Integrate AlphaKEK AI infrastructure into SNET

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Expert Review🌟
Vladimir Sotnikov
Project Owner

Integrate AlphaKEK AI infrastructure into SNET

Funding Requested

$120,000 USD

Expert Review
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Overview

AlphaKEK built AI infrastructure for Web3, composed of our dedicated unbiased AI models and Fractal engine, which creates knowledge graphs from financial data.

We collect data from various sources, including real-time on-chain data and news articles, and use knowledge subgraphs for tasks like question answering and sentiment analysis.

We propose to integrate SNET and AlphaKEK ecosystems in 3 key directions:
1) Develop an open-source framework that enables interoperability between SNET and Fractal by dynamically generating MeTTa modules based on Fractal subgraphs
2) Integrate our AI Apps into the SNET AI Marketplace
3) Populate Fractal with knowledge about SNET and ensure real-time updates

Proposal Description

How Our Project Will Contribute To The Growth Of The Decentralized AI Platform

Our AI tools are designed for crypto users and ecosystems. Therefore, we can expect a synergistic growth effect: 

  1. Our proposed tools empower both users and developers. Not only will it add more apps to the AI platform but also could lead to new apps being created on top of the MeTTa generator.

  2. Any potential new users of our tools are already familiar with crypto. That means that there will be no friction when it comes to onboarding new users onto the decentralized platform.

Our Team

Our team is led by Vladimir Sotnikov who is CEO & Lead of AI at Fractal Labs. AI scientist with 7 years of experience. His works were mentioned in Nvidia GTC and OpenAI’s blog and received the ACM Best Paper Award. Before founding AlphaKEK, was developing LLM tools for astrophysics.

The team also includes:
Vinny Le - marketing professional with 18+ years of experience in banking, web3, and fintech;
Dmytro Sotnyk - Web3 developer
Valery Sotnikov - ML Engineer
Vladimir Khomenok - Web Engineer
View Team

AI services (New or Existing)

MeTTa module generator

Type

New AI service

Purpose

Retrieve the topic projection subgraph from AlphaKEK Fractal and export it in the form of a generated MeTTa module that can be integrated into other MeTTa apps.

AI inputs

Any crypto-related natural language questions e.g. "Are Ethereum ETFs approved?" "What chain WIF token is on?" "Top holder stats for AIKEK token" etc.

AI outputs

The code of a MeTTa module which describes the answer to the user's question as a set of atoms.

Alpha Chat

Type

New AI service

Purpose

Alpha Chat is an AI copilot specifically designed for Web3 research and exploration, evolving strategically to meet the complex and fast-paced needs of the cryptocurrency landscape. It offers real-time insights and tailored in-depth analyses, making it an essential tool for investors, traders, alpha hunters, and content creators within the dynamic Web3 ecosystem. Powered by AlphaKEK Fractal subgraphs, it can handle much larger contexts than its counterparts.

AI inputs

Any finance-related and crypto-related messages, e.g. "Market sentiment for $AGIX", "What are the trending DePIN projects at the moment?", "Are there any upcoming events regarding crypto regulation?", etc.

AI outputs

Natural language replies that are based on real-time crypto market data.

Alpha Visuals

Type

New AI service

Purpose

Users can generate wallpapers, transform images into retro styles, or create detailed art from text prompts. This initiative marks a significant step in our mission to provide innovative digital creativity tools. More information is available here: https://docs.alphakek.ai/products/alpha-visuals

AI inputs

1) text prompt; 2) source image (optional); 3) resolution (optional).

AI outputs

If a source image was provided: a transformed image. If no source image was provided: a generated image.

Company Name (if applicable)

Fractal Labs

The core problem we are aiming to solve

The general problem that AlphaKEK AI is aiming to solve is the following: 

OpenAI's ChatGPT, Anthropic's Claude-3, and other mainstream AI solutions fall short of effectively serving the unique needs of Web3 projects and applications.

Their Large Language Models (LLMs), while revolutionary in their own right, are not tailored to understand the intricate dynamics of the crypto market, often providing generic responses or avoiding the nuanced queries critical to traders, developers, and enthusiasts.

This disconnect stems from a fundamental lack of specialization in the crypto domain, rendering these models less effective for those seeking actionable insights, advanced analytics, and bespoke solutions within the Web3 ecosystem.

