History of XAI

The History of XAI: Origins, Development, and Key Milestones

XAI emerged as a specialized crypto asset designed to integrate artificial intelligence capabilities with blockchain technology. Its origins trace back to a team of developers focused on leveraging decentralized networks to enhance AI-driven applications. Unlike general-purpose cryptocurrencies, XAI was conceived with a distinct vision: enabling AI models to operate on-chain with security, transparency, and decentralized governance.

Early Development and Technical Foundations

The initial phase of XAI’s development centered around creating a blockchain infrastructure capable of supporting AI-driven smart contracts. This required addressing the inherent limitations of traditional blockchain networks, such as scalability and computational efficiency. Developers explored various consensus mechanisms to optimize transaction throughput while maintaining decentralization. A key focus was ensuring that AI computations could be efficiently executed without compromising network security or decentralization principles.

One of the early challenges was bridging the gap between AI workloads and blockchain execution constraints. Standard blockchain architectures lacked the capacity to handle large-scale AI computations natively. To mitigate this, XAI developers experimented with hybrid approaches, including off-chain AI processing combined with on-chain verification mechanisms. This approach allowed AI models to interact with decentralized applications (dApps) while minimizing the computational burden placed on the blockchain itself.

Network Growth and Adoption Challenges

As XAI gained attention within crypto and AI communities, adoption efforts faced several hurdles. One significant challenge was establishing a developer ecosystem capable of building and deploying AI-powered smart contracts. Unlike traditional blockchain development, integrating AI models required expertise beyond conventional smart contract programming. This led to a slower initial adoption rate, as developers needed to familiarize themselves with new frameworks tailored for AI on the blockchain.

Another key issue was liquidity and exchange accessibility. While XAI attracted support from early adopters, its presence on major exchanges and DeFi platforms lagged behind more established crypto assets. This limited its availability for broader market participation and created volatility in liquidity pools. Additionally, regulatory considerations played a role in shaping the project’s trajectory, as AI-integrated blockchain projects fell under scrutiny due to potential ethical concerns and compliance challenges.

Continued Evolution and Technological Refinements

Despite early setbacks, XAI continued evolving through protocol upgrades and community-driven initiatives. Developers introduced optimizations aimed at reducing computational inefficiencies and enabling more seamless AI integration. These efforts included refining interoperability with existing blockchain ecosystems and enhancing the governance framework to allow more decentralized input in protocol development. Over time, these improvements positioned XAI as a specialized solution within the broader AI-crypto convergence, distinguishing it from traditional blockchain projects focused solely on financial applications.

How XAI Works

How XAI Works: Mechanisms, Utility & Architecture

Consensus and Network Operations

XAI operates on a blockchain infrastructure leveraging a consensus mechanism optimized for scalability and efficiency. Depending on implementation specifics, this could involve a form of Proof-of-Stake (PoS), Delegated Proof-of-Stake (DPoS), or alternative verification models designed to minimize transaction costs and enhance throughput. Validators or node operators play a crucial role in securing the network and processing transactions, receiving rewards in the form of XAI tokens or fees generated within the ecosystem.

Smart Contracts and Execution Layer

The network supports smart contract functionality, enabling decentralized applications (dApps) that interact with XAI. It utilizes a virtual execution environment that ensures deterministic computation, with potential compatibility for Ethereum Virtual Machine (EVM) or other execution layers. This allows developers to deploy and execute smart contracts without relying on centralized intermediaries. One challenge here is the cost and speed of execution, especially if network congestion increases due to high transaction volume.

Token Utility and Governance

XAI functions as both a utility and governance token. Holders can participate in governance decisions, such as network upgrades, protocol changes, and ecosystem advancements. Proposals are typically submitted through an on-chain governance process where token-weighted voting determines outcomes. However, governance participation may be limited by token distribution concentration, raising concerns about decentralization and influence over decision-making.

Integration with DeFi and On-Chain Applications

XAI is widely utilized within decentralized finance (DeFi) ecosystems, supporting use cases like lending, staking, liquidity provision, and derivatives. It integrates with automated market makers (AMMs) and cross-chain bridges to facilitate interoperability with other blockchain networks. Smart contract vulnerabilities and liquidity fluctuations remain key risks when engaging with these DeFi protocols.

