Expert Rating 3.3

simuliinc

Project Owner

Entangled Intelligence: Quantum Computing in AGI

Expert Rating

3.3

Type SingularityNET RFP
Funding Request $80,000 USD
RFP Guidelines Review of quantum computing technologies

Overview

By exploring this convergence between quantum and AGI, we glimpse the universe striving to understand its own infinite mind. AGI represents one of computing's most profound challenges, requiring scalable, efficient methods for differentiation, optimization, and information retrieval. Quantum computing (QC) offers a revolutionary approach to these compute-intensive processes, but separating hype from potential demands rigorous evaluation. This work examines three major QC paradigms—gate-based computing, quantum annealing, and measurement-based quantum computing—assessing their ability to accelerate AGI using tools like ZX calculus for cross-paradigm translation.

RFP Guidelines

Review of quantum computing technologies

Complete & Awarded

Type SingularityNET RFP
Total RFP Funding $80,000 USD
Proposals 10
Awarded Projects 1

SingularityNET

Oct. 4, 2024

This RFP seeks to critically evaluate the role of quantum computing in advancing Artificial General Intelligence (AGI). The goal is to distinguish between realistic capabilities and hype, providing clear insights into the practical benefits and limitations of quantum computing for AGI architectures, particularly within the OpenCog Hyperon framework. Part of this should involve interacting with the Hyperon team who've built the existing and in-development MeTTa interpreters.

Proposal Description

Company Name (if applicable)

Simuli Inc

Project details

PROBLEM

Current challenges:

Unclear distinction between quantum computing capabilities vs. hype in AGI
Hardware limitations in current MeTTa/Hyperon implementations
Need for systematic evaluation of quantum-classical hybrid approaches
Lack of clear integration pathway for quantum technologies in AGI
Limited understanding of practical AGI frameworks in quantum computing research
Insufficient differentiation between speculation and reality in current research

SOLUTION

Our approach centers on producing a comprehensive literature review that bridges quantum computing and AGI development, suitable for a peer reviewed journal.

Literature Review Abstract

In the entangled dance of probabilities, quantum computing offers not just a tool, but a paradigm shift—a way to rethink intelligence itself. Its promise is vast, but so are its challenges, lying at the intersection of physics, computation, neuroscience, and imagination. Despite groundbreaking advances, practical quantum computing remains limited by noise, scalability, and the nascent state of hardware and algorithms. For artificial general intelligence (AGI), these limitations pose critical barriers, yet also invite innovative solutions. This review explores three quantum computing paradigms—gate-based quantum computing, measurement-based quantum computing, and quantum annealing—assessing their applicability to AGI tasks such as optimization, reasoning, and learning. Additionally, we examine the need for transformative tools, such as hyperdimensional computing-based simulators and meta quantum compilers, to bridge the gap between classical and quantum AGI frameworks. By navigating the interplay of these paradigms and envisioning new hybrid tools, we aim to chart a path toward quantum AGI—a future where computation transcends its classical roots to achieve true general intelligence.

Analysis Report

We then compile a comprehensive report analysing technical and practical usefulness structured in several key phases:

Technical feasibility

We analyse the technical feasibility of current and near term quantum computing AI and AGI.
Foundation Analysis

Examination of quantum computing fundamentals, focusing on entanglement and quantum probabilities
Deep dive into AI and AGI research challenges and opportunities with respect to quantum computing
Analysis of current vs. future quantum compute abilities
Analysis of NISQC and FTQC paradigms in relation to ML/DL tasks
Exploration of hybrid quantum-classical architectures
Projected quantum AI roadmap

Integration with MeTTa/Hyperon and AGI as a field

Priority investigation of challenges and opportunities for current AI in the SingularityNet ecosystem
Practical considerations of current MeTTa/Hyperon integration with quantum computing
Design of quantum Hyperon framework
Design of quantum MeTTa framework
Exploration of HDC-based AI quantum simulators
Roadmap for integrating Hyperon with quantum

Future Vision Development

Assessment of emerging quantum paradigms and hardware
Investigation of quantum-AGI convergence opportunities and theoretical implications
Future opportunities for AI quantum computing based on projected quantum roadmap and implications for the AGI field and market

Each component will be developed through direct collaboration with the Hyperon team, ensuring practical applicability and alignment with current AGI development efforts.

PERFORMANCE METRICS

Research Coverage:

Review of major quantum computing paradigms
Number of peer-reviewed sources analyzed
Deliverable completion rate across milestones
Integration feasibility score for Hyperon framework
Clear quantification of quantum advantage in identified AGI tasks

Quality Metrics:

Minimum of 50 peer-reviewed sources
Analysis coverage of at least 3 major quantum paradigms
Technical review completion by Hyperon team
Clear framework for distinguishing hype from reality

USEFULNESS

Critical evaluation of quantum computing's role in AGI development
Practical guidance for SingularityNET/OpenCog's technology roadmap
Clear differentiation between viable applications vs. speculative claims
Actionable recommendations for Hyperon framework optimization
Educational resources for AGI engineers

COMPETITION AND USP UNIQUE STRENGTHS

Unique Strengths:

Direct collaboration with Hyperon team
Practical focus on implementation
Clear distinction between hype and reality
Integration-focused approach
ZX-calculus based analysis
Educational component for knowledge transfer

Competitive Advantages Over Existing Research:

Strong focus on practical implementation
Deep understanding of AGI frameworks
Clear methodology for differentiating speculation from reality
Educational resources development