Specifically, in the case of SNET, we're also solving the problem of SNET's OpenCog Hyperon and AlphaKEK Fractal - two seemingly similar knowledge metagraph systems - being disconnected from each other. We believe that bringing them closer together will benefit both ecosystems, as well as their developers.

Our specific solution to this problem

We propose to integrate SNET and AlphaKEK ecosystems in 3 key directions:

  1. Develop an open-source framework that enables interoperability between SNET and Fractal, and make this framework extensible and reusable. It will be achieved by dynamically generating MeTTa modules based on Fractal subgraphs. These modules could then be imported as any other MeTTa module, reused, and extended as needed. Depending on the query, Fractal subgraphs can contain both on-chain data such as smart contract code audits, liquidity pool stats, and trading volumes, and off-chain data such as news articles, social media posts, technical documentation, forum discussions, etc. Integrate the resulting app into the SNET AI Marketplace.

  2. Integrate AlphaKEK AI Apps into the SNET AI Marketplace: Alpha Chat, Alpha Toolkit, Alpha Visuals.

  3. Populate Fractal with knowledge about SNET and ensure real-time updates. This will improve the quality of generated MeTTa modules and all the other services relying on AlphaKEK Fractal such as our Alpha API and chatbots when retrieving SNET-related information.

Project details

AlphaKEK is building a robust, tailor-made AI infrastructure for Web3. The key components of our infrastructure are dedicated, unbiased AI Models and the proprietary knowledge graph engine called Fractal. 

The key feature of AlphaKEK Fractal is the ability to generate self-organizing fuzzy knowledge graphs using the ingested financial data. We collect various sources of crypto-related data - from real-time on-chain data such as liquidity pool stats and smart contract code to news articles and forum discussions.

We use knowledge subgraphs to perform question answering, semantic search, sentiment analysis, and narrative clustering. Our long-term goal is to build autonomous AI agents with Fractal serving as their agentic environment.

We propose to integrate SNET and AlphaKEK ecosystems in 3 key directions:

  1. Develop an open-source framework that enables interoperability between SNET and Fractal, and make this framework extensible and reusable. It will be achieved by dynamically generating MeTTa modules based on Fractal subgraphs. These modules could then be imported as any other MeTTa module, reused, and extended as needed.

  2. Integrate AlphaKEK AI Apps into SNET Marketplace: Alpha Chat & Alpha Toolkit - an unbiased AI chat with real-time on-chain and off-chain crypto market data updates, and Alpha Visuals - our AI toolkit for generating and manipulating images with text prompts.

  3. Populate Fractal with knowledge about SNET and ensure real-time updates. Fractal knowledge subgraphs are then used for MeTTa module generation and Alpha Chat replies both inside and outside the SNET ecosystem.


A demo example of a generated MeTTa module: 

```
(= (chain DOG) Bitcoin)
(= (chain WIF) Solana)
(= (chain AIKEK) Ethereum)
(= (liquidity-lock AIKEK) Locked)
(= (sentiment memecoins) 0.78)
(= (approved-ETF Bitcoin) True)
(= (approved-ETF Ethereum) False)

```

Competition and USPs

The key difference of our project is that we already have a working service that leverages knowledge graphs for a wide variety of applications as the hundreds of regular users.

Our key proposal is to integrate these services into the SingularityNET ecosystem in a way that will benefit both end-users of SNET AI Marketplace and developers who are using OpenCog Hyperon for cryptocurrency-related applications.

Existing resources

We already have AlphaKEK Fractal - our knowledge engine, unbiased LLMs that are fine-tuned on retrieving data from Fractal, and data collection/ingestion pipelines. However, most of its APIs are still private, and those that are public are using REST rather than gRPC.

On the hardware side, we also have our hybrid cloud GPU infrastructure with client-facing services being hosted in the highly available Google Kubernetes Engine cluster, and the resource-intensive data ingestion and knowledge graph generation pipelines running on the self-hosted private cloud.

We will reuse these resources for implementing and hosting applications described in the proposal.

Open Source Licensing

MIT - Massachusetts Institute of Technology License

The proposed framework for generating MeTTa modules from Fractal subgraphs will be fully open-source. However, the Fractal itself, while having a public API, is a closed source. To make sure that the open source community will be able to benefit from the framework without having to depend on a proprietary API, we will also provide an option to use a local LLM as a provider (which, however, will have limited functionality compared to Fractal).