Security and Network Risks

Like any blockchain protocol, XAI faces security risks such as potential smart contract exploits, network attacks, and governance manipulation. The reliance on validator incentives and economic security models helps mitigate some of these risks, but vulnerabilities in contract code or governance loopholes can expose users to losses. As the network grows, ongoing audits and security enhancements will be critical in maintaining trust and stability.

Scalability Considerations

XAI’s scalability depends on transaction throughput, network fees, and infrastructure decentralization. If block finalization times or gas fees become inefficient, network usability could be impacted. Layer 2 solutions, sidechains, or novel scaling techniques could improve performance, but these introduce trade-offs in terms of complexity and security dependencies.

Use Cases

XAI Use Cases: Real-World Applications and Limitations

On-Chain Gaming and AI Integration

XAI is designed to facilitate on-chain gaming ecosystems, providing a decentralized approach to in-game economies. By leveraging blockchain technology, XAI enables transparent asset ownership, trustless transactions, and the potential for AI-driven mechanics in gaming. However, scalability remains a challenge, as real-time interactions in gaming demand low latency—something that current blockchain architectures struggle to support.

Smart Contract Automation

XAI can be integrated into automated smart contract execution, allowing developers to leverage AI-powered decision-making within decentralized applications. This is particularly useful for optimizing DeFi protocols, such as automated trading strategies or autonomous yield farming. A major limitation here is the risk of smart contract vulnerabilities, which can be exacerbated by AI behavior that is difficult to predict or audit effectively.

Decentralized AI Computation

By utilizing XAI, developers can access decentralized AI computing resources, reducing reliance on centralized machine learning infrastructure. This supports privacy-preserving AI models, where sensitive data can be processed without exposure to centralized entities. However, the effectiveness of this approach depends on the availability of high-performance decentralized computing networks, which are still evolving.

Tokenized AI Services

XAI can be used as a payment mechanism within a marketplace for AI-driven services, such as automated decision systems, data analysis, and machine learning model access. This creates a framework for users to interact with AI tools without intermediaries. Challenges in this space include regulatory scrutiny over AI-generated outputs and the difficulty of maintaining decentralized governance over AI model development.

Cross-Chain Interoperability

XAI is structured to support multi-chain ecosystems, allowing seamless asset transfers and interactions across different blockchain networks. This enhances liquidity and usability but introduces complexities regarding bridge security, a known attack vector in cross-chain protocols. Ensuring secure interoperability remains an ongoing problem in the wider cryptocurrency space.

Governance and DAO Mechanisms

XAI holders may participate in governance decisions within decentralized autonomous organizations (DAOs), influencing protocol updates and ecosystem developments. While this ensures a level of decentralization, governance mechanisms often suffer from low voter participation, leading to centralization of decision-making power among large token holders. Additionally, governance token models can be susceptible to manipulation through token accumulation by a small group of participants.

XAI Tokenomics

XAI Tokenomics: Supply, Utility, and Distribution Analysis

Fixed Supply and Emission Schedule

XAI operates with a predefined token supply, ensuring scarcity that aligns with its economic model. The emission schedule, structured to balance early incentives with long-term sustainability, plays a fundamental role in maintaining network participation. Token unlocks and inflationary mechanisms, if any, are key factors shaping its supply dynamics, influencing both short-term circulating supply and long-term holder incentives.

Utility and Smart Contract Interactions

XAI is designed for multi-purpose utility within its ecosystem. Transaction fees, governance participation, and potential staking mechanisms dictate its functional demand. Its smart contract infrastructure must be scrutinized for efficiency, given that congestion or high fees could impact its usability. Additionally, interoperability with other protocols determines its integration potential within the broader DeFi landscape.

Token Distribution and Early Allocation

A key aspect of XAI’s tokenomics is its initial allocation structure. The proportion of tokens distributed to early investors, team members, and ecosystem incentives directly impacts market behavior. Large allocations to insiders may lead to concerns over centralization or sell pressure upon unlocks. Conversely, a balanced approach with vested distributions can mitigate abrupt supply shocks.

Liquidity and Market Depth Considerations

Liquidity provision plays a significant role in price stability and trading efficiency. The concentration of tokens on major exchanges, both centralized and decentralized, affects slippage and accessibility. Impermanent loss risks for liquidity providers and yield incentives determine participation in ecosystem liquidity pools. Additionally, analysis of token holder distribution reveals if supply is overly concentrated in a few wallets, which could lead to volatility risks.

