Rebecca_Spine

Project Owner

Spine Archive

Expert Rating

n/a

Type Community RFP
Funding Request n/a
RFP Guidelines Reputation and Voting Weight System

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Overview

The Spine Archives Pod Channel aims to create the world's most comprehensive spine health knowledge ecosystem. By transforming centuries of research into an AI-powered platform, we facilitate intelligent discovery and provide medical insights to healthcare professionals and patients alike. Our initiative focuses on preserving historical spine research, indexing literature, engineering knowledge frameworks, and developing AI agents to advance spine health.

RFP Guidelines

Reputation and Voting Weight System

Internal Proposal Review

Type Community RFP
Total RFP Funding $140,000 USD
Proposals 14
Awarded Projects n/a

Juana Attieh

Dec. 19, 2024

The goal of this project is to develop functionality that will enable modular microservices that support data collection, scoring, and analytics functions as part of a reputation and voting weight system. This should include an architecture to allow for the integration of future microservices, an initial suite of key microservices, and a user interface that allows users to find and utilize various configurations of the microservices.

Proposal Description

Proposal Details Locked…

In order to protect this proposal from being copied, all details are hidden until the end of the submission period. Please come back later to see all details.

Total Milestones
3
Total Budget
$100,000_USD
Last Updated
28 Feb 2025

Milestone 1 - Preservation Layer

Description

Digitize 20,000 documents and establish storage

Deliverables

Tasks: 1. OCR Pipeline: ○ Custom OCR model using Google Cloud Vision API for 200,000 pages. 2. Storage: ○ Centralized GCS + Nearline backups (10 TB total). Google Cloud Services: ● Cloud Vision API: $300 (200,000 pages). ● Compute Engine: OCR fine-tuning (50 vCPUs, ~$3,000). ● Google Cloud Storage: 10 TB, 4 months (~$800 centralized, $200 Nearline).

Budget

$15,000 USD

Success Criterion

Digitized archive in GCS.

Milestone 2 - Indexing Layer

Description

Index 20,000 documents and integrate with 4.5M articles.

Deliverables

Tasks: 1. Database: ○ BigQuery for 15 TB of data (documents + articles). 2. Search: ○ Basic semantic search with Vertex AI. Google Cloud Services: ● BigQuery: 4 months (~$1,000/month, $4,000 total). ● Vertex AI: Initial embeddings/search (~$10,000). ● Compute Engine: Indexing pipeline (25 vCPUs, ~$2,000).

Budget

$25,000 USD

Success Criterion

Indexed database with basic search at archive.spineDAO.com

Milestone 3 - Knowledge Engineering + AI Agents

Description

Build initial knowledge graphs and AI agents.

Deliverables

Tasks: 1. Knowledge Graphs: ○ Semantic networks from 20,000 documents using Vertex AI. 2. AI Agents: ○ Deploy one specialized agent (e.g., Spinal Deformity) and one general agent. Google Cloud Services: ● Vertex AI: Embeddings + agent training (~$25,000). ● Cloud TPU: Graph computation (250 hours, ~$2,500). ● Cloud Run: Host agents (~$2,500).

Budget

$60,000 USD

Success Criterion

Basic knowledge graphs and two AI agents (demo-ready).

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3 Comments

0

robelbelete
Apr 5, 2025 | 4:53 PM

Edit Comment

Good project, but wrong place. Please kindly check what the RFP is about https://deepfunding.ai/rfp/reputation-and-voting-weight-system/

Good project, but wrong place. Please kindly check what the RFP is about https://deepfunding.ai/rfp/reputation-and-voting-weight-system/
- 0
  
  Rebecca_Spine
  Project Owner Apr 17, 2025 | 2:04 PM
  
  Edit Comment
  
  Okay, thank you very much.So, what does this mean for the project proposal submitted?
  
  Okay, thank you very much.So, what does this mean for the project proposal submitted?
  - 0
    
    robelbelete
    Apr 17, 2025 | 3:49 PM
    
    Edit Comment
    
    It won’t be considered for this RFP, but you can submit it during rounds.
    
    It won’t be considered for this RFP, but you can submit it during rounds.

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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

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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

0 /50 chars

0 /5000 chars

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

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.

Rebecca_Spine

Project Owner

I work as a researcher and product manager for the project spine archive.

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Project CoFounder

Spine Surgeon/Co-founder SpineDAO

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v_lafage

Project CoFounder

Spine Surgeon/Co-founder SpineDAO

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ComputerScientist

Founder Preprints.io/Contributor of SpineDAO

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Scott Itepu

Product Owner

Product Manager

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Spine Archive

Rebecca_Spine

Spine Archive

Expert Rating

Overview

RFP Guidelines

Reputation and Voting Weight System

Juana Attieh

Proposal Description

Proposal Details Locked…

Proposal Video

Not Avaliable Yet

3

$100,000 USD

28 Feb 2025

Milestone 1 - Preservation Layer

Description

Deliverables

Budget

Success Criterion

Milestone 2 - Indexing Layer

Description

Deliverables

Budget

Success Criterion

Milestone 3 - Knowledge Engineering + AI Agents

Description

Deliverables

Budget

Success Criterion

Join the Discussion (3)

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robelbelete

Rebecca_Spine

robelbelete

Expert Ratings

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Rebecca_Spine

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v_lafage

Account Pending

Scott Itepu

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SingularityNET

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