Executive Summary
Exabits operates as a decentralized infrastructure designed for AI and computationally intensive applications. It empowers users by allowing them to contribute to the infrastructure and train their distinct AI models. Users can offer distributed GPU services, data storage, and expertise to AI communities without reliance on a central authority or intermediary. Participants leverage their web3 identities to engage in the marketplace and provide services to the AI ecosystem.
About the Project
Vision – Their vision is to build a dynamic digital ecosystem where users actively participate by providing computing resources, training machine learning models, sharing data, and gaining benefits. They want a future where knowledge and resources are shared freely.
Problem – The computing industry exhibits centralization, where a handful of organizations wield disproportionate power, leading to a singular point of failure and potential for censorship.
Solution – Exabits decentralized model redistributes power and control, mitigating the risks associated with centralized systems. Users can participate in the network, contributing computing resources and accessing services, creating a more inclusive and resilient computing environment. It is a decentralized infrastructure for AI and computationally intensive applications, enabling users to contribute to the Exabits infrastructure and train their AI models. The platform’s marketplace facilitates accessing and purchasing various AI-related services and resources, including computing services and data storage. This approach promotes fairness, efficiency, and performance in AI, nurturing the expansion of the AI ecosystem. This democratization of AI infrastructure enhances innovation and collaboration, driving the industry toward a more sustainable and equitable future.
Features
- Decentralized AI Infrastructure – Exabits focuses on establishing a decentralized platform for AI and computationally intensive applications, thereby promoting the development of an equitable and accessible AI ecosystem.
- Distributed GPU Services and Data Storage – The platform enables users to contribute their GPU services and data storage capabilities, thereby enhancing the diversity and capacity of the AI network.
- Marketplace for AI Services – Exabits provides a marketplace for AI-related services, including computing services, data storage, and Model as a Service (MaaS), fostering a competitive and efficient AI service environment.
- CONA architecture – The CONA architecture ensures flexibility, efficiency, and reliable transmission within the AI network, which is crucial for high-performance computing tasks.
- Available GPUs – With access to over 350k GPUs, Exabits leverages underutilized consumer GPUs, converting them into AI computing solutions.
Market Analysis
Market Picture – The Cloud Computing Market is currently valued at $0.68T in 2024, with projections indicating a growth to $1.44T by 2029, representing a Compound Annual Growth Rate (CAGR) of 16.40% during the forecast period (2024-2029). This growth is primarily attributed to the increasing demand for and adoption of AI and ML models, indicating significant potential for expansion within the sector.
The integration of blockchain technology has further enhanced the sector by providing improved use cases for decentralization. With a market cap of nearly $19B, the crypto AI market is experiencing robust growth, underscoring the increasing synergy between these technologies.
Team
Traction
The company boasts extensive experience in the field, with unique access to enterprise-grade H100 and A100 GPUs (and soon the new B200s) stemming from its longstanding presence in the data center business. They also have access to 350k GPUs to power the computing requirements. Exabits has partnered with projects such as io.net, Render Network, Akash Network, Aethir, and Solana to create an extensive, interconnected decentralized computing network. Exabits also incentivize market participants worldwide to contribute their computing resources in exchange for tokens.
Conclusion
Exabits’ commitment to tackling a significant challenge in the computing industry is underscored by its focus on providing highly effective solutions. The company has secured access to a large fleet of GPUs, enhancing its capacity to deliver cutting-edge computing services, and it has partnered with GPU marketplaces. Moreover, Exabits’ strong team of experts and professionals brings a wealth of experience and expertise to the project, further solidifying its position as a standout player in the industry. This combination of innovative solutions, strategic partnerships, and a talented team makes Exabits a compelling and noteworthy project poised to impact the computing landscape significantly.
| Fundamental Analysis | |||||
| Assessment | |||||
| Problem | Significant, long-term problem | 3 | |||
| Solution | Distinct, defensible solution | 3 | |||
| Market Size | Large market, significant growth potential | 3 | |||
| Competitors | Emerging market with few strong competitors | 3 | |||
| Unique Value Proposition | Some differentiation, but overlap with existing solutions | 2 | |||
| Current Traction | Early traction, user engagement starting to grow | 2 | |||
| Unit Economics | Positive unit economics, with plans for further improvement | 3 | |||
| Tokenomics | No clear token strategy or poorly conceived strategy | 1 | |||
| Product Roadmap | Basic roadmap, lacks detail or innovative features | 2 | |||
| Business Model | Proven business model with clear path to profitability | 3 | |||
| Go-to-Market Strategy | Basic GTM strategy, lacks detail or differentiation | 2 | |||
| Regulatory Risks | Minimal regulatory risk, strong mitigation and adaptability | 4 | |||
| Total | 64.58% | ||||