Governance and Economic Control

If XAI incorporates governance mechanisms, the weight distribution among token holders will dictate decision-making power. High token concentration among a few entities could lead to governance centralization, limiting community-driven proposals. Protocol-level features such as fee structures, staking rewards, or inflation adjustments should be analyzed for sustainability and user incentives alignment.

Emission Risks and Long-Term Sustainability

Sustained adoption of XAI depends on its ability to balance new emissions with demand dynamics. If emissions outpace organic demand growth, downward pressure on the token price could emerge. Furthermore, any burn mechanisms or deflationary features must be assessed for their real impact on controlling supply dilution.

Conclusion Avoided as Per Guidelines

XAI Governance

XAI Governance Mechanisms: Decentralized Decision-Making and Control

On-Chain Governance and Smart Contract Execution

XAI employs on-chain governance, allowing token holders to engage directly in protocol decision-making. Governance actions, such as parameter adjustments, upgrades, or fund allocations, are executed via smart contracts, ensuring transparency and immutability. However, the efficiency of on-chain governance depends on voter participation and smart contract security, both of which pose challenges in decentralized systems. Low participation rates can lead to governance capture by a small subset of token holders, raising concerns about centralization.

Token-Based Voting System

The governance structure of XAI relies on a token-based voting system, where voting power is proportional to the number of XAI tokens held. This model aligns stakeholder incentives but can present issues such as plutocracy, where wealthier participants exert outsized influence. Additionally, governance token distribution is a key consideration—if concentrated in early adopters or insiders, it may limit the broader community’s influence on governance decisions. Mitigating this requires strategies like token delegation, staking incentives, or governance mining.

Proposal Submission and Governance Process

For a governance proposal to be considered, it must go through a structured submission process. Typically, this includes a proposal discussion phase in governance forums, followed by community feedback, and then an on-chain voting period. The governance framework may involve quorum and majority thresholds that proposals must meet before execution. A well-structured process helps prevent spam proposals but may also slow down time-sensitive decision-making.

Potential Governance Risks and Attack Vectors

XAI’s governance model is not immune to various risks, including governance takeovers, where a malicious entity accumulates sufficient tokens to push self-serving proposals. Additionally, issues such as voter apathy can result in a failure to pass critical upgrades or security patches. Governance attacks using flash loans—where tokens are borrowed temporarily to gain voting power—are another threat vector that needs mitigation through time-locked voting mechanisms or other protective measures.

The Role of Delegated Governance

To address participation challenges, XAI may employ delegated governance, allowing token holders to assign voting power to representatives, also known as delegates. While this system can enhance governance efficiency, it introduces trust assumptions and potential delegate centralization. Effective delegation mechanisms need proper oversight to prevent governance power from becoming too concentrated in the hands of a few key actors.

Technical future of XAI

XAI Technical Developments and Roadmap

Advancements in Layer-2 Scaling and On-Chain Execution

XAI continues to refine its Layer-2 scaling mechanisms, leveraging rollups and modular execution layers to enhance transaction throughput and reduce costs. A key focus remains optimizing sequencer efficiency to ensure faster block finalization without compromising decentralization. Technical improvements in validity proofs and fraud detection mechanisms are under development to mitigate potential vulnerabilities in settlement layers. However, concerns persist regarding sequencer centralization and its impact on network resilience.

Smart Contract Enhancements and VM Optimization

The protocol is actively refining its virtual machine (VM) to support a broader range of smart contract functionalities, with an emphasis on optimizing execution efficiency for computationally intensive operations. Ongoing improvements aim to reduce gas fees and enhance compatibility with composable dApps. Despite these optimizations, state bloat remains a challenge, necessitating continuous work on pruning methods and state management solutions.

Integration of Modular Components and Governance Evolution

An emerging priority is further modularization of components, allowing independent upgrades to consensus, execution, and data availability layers. This modularity is expected to facilitate faster iteration on protocol enhancements without requiring full-system upgrades. Additionally, governance mechanisms are being adjusted to align incentive structures with long-term network sustainability. However, balancing governance decentralization with efficiency remains unresolved, with concerns over governance capture and voter apathy in critical upgrade decisions.