Similarly, the code for integrating AlphaKEK AI Apps into SNET Marketplace will be fully open source, while the underlying already existing APIs remain closed source, at least for now.

TLDR: all the code created as a part of the proposal will be open source, but it will depend on some proprietary tools.

Revenue Sharing Model

API Calls

API Description:

We will use the same revenue share model for all of the proposed services, namely:

1) MeTTa module generator

2) Alpha Chat

3) Alpha Visuals

API Revenue Service

1000

API Revenue Percentage

20

API Revenue Year

2026

Proposal Video

DF Spotlight Day - DFR4 - Vladimir Sotnikov - Integrate AlphaKEK AI infrastructure into SNET

3 June 2024
  • Total Milestones

    8

  • Total Budget

    $120,000 USD

  • Last Updated

    3 Jun 2024

Milestone 1 - API Calls & Hostings

Description

This milestone represents the required reservation of 25% of your total requested budget for API calls or hosting costs. Because it is required we have prefilled it for you and it cannot be removed or adapted.

Deliverables

You can use this amount for payment of API calls on our platform. Use it to call other services or use it as a marketing instrument to have other parties try out your service. Alternatively you can use it to pay for hosting and computing costs.

Budget

$30,000 USD

Milestone 2 - Integrate Alpha Chat into SNET AI Marketplace

Description

1) Develop a gRPC API for the Alpha Chat and deploy it 2) Develop an API adapter for the Alpha Chat 3) Publish the Alpha Chat on SNET AI Marketplace 4) Publish the source code of the API adapter

Deliverables

1) Alpha Chat is available on SNET AI Marketplace 2) The source code of the gRPC adapter for Alpha Chat is available under MIT license

Budget

$10,000 USD

Milestone 3 - Populate Fractal KG with real-time SNET data

Description

1) Assess what data about SNET is missing in AlphaKEK Fractal (e.g., social media posts, MeTTa documentation, roadmap, etc.) 2) Develop a data pipeline for collecting SNET-related data from Web2 and Web3 3) Integrate the pipeline into AlphaKEK Fractal 4) Injest and index all the missing data 5) Publish the source code of a data pipeline

Deliverables

1) AlphaKEK Fractal gets real-time updates about the SNET ecosystem 2) The Alpha Chat app in the SNET AI Marketplace (implemented during the previous milestone) is aware of these updates 3) All AlphaKEK services, e.g. Telegram bots, are aware of these updates

Budget

$10,000 USD

Milestone 4 - Implement MeTTa module generator - Stage 1

Description

1) Develop the first version of the MeTTa module generator powered by AlphaKEK Fractal's knowledge subgraphs 2) Integrate the MeTTa module generator into SNET AI Marketplace 3) Publish the source code 4) Start collecting feedback Note: implementing such a tool is a complex task. To make sure that it meets developers' needs, we will launch the first version of the generator at a zero price (covered by the grant) and encourage the community to provide feedback and suggestions while we're working on Milestone 5.

Deliverables

1) The first working version of the MeTTa module generator is launched on SNET AI Marketplace 2) The source code of the MeTTa module generator is published under the MIT license 3) The feedback collection process is initiated

Budget

$25,000 USD

Milestone 5 - Integrate Alpha Visuals into SNET AI Marketplace

Description

1) Develop a gRPC API for the Alpha Visuals and deploy it 2) Develop an API adapter for the Alpha Visuals 3) Publish the Alpha Visuals on SNET AI Marketplace 4) Publish the source code of the API adapter Note: during this milestone, we will be collecting feedback about the first version of the MeTTa module generator developed in the previous milestone.

Deliverables

1) Alpha Visuals is available on SNET AI Marketplace 2) The source code of the gRPC adapter for Alpha Visuals is available under MIT license 3) Feedback for the MeTTa module generator is collected

Budget

$10,000 USD

Milestone 6 - Implement MeTTa module generator - Stage 2

Description

1) Process the feedback for the MeTTa module generator 2) Address the possible issues and/or feature requests 3) Release the new version of the MeTTa module generator in the SNET AI Marketplace 4) Release the updated source code

Deliverables

1) Developer feedback for the first version of the MeTTa module generator is processed and addressed 2) The new version of the MeTTa module generator is published along with the source code

Budget

$25,000 USD

Milestone 7 - Perform testing and write documentation

Description

1) Perform functional testing and load testing 2) Fix potential issues 3) Write an exhaustive documentation for all the developed services and their code

Deliverables

1) Any possible issues are fixed 2) Documentation is ready and covers both AI Services and their source code

Budget

$5,000 USD

Milestone 8 - Launch a marketing/awareness campaign

Description

Launch a small marketing/awareness campaign to encourage users and Web3 developers to start using our new tools. Platforms: Twitter.

