of artificial intelligence (AI) and cryptography represents a significant shift in how data is handled, models are trained, and inference is applied, profoundly impacting both fields. Yet, a central challenge remains: achieving a level of decentralization in AI that mirrors the autonomous nature of systems like Bitcoin, free from the influence of any single authority.

To understand how AI can achieve this level of decentralization, several key questions must be addressed:

1. Who can build these models? - The development of AI models traditionally requires significant resources and technical expertise, which can limit accessibility and control to a few well-equipped entities.
2. Who has the data? - Data is the cornerstone of AI. The ownership and control over data sources are crucial in determining who can train effective models.
3. Who has the resources? - Computational power and financial resources are necessary for training sophisticated AI models, often putting these capabilities beyond the reach of individuals or smaller organizations.
4. Who is creating products atop these models? - The applications and services developed using AI models can influence various sectors, but the creators of these products often dictate the technology's direction and implementation.

EQTY + Hedera

As AI continues to evolve and these new risks/questions emerge, regulatory bodies are increasingly focusing on ensuring these technologies are developed and implemented responsibly. In this context, EQTY Lab, a Los Angeles-based startup, has pioneered a novel approach using the Hedera blockchain to enhance the transparency and accountability of AI systems.

EQTY Lab has developed an AI Integrity Suite, an innovative solution that employs cryptography and the power of blockchain to trace the origins and attributes of large language models (LLMs). This technology aims to provide a clear and immutable audit trail of an AI model's development process. By recording every step of the model's creation on a blockchain, the suite makes it virtually impossible to alter any part of the model's history, thereby ensuring a high degree of transparency and security.

The application of EQTY Lab's technology could revolutionize how companies and regulators interact with and oversee AI technologies. By providing a transparent method to track and verify the components and behaviors of AI models, stakeholders can ensure these models are used safely and ethically. Furthermore, this approach aligns with global regulatory trends focusing on the safety and reliability of AI systems, as underscored by initiatives like the U.S. Commerce Department's new AI Safety Institute.

Accenture, a global consulting giant, is currently evaluating EQTY Lab’s technology in its AI lab in Brussels. The goal is to determine if this software can be scaled effectively to meet the needs of Accenture’s vast clientele, which includes many Fortune 100 companies. 

EQTY’S ClimateGPT

Looking to leverage its new technological unlocks within the world of climate science, EQTY Lab recently unveiled ClimateGPT on the Hugging Face community AI platform. ClimateGPT, developed in collaboration with Erasmus.AI and trained by Apptek, represents a new AI-led approach to tackling environmental issues. It is an ensemble of task-specific AI models that aims to enhance the reliability and transparency of climate data. This model supports over 20 languages and incorporates a substantial foundational model that consists of 7 billion parameters and more than 300 billion climate-specific tokens. Notably, the entire training process is powered by renewable energy, underscoring the project's commitment to sustainability.

By incorporating Hedera’s blockchain technology, EQTY Lab ensures that ClimateGPT adheres to the highest standards of data integrity and security. This integration empowers developers to build and deploy AI-driven applications with confidence in the authenticity and accuracy of the data being used.

With ClimateGPT available on the Hugging Face platform, developers worldwide now have access to a powerful tool for creating solutions that address critical environmental challenges. EQTY Lab's AI integrity fabric, which is part of this integration, provides an essential framework for authenticating, securing, and governing AI models. This setup not only fosters innovation but also ensures that such innovations are conducted responsibly and sustainably.

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Disclaimer: This report was commissioned by Swirl Labs. This research report is exactly that — a research report. It is not intended to serve as financial advice, nor should you blindly assume that any of the information is accurate without confirming through your own research. Bitcoin, cryptocurrencies, and other digital assets are incredibly risky and nothing in this report should be considered an endorsement to buy or sell any asset. Never invest more than you are willing to lose and understand the risk that you are taking. Do your own research. All information in this report is for educational purposes only and should not be the basis for any investment decisions that you make.