Open Source Licensing

GNU GPL - GNU General Public License

Links and references

https://openaccess.thecvf.com/content/CVPR2024/html/Poduval_HDQMF_Holographic_Feature_Decomposition_Using_Quantum_Algorithms_CVPR_2024_paper.html

https://arxiv.org/abs/2406.11889

https://www.mdpi.com/1099-4300/25/3/449

https://pmc.ncbi.nlm.nih.gov/articles/PMC10606108/

https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2014.00063/full

https://arxiv.org/abs/1806.01421

Activity Summary

Milestones

4

Total

Discussion

0

Total Comments

Reviews

3

Total Posted

Project Team

2

Total People

Total Milestones
4
Total Budget
$80,000_USD
Last Updated
8 Dec 2024

Milestone 1 - Quantum Computing Paradigm Analysis

Description

Develop comprehensive research framework and conduct initial analysis of quantum computing paradigms relevant to AGI development focusing on gates annealers and hybrid systems. This phase establishes the theoretical foundation and analytical approach for the entire project.

Deliverables

Detailed research plan and methodology document Initial analysis of quantum computing paradigms Review of AI and AGI technical challenges Review of quantum computing paradigms Analysis of intersection between technical challenges and opportunities in AI and quantum Review of current AI quantum computing and near term capabilities Review of pseudo-quantum approach of Hyperdimensional Computing Projections on quantum AI computing roadmap

Budget

$20,000 USD

Success Criterion

Analysis covers at least 3 major quantum paradigms Minimum of 50 peer-reviewed sources identified Research methodology approved by Hyperon team Clear framework for distinguishing hype from reality established Submission to peer-reviewed journal

Milestone 2 - Technical Feasibility Assessment

Description

Deep technical evaluation of how quantum computing approaches can address specific AGI computational challenges with focus on practical implementation within the Hyperon framework through collaborative analysis with the development team.

Deliverables

Review of quantum technical capabilities and fundamentals Review of AGI/AI technical capabilities and fundamentals Analysis of existing AI quantum compute and feasible solutions Analysis of NISQC and FTQC paradigms in relation to ML/DL tasks Review of quantum-classical hybrid solutions in AI Projected quantum AI roadmap Detailed integration scenarios document Resource requirement analysis Scalability assessment report Updated technical findings documentation Refined use case specifications

Budget

$20,000 USD

Success Criterion

Complete analysis of hybrid quantum-classical approaches Resource requirements quantified for each scenario Integration pathways validated by technical team Clear differentiation between near-term vs future benefits

Milestone 3 - Integration Planning & Analysis

Description

Comprehensive analysis of integration pathways for quantum computing within AGI systems focusing on hybrid approaches and practical implementation strategies that address current technological limitations while preparing for future capabilities.

Deliverables

Review of current Hyperon bottlenecks Initial mapping of quantum approaches to AGI tasks Technical analysis report of MeTTa/Hyperon architecture Performance bottleneck analysis Quantum advantage calculations using ZX-calculus Initial use case specifications Preliminary integration assessment Design of Hyperon/MeTTa quantum integrations Roadmap of integrating quantum compute into SingularityNet

Budget

$20,000 USD

Success Criterion

Identification of at least 3 concrete use cases ZX-calculus analysis completed for key operations Technical review completed by Hyperon team Clear quantification of potential quantum advantages

Milestone 4 - Final Research Synthesis

Description

Final synthesis of all research findings technical analyses and integration planning into a comprehensive roadmap for quantum computing integration in AGI development with clear recommendations for immediate and future actions.

Deliverables

Final research report with actionable recommendations Integration roadmap for Hyperon framework Future research recommendations Presentation of findings to stakeholders Complete technical documentation package

Budget

$20,000 USD

Success Criterion

All claims supported by peer-reviewed sources Clear recommendations for at least 3 implementation paths Roadmap approved by Hyperon team Comprehensive hype vs. reality assessment completed

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Expert Ratings

Reviews & Ratings

Group Expert Rating (Final)

Overall

3.3

Feasibility 3.7
Desirabilty 3.3
Usefulness 3.7

Expert Review 1
Overall

1.0
- Compliance with RFP requirements 1.0
- Solution details and team expertise 1.0
- Value for money 1.0
proposal is incomplete

Expert Review 2
Overall

4.0
- Compliance with RFP requirements 5.0
- Solution details and team expertise 4.0
- Value for money 5.0
A very solid proposal with an engineering flavor, compellingly addressing the RFP requirements

This team seems highly competent to perform the tasks and their proposal makes sense and has a strong practical engineering flavor.... It does not go as far as some other proposals in terms of suggesting e.g. practical simulation modeling to flesh out / explore ideas, but it covers everything in the RFP super nicely.

Expert Review 3
Overall

5.0
- Compliance with RFP requirements 5.0
- Solution details and team expertise 5.0
- Value for money 5.0
Comprehensive proposal with good problem understanding and proposed approach.

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

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Review Summary

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The weighted average of the 4 perspectives Overall

3.3
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

3.7
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

3.7
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

3.3

Warning: Adding final group rating for this project will prevent expert users from adding new or editing existing reviews

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Review Conclusion(optional)

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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.

simuliinc

Project Owner

Co-Principal Investigator with expertise in AGI systems and pseudo-quantum computing, specializing in Hyperon and hyperdimensional computing implementations.

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Del Lucent

PI bringing expertise in computational physics, quantum mechanics education, and distributed computing. Stanford PhD in biophysics with focus on complex systems and teaching quantum computing.

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