Deliverables

New users and developers from the marketing/awareness campaign.

Budget

$5,000 USD

Join the Discussion (4)

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4 Comments
  • 0
    commentator-avatar
    CLEMENT
    Jun 1, 2024 | 3:50 PM

    Hi Vladimir. Great job with this initiative.  However, I sense possible concerns associated with this project may include issues related to data privacy, security, and bias in AI models. Any thoughts on mitigating these concerns ?

    • 0
      commentator-avatar
      Vladimir Sotnikov
      Jun 1, 2024 | 4:07 PM

      Hello Clement! Thank you for the review and the question. We take privacy, security, and bias very seriously. Here's how we address them:   1) Privacy: the proposed project will only use publicly available data.   2) Security: all the code written as a part of the proposal will be published under the MIT license. This will ensure the whole project's transparency and allow all interested parties to perform any additional security cross-checks. We intentionally split the integration of the biggest AI service into two separate milestones to let the community test it out as early as possible, and then iterate based on the feedback.   3) Bias: we train our AI models to be unbiased regarding cryptocurrency-related questions. That's a very important nuance: our services only cover cryptocurrency-related topics, and we do not guarantee that there will be no bias in case of any unintended use. The framework and the dataset we use to ensure bias-free crypto-related answers is still under active development, we plan to release it later.

      • 0
        commentator-avatar
        CLEMENT
        Jun 1, 2024 | 4:10 PM

        Thanks Vladimir. Your reply is very helpful.  Kudos to you and your team ! Also, you are also welcomed to make comments on our team proposal as well https://deepfunding.ai/proposal/4757/  - AI4M (Enhancing Malaria Predictability using AI) https://deepfunding.ai/proposal/biotek-nexus-next-gen-biodiversity-conservation/  - BIOTEK NEXUS (Blockchain Biodiversity Conservation)

  • 0
    commentator-avatar
    Vladimir Sotnikov
    May 29, 2024 | 7:07 PM

    Hi everyone! Here's a link to our slides from the Deep Funding Spotlight Day #2: https://drive.google.com/file/d/1ZqEjsRFCKdLkLEYnnTzsNmMsVIxPW4lK/view?usp=drive_link 

Expert Review

Overall

5

user-icon
  • Feasibility 5
  • Viability 5
  • Desirabilty 5
  • Usefulness 5
Strong technical foundation and resources in place

The AlphaKEK proposal is both needed and feasible. It addresses a specific gap in the crypto and Web3 domains where existing AI solutions fall short, by providing tailored, real-time insights and analyses through its knowledge graph engine and specialized AI models. The integration of AlphaKEK's tools into the SingularityNET ecosystem is viable due to the strong technical foundation and resources already in place, including a robust AI infrastructure, existing data pipelines, and a team with relevant expertise.

Sort by

9 ratings
  • 0
    user-icon
    Gombilla
    Jun 10, 2024 | 11:39 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    Interoperability between SNET and Fractal

    I would advice that the team pays attention to ensuring scalability of of your proposed integrated ecosystem to accommodate growing user demand and data volume is crucial for maintaining performance and reliability over time. I believe that this will benefit SNET via interoperability. This is because the development of an open-source framework will enable interoperability between SNET and Fractal, facilitating seamless communication and data exchange between the two ecosystems.

    Kudos !

  • 1
    user-icon
    BlackCoffee
    Jun 10, 2024 | 12:38 AM

    Overall

    5

    • Feasibility 4
    • Viability 5
    • Desirabilty 5
    • Usefulness 5
    Web 3 benefits that the proposal brings

    We cannot deny the utility that this proposal brings to the Web 3 ecosystem. It is clearly something that is both novel and effective. I think users in the SNET ecosystem will have a better experience because of the conveniences that this proposal brings through the application of a series of advanced technologies today.

  • 0
    user-icon
    TrucTrixie
    Jun 9, 2024 | 1:55 PM

    Overall

    3

    • Feasibility 5
    • Viability 4
    • Desirabilty 3
    • Usefulness 3
    How long does each milestone last?

