AlienRem

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MOSAIC: Motivation System for AI Collaboration

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Type SingularityNET RFP
Funding Request n/a
RFP Guidelines Develop a framework for AGI motivation systems

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Overview

MOSAIC aims to leverage the emerging collaborative dynamics of a design-focused social media platform to motivate collaborative world-building by all intelligences. On MOSAIC, users are able to mint design drafts, sketches, specs and requirements as NFTs, while matchmaking algorithms connect creators with potential collaborators possessing complementary skills. As these collaborations unfold, AI agents observe, participate, and learn about design processes. This project is grounded on a rigorous mathematical approach to AGI motivation that implements topos theoretical interpretations of logic and values through categorical semantics, building on Spivak's idea of Plausible Fiction and OLogs.

RFP Guidelines

Develop a framework for AGI motivation systems

Proposal Submission (7 days left)

Type SingularityNET RFP
Total RFP Funding $40,000 USD
Proposals 7
Awarded Projects n/a

SingularityNET

Apr. 14, 2025

Develop a modular and extensible framework for integrating various motivational systems into AGI architectures, supporting both human-like and "alien digital" intelligences. This could be done as a highly detailed and precise specification, or as a relatively simple software prototype with suggestions for generalization and extension. Bids are expected to range from $15,000 - $30,000.

Proposal Description

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Total Milestones
3
Total Budget
$20,000_USD
Last Updated
13 May 2025

Milestone 1 - Motivation for MOSAIC

Description

Initial documentation detailing the MOSAIC platform and the Desire Machine Architecture. The prototype for MOSAIC will be described in a technical white paper complemented by a survey that covers the mathematical foundations of our framework. The research plan consists of applying categorial semantics to describe behavioural patterns emerging in dynamical environments where humans and AI agents collaborate together thus evolving different sets of values desires and motivations. We provide motivation for our framework that highlights the potential benefits of the adoption of such a platform and the actual feasibility of our approach thanks to blockchain inspired technologies which also addresses privacy concerns.

Deliverables

Skeleton of the architecture and high level description of the platform. Mathematical considerations about existing SingularityNet technologies and research directions on the topic of AGI motivation. Discussion of expected benefits gained from the adoption of MOSAIC.

Budget

$8,000 USD

Success Criterion

Initial documentation and rigorous justification of the framework’s principles.

Milestone 2 - Core Functionalities

Description

High level description of main components of the MOSAIC platform consisting of: templates for design NFTs inspired by OLogs and devised with a modular approach AI powered matchmaking algorithm AI agents integration. Further development of the philosophy behind Plausible Fiction and Plausibly Factored Platforms.

Deliverables

Full prototype of MOSAIC. Templates for design NFTs. Schematics for the matchmaking algorithm and AI agents integration.

Budget

$8,000 USD

Success Criterion

Comprehensive high level description of core functionalities.

Milestone 3 - Community Bootstrapping

Description

Community bootstrapping via the creation of appropriate communication channels for the development and adoption of MOSAIC. Organization of community building activities such as design challenges with shared rewards as collaboration incentives. Sketches of privacy protocols following best practices in terms of user data safety.

Deliverables

Creation of dedicated communication channels around MOSAIC. Suggestions for initial adopters involvement. Verification of compliance with privacy best practices.

Budget

$4,000 USD

Success Criterion

Community initial set up.

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The weighted average of the 4 perspectives Overall

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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

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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

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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.

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