Leandro França de Mello

Project Owner

Quantum Lightning

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Type SingularityNET RFP
Funding Request n/a
RFP Guidelines Explore theoretical quantum computing models

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Overview

Funding cutting-edge research in quantum computing and post-quantum encryption. Our token utilizes quantum-resistant algorithms to ensure the security of your digital assets against future quantum computing attacks. Current cryptographic systems that secure most cryptocurrencies rely on mathematical problems that are difficult for classical computers to solve. However, quantum computers, using principles of quantum mechanics, can solve these same problems exponentially faster. Shor's algorithm, when implemented on a sufficiently powerful quantum computer, can break RSA and ECC encryption that secure most blockchain networks today.

RFP Guidelines

Explore theoretical quantum computing models

Proposal Submission (24 days left)

Type SingularityNET RFP
Total RFP Funding $100,000 USD
Proposals 1
Awarded Projects n/a

SingularityNET

Apr. 14, 2025

SingularityNET

rfp owner

Explore theoretical quantum computing models

Proposal Submission (24 days left)

This RFP seeks a technical and experimental assessment of quantum computing architectures in AGI applications. Proposals should explore the practicality and limitations of various quantum approaches — including trapped-ion, superconducting, photonic, and topological quantum computing — in handling probabilistic reasoning, parallel processing, and large-scale knowledge representation. The research could include quantum-classical hybrid simulations and feasibility studies for applying quantum advancements to AGI workloads. Bids are expected to range from $20,000 - $100,000.

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Proposal Description

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Total Milestones
4
Total Budget
$100,000_USD
Last Updated
15 Apr 2025

Milestone 1 - Algorithm Optimization

Description

Developing optimized implementations of post-quantum cryptographic algorithms specifically designed for blockchain environments, with a focus on minimizing computational overhead and storage requirements.

Deliverables

- FPGA and ASIC acceleration for verification - Memory-efficient hash-based signatures - Batch verification techniques

Budget

$25,000 USD

Success Criterion

Standardization Goals - Compatibility with NIST PQC standardization process - Clear migration path from existing cryptographic schemes - Formal security proofs or strong security reduction arguments

Milestone 2 - Protocol Security

Description

Analyzing the security of blockchain protocols against quantum threats and developing quantum-resistant alternatives that maintain the same functionality and security properties.

Deliverables

- Formal verification of quantum-resistant protocols - Side-channel resistance in implementations - Backward compatibility strategies

Budget

$25,000 USD

Success Criterion

Overall Protocol Success Criteria - Standardization acceptance by relevant industry bodies - Comprehensive security audit clearance with no critical vulnerabilities - Practical transaction throughput maintained (minimum 90% of pre-quantum levels) - Hardware compatibility with existing validator infrastructure - Wide adoption by major blockchain implementations

Milestone 3 - Cryptographic Agility

Description

Designing blockchain systems that can rapidly transition between cryptographic algorithms as vulnerabilities are discovered or as quantum computing advances.

Deliverables

- Modular cryptographic frameworks - Seamless algorithm transition mechanisms - Governance systems for crypto updates

Budget

$25,000 USD

Success Criterion

Overall Agility Success Criteria - Algorithm transition time under 90 days from decision to full network adoption - Multiple simultaneous algorithms support (minimum of 3 signature schemes) - Regular cryptographic review cycles (at least annual) - Backward compatibility with all historical signatures - Forward compatibility provisions for anticipated future algorithms - Recovery mechanisms in case of transition failures

Milestone 4 - Zero-Knowledge Proofs

Description

Developing quantum-resistant zero-knowledge proof systems for privacy-preserving blockchain applications that maintain their security properties against quantum adversaries.

Deliverables

- Lattice-based ZK proofs - SNARKs with post-quantum security - Private transaction protocols

Budget

$25,000 USD

Success Criterion

Adoption Criteria - Standardization potential aligned with NIST and other standards bodies - Open-source implementations with peer review - Reasonable transition path from current ZKP systems - Backward compatibility mechanisms during migration periods - Developer accessibility with comprehensive documentation and tooling

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The weighted average of the 4 perspectives Overall

0.0
Each RFP defines a maximum allowed budget, but teams can differentiate their proposal by offering a solution with a lower budget or a wider scope.Value for money

0.0
This rating indicates compliance to 'Must haves' but also adaptation of 'Nice to haves' and Non-functional requirements defined in the RFP.Compliance with RFP requirements

0.0
RFPs will offer varying degrees of freedom. This rating indicates the quality of the team's specific solution ideas, the provided details, and the reviewer's confidence in the team's ability to execute.Solution details and team expertise

0.0

Review Headline

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Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses. Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively). Feasibility (secondary) This represents the user\'s assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding. Viability (secondary) This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?” Examples:

A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.

Desirability (secondary) Even if the project team succeeds in creating a product, there is the question of market fit. Is this a project that fulfills an actual need? Is there a lot of competition already? Are the USPs of the project sufficient to make a difference? Example:

Creating a translation service from, say Spanish to English might be possible, but it\'s questionable if such a service would be able to get a significant share of the market

Usefulness (secondary) This is a crucial category that aligns with the main goal of the Deep Funding program. The question to be asked here is: “To what extent will this proposal help to grow the Decentralized AI Platform?” For proposals that develop or utilize an AI service on the platform, the question could be “How many API calls do we expect it to generate” (and how important / high-valued are these calls?). For a marketing proposal, the question could be “How large and well-aligned is the target audience?” Another question is related to how the budget is spent. Are the funds mainly used for value creation for the platform or on other things? Examples:

A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.

A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.

Leandro França de Mello

Project Owner

Specialized security researcher and blockchain developer with expertise in post-quantum cryptography and zero-knowledge proof systems. Focused on designing and implementing quantum-resistant protocols

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