    The 8 milestones have clear descriptions and clear deliverables. This is a plus point in planning. But the minus point is probably that the duration of each milestone is not presented. So the team should limit the minus points and try to increase the plus points.

  • 0
    user-icon
    Max1524
    Jun 8, 2024 | 2:12 PM

    Overall

    3

    • Feasibility 4
    • Viability 3
    • Desirabilty 3
    • Usefulness 3
    Be clear about risks when implementing proposal

    I have an open question about what risks the team can anticipate when implementing this proposal? And what is the solution to limit that risk? I ask this question because it is part of the ability to survive. If we want to survive, we must be able to overcome foreseeable risks. I hope the team will consider my opinion.

    user-icon
    Vladimir Sotnikov
    Jun 8, 2024 | 3:44 PM
    Project Owner

    Hello Max,

    Can you please define the risks you're concerned about so we can address them precisely?

    We already covered three risks, including potential bias in the models, in the Discussion section.

    We encourage everyone to take a look before leaving a review. Here's a small excerpt:

    Question:

    Hi Vladimir. Great job with this initiative.  However, I sense possible concerns associated with this project may include issues related to data privacy, security, and bias in AI models. Any thoughts on mitigating these concerns?

    Answer:

    Hello Clement! Thank you for the review and the question. We take privacy, security, and bias very seriously. Here's how we address them:   1) Privacy: the proposed project will only use publicly available data.   2) Security: all the code written as a part of the proposal will be published under the MIT license. This will ensure the whole project's transparency and allow all interested parties to perform any additional security cross-checks. We intentionally split the integration of the biggest AI service into two separate milestones to let the community test it out as early as possible, and then iterate based on the feedback.   3) Bias: we train our AI models to be unbiased regarding cryptocurrency-related questions. That's a very important nuance: our services only cover cryptocurrency-related topics, and we do not guarantee that there will be no bias in case of any unintended use. The framework and the dataset we use to ensure bias-free crypto-related answers is still under active development, we plan to release it later.

     
    Please do not hesitate to ask if you have any additional specific questions or concerns.

  • 0
    user-icon
    Nicolad2008
    Jun 7, 2024 | 8:15 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    AlphaKEK Potential

    The project will help create Metta modules based on fractal segmenting knowledge graphs, opening up to the ability to apply AI more widely in the field of cryptocurrencies. In terms of practical value, the project can bring great benefits to cryptocurrency users and related ecosystems by integrating AI applications into AI Snet market and updating knowledge about SNET in Fractal in real time. However, the project also faces significant challenges. The integration of different technologies is a complex process, requiring extensive understanding of both ecosystems and effective coordination between them. In addition, maintaining real -time data updates is a big challenge, requiring the system to be able to process and synchronize information continuously without having problems. More importantly, ensuring no biased in AI models is an important factor that needs to be carefully considered, because any mistake in this process can lead to unwanted results.

  • 1
    user-icon
    Onize Olie
    Jun 6, 2024 | 6:19 PM

    Overall

    5

    • Feasibility 5
    • Viability 4
    • Desirabilty 5
    • Usefulness 5
    Project Makes Good Contribution to SNET Ecosystem.

    I believe this project is well-conceived with a clear understanding of the market needs and the technical capabilities required to address them. Its focus on interoperability, real-time data updates, and advanced analytics positions it as a valuable addition to the Web3 ecosystem, promising significant benefits for both SNET and AlphaKEK communities.

    The proposed solutions offer significant utility for the Web3 ecosystem. The integration of AlphaKEK's AI apps into the SNET Marketplace will provide users with advanced tools for real-time crypto market analysis, sentiment analysis, and data visualization. These tools are critical for traders, developers, and enthusiasts who require specialized insights and analytics that general-purpose AI models cannot provide. Furthermore, the dynamic generation of MeTTa modules based on Fractal subgraphs will enable more sophisticated and context-aware responses, enhancing the overall user experience within the SNET ecosystem.

  • 0
    user-icon
    CLEMENT
    Jun 1, 2024 | 3:48 PM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    Project aims to enhance SNET interoperability

    For me,  this project has the potential to significantly impact the AI landscape. It showcases the power of collaboration and integration, leveraging the strengths of both AlphaKEK and SNET to create a robust and versatile AI infrastructure for Web3. 