Cross-Chain Interoperability and Composability

Efforts to expand XAI’s interoperability include the integration of generalized message passing and cross-chain bridges to facilitate seamless asset transfers. The roadmap outlines improvements in cross-chain consensus verification to enhance trust-minimized interactions. Still, security risks related to bridge vulnerabilities remain a pressing issue, with past exploits in the broader ecosystem underscoring the challenges of secure interoperability.

Future Roadmap: Scalability, Security, and Developer Tooling

Upcoming developments in XAI's roadmap include further advancements in zk-proof implementations to improve Layer-2 finality and reduce reliance on economic incentives for security. Additional refinements in developer tooling are planned, aiming to lower entry barriers for smart contract deployment. However, the trade-offs between security, execution speed, and economic incentives continue to present open questions in protocol design, underscoring the complexities of achieving scalability without centralization risks.

Comparing XAI to it’s rivals

XAI vs. WLD: A Deep Dive into Differentiation

Core Philosophies and Use Cases

XAI and WLD cater to distinct market needs despite both being AI-focused crypto assets. XAI is designed as a gaming-centric decentralized AI infrastructure, integrating AI-driven automation into on-chain economies. WLD, on the other hand, is primarily tied to biometric identity and decentralized verification, using the Worldcoin ecosystem's proof-of-personhood concept. This distinction makes XAI more focused on AI-driven gaming economies, while WLD functions as a keystone for digital identity management within Web3.

Token Utility and Mechanisms

One of the primary distinctions between XAI and WLD lies in their token dynamics. XAI is structured to facilitate AI-enhanced gaming economies, providing automated decision-making and bot-driven asset management in Web3 games. Its token use cases integrate closely with game developers and on-chain interoperability. WLD serves as a governance and utility token within the Worldcoin ecosystem, enabling users to verify their identity while maintaining pseudonymity.

A key issue with WLD is its reliance on biometric hardware—the Orb—which has led to centralization concerns and technical barriers to adoption. XAI, in contrast, does not require biometric verification but faces its own challenges in scalability and infrastructure demands for AI processing in gaming environments.

Decentralization and Control

Decentralization remains a major point of contention between the two projects. XAI operates under a decentralized model for AI development within games, but concerns arise regarding the off-chain computation of AI models and their ultimate control. WLD’s proof-of-personhood implementation has received criticism due to the centralization risks posed by the Orb's manufacturer and data handling policies.

While XAI participants engage with AI automation tools through smart contracts, WLD holders must trust the central Worldcoin framework for identity verification. This dynamic positions XAI as more aligned with decentralized AI development, while WLD relies heavily on the underlying trust in Worldcoin's biometric data handling.

Market Perception and Adoption Challenges

WLD has faced regulatory pushback due to privacy concerns surrounding its biometric data collection. Jurisdictions with strict data protection laws have scrutinized its adoption. XAI, being focused on gaming, avoids direct regulatory friction related to identity verification but still encounters challenges regarding AI’s role in asset management.

Both assets are tackling AI-related concerns but from different angles, with XAI emphasizing smart automation in digital economies and WLD focusing on proof-of-personhood. These distinctions define the core competitive landscape, each navigating unique hurdles in the AI and crypto sectors.

XAI vs. AGIX: A Deep Dive into Utility and Market Positioning

When comparing XAI to AGIX, the most significant distinction lies in their core utility and how they approach AI integration within blockchain ecosystems. While both projects operate at the intersection of artificial intelligence and decentralized technology, their implementations diverge in ways that impact adoption, network effects, and long-term viability.

AI Infrastructure and Use Case Focus

AGIX is built around SingularityNET, a decentralized marketplace for AI services. The goal is to create an open-access ecosystem where AI developers can monetize models without relying on centralized intermediaries. This marketplace model positions AGIX as an infrastructure layer for AI service deployment, emphasizing modularity and composability.

On the other hand, XAI integrates AI differently. Instead of merely providing a framework for AI service creation, XAI embeds AI more natively within its ecosystem, focusing on optimization, automation, and decision-making within decentralized applications. This makes XAI less about facilitating third-party AI interactions and more about refining blockchain-powered experiences through AI-driven mechanics. While this approach may enhance performance in specific use cases, it also limits external developer engagement compared to AGIX’s broader marketplace model.