    Moreover, It also contributes to the SNET AI Marketplace, by adding valuable AI apps powered by AlphaKEK\'s infrastructure, expanding the marketplace\'s offerings and attracting users interested in financial data analysis, question answering, and sentiment analysis. Furthermore, the integration of Fractal knowledge graphs with SNET enhances the platform\'s capabilities, enabling users to access comprehensive and dynamic information relevant to their needs.

  • 0
    user-icon
    Tu Nguyen
    May 23, 2024 | 1:58 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 3
    • Usefulness 4
    Integrate AlphaKEK AI Infrastructure Into SNET

    This proposal would solve the problem of OpenCog Hyperon and SNET's AlphaKEK Fractal - two seemingly identical metadata systems - being disconnected from each other. They will tackle the problem in three main directions: (i) Develop an open source framework that enables interoperability between SNET and Fractal, while making the framework extensible and reusable. (ii) Integrate AlphaKEK AI Application into SNET AI Marketplace. And (iii) Provide Fractal with SNET knowledge and ensure real-time updates. Their solution is quite logical and clear. 
    Information about the members is very clear. They have a number of members with a wide range of experience and skills suitable for this proposition.
    Some other comments: I think they should define the start and end time of each milestone. Additionally, they should define their budget in more detail based on milestones.

  • 0
    user-icon
    Joseph Gastoni
    May 22, 2024 | 9:18 AM

    Overall

    4

    • Feasibility 4
    • Viability 3
    • Desirabilty 3
    • Usefulness 4
    This proposal outlines an integration

    This proposal outlines an integration between AlphaKEK's Web3-focused AI tools and SNET's decentralized AI platform. Here's a breakdown of its strengths and weaknesses:

    Feasibility:

    • Moderate-High: The core activities (framework development, app integration, knowledge graph population) seem feasible with existing technologies.
      • Strengths: Leverages existing AI models and knowledge graph technology from both teams.
      • Weaknesses: Developing an open-source framework for interoperability might require additional technical effort.

    Viability:

    • Moderate: Success depends on the user adoption of the integrated tools, the value proposition for developers, and the overall growth of the SNET AI Marketplace.
      • Strengths: The proposal offers a unique set of AI tools tailored for the Web3 space.
      • Weaknesses: The proposal lacks details on the target market size and potential revenue streams for AlphaKEK's tools within the SNET marketplace.

    Desirability:

    • Moderate: For developers and users seeking Web3-specific AI tools, this could be desirable.
      • Strengths: The proposal offers potentially valuable tools for question answering, sentiment analysis, and data visualization within the crypto market.
      • Weaknesses: The proposal needs to demonstrate the clear differentiation and value proposition of AlphaKEK's tools compared to existing solutions in the SNET marketplace.

    Usefulness:

    • Moderate-High: The project has the potential to improve the functionality of the SNET AI Marketplace for Web3 users, but its impact depends on the effectiveness of the integrated tools and their adoption rate.
      • Strengths: The proposal offers a way to expand the range of AI services available for the crypto market.
      • Weaknesses: The proposal lacks details on how the effectiveness of the tools will be measured and how they will address potential security concerns related to on-chain data access.

    Overall, this integration project has a promising approach, but focus on:

    • Technical Feasibility: Providing a more detailed plan for developing the open-source framework for interoperability between SNET and Fractal.
    • Market Validation: Conducting further research to validate the user demand for AlphaKEK's specific AI tools within the SNET marketplace.
    • Value Proposition: Clearly articulating the unique benefits and competitive advantages of AlphaKEK's tools compared to existing offerings.
    • Security Considerations: Addressing potential security risks associated with accessing and processing on-chain data within the integrated platform.

    By addressing these considerations, this AlphaKEK and SNET integration project can increase its chances of success and attract users and developers to the SNET AI Marketplace.

    Here are some strengths of this project:

    • Focuses on a specific niche - Web3 - with dedicated AI models and knowledge graphs.
    • Offers a range of potentially valuable tools for crypto users and developers.
    • Proposes an open-source framework for interoperability, fostering collaboration within the decentralized AI space.

Summary

Overall Community

4

from 9 reviews
  • 5
    2
  • 4
    5
  • 3
    2
  • 2
    0
  • 1
    0

Feasibility

4.2

from 9 reviews

Viability

3.9

from 9 reviews

Desirabilty

3.8

from 9 reviews

Usefulness

4

from 9 reviews

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