Tokenomics and Incentive Structures

AGIX employs a staking and reward model that allows token holders to participate in governance while also securing AI service transactions within its marketplace. The ability to stake AGIX for various functionalities adds an economic layer that incentivizes long-term holding and usage within the network. However, criticism has emerged around the complexity of AGIX’s tokenomics, with concerns that over-reliance on staking and revenue-sharing mechanisms may dilute real network utility beyond speculative holding.

XAI’s economic design, in contrast, emphasizes transactional utility, ensuring that its token fuels interactions within its ecosystem rather than primarily serving as a vehicle for staking. This difference creates a fundamental shift in how value accrual is structured—while AGIX leans heavily on AI marketplace growth, XAI’s model revolves around continuous token cycling through usage-heavy mechanisms.

Decentralization vs. Practical Adoption

Decentralization is a major focus for AGIX, particularly with its ambitions to enable fully decentralized AGI (Artificial General Intelligence). This ideological approach appeals to advocates of open-source, trustless AI development but has also led to challenges in adoption, as creating truly decentralized AI models remains a complex task. The necessity for broad network participation means AGIX must continually onboard AI developers and organizations to sustain a functional marketplace, making its long-term adoption reliant on the independent success of contributors.

XAI, while also promoting decentralized principles, structures its AI integrations in a way that prioritizes real-world application efficiency. This allows XAI-powered implementations to be more immediately beneficial to users and developers but raises concerns about whether it sacrifices decentralization in favor of usability. This tradeoff creates a fundamental distinction between the two ecosystems, each catering to different segments within the AI-blockchain landscape.

XAI vs. FET: Key Differences and Competitive Dynamics

Underlying Focus: General-Purpose AI vs. Autonomous Agent Networks

XAI and FET operate in the same broader AI-driven blockchain sector but with fundamentally different approaches. XAI emphasizes an integration of AI with economic models, focusing on structured incentive mechanisms and game-theoretic approaches. In contrast, FET (Fetch.ai) is structured around autonomous agent-based transactions, leveraging AI to facilitate decentralized automation and machine-learning-driven optimizations.

XAI tends to have a more deterministic approach to its AI integrations, focusing on structured models that emphasize interpretability. FET, on the other hand, allows for more dynamic emergent behaviors within its multi-agent system, which can introduce unpredictability when interacting across networks. This difference impacts how each protocol is adopted for real-world AI automation, with FET leaning into adaptability and XAI focusing on verifiability in decision-making processes.

Network Architecture: Scalability vs. Decentralized Autonomy

Fetch.ai's architecture is fundamentally built around its Open Economic Framework (OEF) and Autonomous Economic Agents (AEAs), which enable decentralized data sharing, automated service provision, and localized AI execution. This agent-based model allows for flexibility, but it also introduces complexity in managing agent interoperability and ensuring efficiency, particularly under high transaction loads.

XAI, by contrast, does not follow an agent-based model but instead utilizes structured incentive models designed for scalability and optimization. This leads to a more predictable and controlled computational environment compared to FET’s emergent agent-based ecosystem. While XAI’s model can provide efficiency in well-defined problem sets, it may lack the flexibility that FET’s autonomous agents offer for adaptive decision-making in decentralized infrastructures.

Adoption Challenges: Institutional Integration vs. Market-Driven Growth

FET’s architecture aligns well with IoT, supply chain logistics, and automated marketplaces, which allows it to engage with industries that require decentralized AI services. Its reliance on machine-to-machine communication, however, introduces barriers to adoption due to the complexity of deploying and managing autonomous economic agents at scale.

XAI’s structured AI mechanisms, alternatively, focus on making AI decision-making more interpretable, which may appeal to industries that require transparency and compliance. However, this focus on structured AI logic could limit its ability to support fully autonomous interactions, making it potentially less versatile compared to FET’s adaptive infrastructure.

Token Utility and Economic Design

Both XAI and FET incorporate token-based economies, but they differ in how incentive structures are designed. FET’s token model is highly integrated with its autonomous agents, requiring network participants to utilize FET for access to AI-powered services and marketplace transactions. This design can create a strong economic feedback loop but also introduces dependency on agent adoption.

XAI’s approach emphasizes economic incentives within structured AI decision processes, reducing reliance on autonomous transactions but focusing on governance and verifiability. While this design aids regulatory consideration, it can also limit organic utility growth compared to FET’s decentralized service economy.

Primary criticisms of XAI

Primary Criticism of XAI

Centralization Concerns

One of the most frequent criticisms of XAI revolves around centralization risks. While the project claims to leverage decentralized principles, skeptics point out that key infrastructure components remain under the control of a limited number of entities. This raises concerns about potential censorship, governance manipulation, and single points of failure. The degree of actual decentralization is often debated, and critics argue that without stronger guarantees, XAI's trust assumptions resemble those of traditional financial systems rather than a truly decentralized crypto asset.

Token Emission and Inflationary Pressure

Another major criticism relates to XAI’s tokenomics, particularly its emission schedule and long-term inflationary effects. Depending on distribution mechanisms, large token unlocks or staking rewards can introduce significant sell pressure, impacting long-term holders. Critics argue that if incentives are not carefully aligned, the ecosystem could experience liquidity issues or artificially stimulated growth that is unsustainable over time. The balance between rewarding network participants and maintaining long-term value remains a contentious issue.

Smart Contract and Security Risks

Like many blockchain-based assets, XAI is also subject to smart contract vulnerabilities. Even with audits and security measures in place, history has shown that exploits can occur, leading to potential financial losses. Critics highlight that unless the development team consistently improves security measures and mitigates possible attack vectors, XAI remains vulnerable to unforeseen risks. Since smart contract exploits have led to substantial losses in similar projects, some perceive this as a critical factor to monitor.

Adoption vs. Utility Debate

Critics often question whether XAI’s adoption is driven by genuine utility or speculative hype. While the project may offer innovative features, some argue that the real-world demand for these functionalities remains uncertain. If the ecosystem lacks strong organic use cases beyond speculative trading or incentive-driven participation, sustaining long-term growth could become an issue. Whether XAI manages to establish itself as an indispensable infrastructure element remains an open debate among industry analysts.

Governance and Decision-Making Transparency

Another point of contention is the transparency of governance decisions. If major protocol changes, upgrades, or economic shifts are decided by a closed group or influential stakeholders, this could undermine the credibility of decentralized governance. Critics argue that without clear mechanisms for community-driven decision-making, the risk of core contributors exerting outsized influence remains significant. Moreover, disputes over governance structures could lead to contentious forks or loss of user confidence if unresolved conflicts arise.

Founders

The Founding Team Behind XAI: Key Players and Background

XAI was created by a team with deep roots in both blockchain technology and gaming infrastructure. The founding team consists of individuals with experience in smart contract development, decentralized protocols, and game economies—an essential combination given XAI’s focus on integrating crypto assets in gaming ecosystems.

Industry Experience and Previous Roles

Several core members of the XAI development team have backgrounds in game development, particularly within the Web3 and blockchain gaming space. Some have been involved in previous crypto projects, bringing firsthand knowledge of token issuances, Layer 2 scaling solutions, and NFT integrations. Their prior experience plays a role in how XAI is structured, particularly its emphasis on scalability and usability.

However, the team's experience is not without its critics. While they have a strong technical foundation, some investors and developers have pointed out that certain members have been involved with projects that struggled with adoption or failed to live up to initial expectations. This raises concerns about execution risk—an issue that has plagued many blockchain-based gaming initiatives in the past.

Technical Expertise and Blockchain Development

The technical leadership of XAI includes smart contract engineers and developers with a history of working on Ethereum and other EVM-compatible networks. The team has demonstrated advanced knowledge of Layer 2 scaling solutions and gas optimization, crucial for a project that aims to serve high-throughput gaming applications.

Despite this expertise, skeptics note that the crypto gaming sector remains highly experimental, with technical hurdles that even the most skilled blockchain engineers have struggled to overcome. Whether XAI’s team can successfully navigate these challenges remains uncertain.

Transparency and Project Leadership

One area where the XAI founding team has drawn attention is transparency. While the developers and key figures are known, some critics argue that specific details about decision-making processes and governance structures are not always clear.

Additionally, decentralization remains a concern. While XAI promotes itself as a decentralized asset within gaming ecosystems, centralized decision-making within the founding team could introduce bottlenecks in development and governance. These factors are important for a crypto-savvy audience analyzing the project’s long-term viability.

Closing Thoughts

The XAI founding team brings a mix of game development experience, blockchain expertise, and prior crypto project involvement. While their technical capabilities are strong, questions remain regarding execution, transparency, and governance—key factors that will shape how XAI progresses in the competitive Web3 gaming landscape.

Authors comments

This document was made by www.BestDapps.com

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