The recent rise in AI and ML has resulted in the lack of affordable and available GPU and CPU computing power on the market for bioinformatics/medical/physics research.
NuNet is a decentralized, open source, p2p computing network utilizing latent computing resources of the world and will enable bioinformatics/medical/physics simulations to run via its network.
This is the total amount allocated to NuNet: Bioinformatics simulations with Decentralized Computing // Enabling cheap and reliable simulations on decentralized hardware for Bioinformatics via frameworks. Bioinformatics is essential for management of data in modern biology and medicine..
Avimanyu Bandyopadhyay, PhD candidate
Lead Researcher and systems scientist
Kabir Veitas, PhD
CEO and lead architect
For the development we shall use only open source frameworks as follows:
These technical dependencies do not require permissions to use outside Open Source licensing and are taken into account in our feasibility study. Therefore, integrating these dependencies will not cause any delays.
https://github.com/cellmodeller/CellModeller
Project will be fully open source in line with our licensing policy.
SDG Goals
SDG Subgoals
Problem:
The recent rise in AI and ML has resulted in the lack of affordable and available GPU and CPU computing power on the market for bioinformatics/medical/physics research. In addition, smaller institutions or private researchers might struggle to find available and affordable computing resources for their research.
Unique solution:
NuNet is a decentralized, open source, p2p computing network utilizing latent computing resources of the world and will enable bioinformatics/medical/physics simulations to run via its network. Via this project, NuNet will enable running compute workflows on the network that require dependencies to popular data science and modeling frameworks (e.g. Anaconda and CellModeller). For example, 35 million users are utilizing the Anaconda framework for their work.
Empowering Decentralized Research on the Cardano Blockchain
Cancer research through blockchains underscores the importance of leveraging blockchain technology for innovative research applications. The focus here is on the Cardano blockchain, a truly decentralized platform that is revolutionizing the way research is conducted. With its robust smart contract capabilities, Cardano is paving the way for a new era of decentralized science (DeSci), particularly in fields such as bioinformatics and other STEM and non-STEM disciplines.
Cardano's decentralized infrastructure and robust smart contract capabilities make it an ideal platform for conducting complex research processes. For instance, multiple research teams can simultaneously update their compute models, enhancing the efficiency and effectiveness of the research process.
Enabling medical/bioinformatics/physics simulations by utilizing Cardano blockchain as a transaction and settlement layer may greatly increase real world usage of Cardano ecosystem within DeSci, STEM and research community.
An interesting comparison between Traditional science & research (TradSci) and Decentralized Science (DeSci) is visualized in the tweet below:
Basically the flow of info/$$ in TradFi involves a big public/government institution as a middleman. In the DeSci the flow of info/$$ is directly between the public and researchers. Enabling simulations for this on decentralized hardware empowers all research to be done independent of the influence of big government, public or private institutions.
https://www.cryptoaltruism.org/blog/infographic-decentralized-science-vs-traditional-science
Benefits for the Cardano ecosystem:
The research is a continuation and expansion of the already completed Fund8 proposal. It will enable data science, DeSci, STEM and research use cases – specifically bioinformatics/medical/physics simulations – in the web2 and web3 space that need GPU computing power to source it via NuNet. The value for the compute provided will be exchanged via NTX token which is a Cardano Native Token.
Each transaction will be executed as a Smart Contract on the Cardano blockchain which will directly increase the volume of tx, volume of CNT as well as provide unique use cases utilizing bioinformatics/medical/physics frameworks to be built on top of it for the Cardano ecosystem.
The proposal addresses the following directions of the challenge:
Introduction:
The NuNet platform, as outlined in the proposal, currently offers an infrastructure for machine learning computations. However, the potential of this platform can be significantly expanded by integrating an additional option of data platform (Anaconda) containers. This would allow the platform to cater to a wider range of use-cases, including business solutions for both STEM and non-STEM research, thereby making it a more versatile tool for decentralized science and research.
Impact on the Cardano Ecosystem:
The integration of data science platform (Anaconda) containers into the NuNet platform can have a transformative impact on the Cardano ecosystem. By broadening the scope of computational possibilities, the platform can attract a diverse range of researchers from traditional science communities worldwide. This influx of users would not only increase the number of transactions but also strengthen the Cardano community by bringing in new perspectives and ideas.
The proposed solution addresses a key challenge in the Cardano ecosystem: the need for a more versatile computational platform that can cater to a wide range of research needs. By offering a solution that can handle both machine learning and non-machine learning computations, the platform can become a one-stop solution for researchers, thereby solving this issue.
Benefits:
1. Increased User Base: By catering to a broader range of research needs, the platform can attract a larger user base. This would include researchers from various fields who are looking for a decentralized platform for their computational needs.
2. Strengthening the Ecosystem: The influx of new users and the increased number of transactions would strengthen the Cardano ecosystem. It would also foster a more diverse community, which can lead to innovative ideas and solutions.
3. Versatility: The integration of Anaconda containers would make the platform more versatile, allowing it to handle a wide range of computations. This would make it a more attractive option for researchers.
4. Decentralized Science and Research: By providing a platform that can handle a wide range of research computations, the proposed solution would further the cause of decentralized science and research. This would democratize access to computational resources and foster collaboration among researchers.
In terms of quantifying the impact, it's realistic to expect a significant increase in the number of users and transactions within a reasonable timeframe after the project completes. The exact numbers would depend on various factors, including the marketing efforts and the adoption rate among researchers. However, given the unique value proposition of the platform, it's reasonable to expect a positive response from the research community.
Introduction:
The success of integrating data science platform (Anaconda) containers into the NuNet platform can be measured through a combination of quantitative and qualitative metrics. These metrics will provide insights into the impact of the project on the Cardano ecosystem's productivity and growth, both in the short and long term.
Quantitative Metrics:
1. User Adoption: Monitor the number of users (as a number of unique DIDs or DApp integrations) who start using the platform for their research needs. This can be further broken down into the number of STEM and non-STEM researchers (private persons or organizations using NuNet solutions).
2. Transaction Volume: Track the number of transactions on the platform. An increase in transaction volume would indicate a higher usage of the platform.
3. Successful Deployments: Count the number of successful deployments of research tools, such as the CellModeller framework with 480 citations for multi-cellular modeling. This would provide a direct measure of the platform's utility for research purposes.
Qualitative Metrics:
1. User Feedback: Collect feedback from users about their experience with the platform. This could include their opinions on the ease of use, the versatility of the platform, and the benefits of decentralization.
2. Community Engagement: Monitor the level of engagement within the Cardano community. This could include discussions about the platform on forums, social media, and other platforms.
3. Research Outcomes: Track the outcomes of the research conducted using the platform. This could include the number of research papers published, the impact of the research, and the innovative solutions developed.
The integration of the data science platform (Anaconda containers) into the NuNet platform is expected to have a positive impact on Cardano's productivity and growth. In the short term, it can attract a larger user base and increase the number of transactions. In the long term, it can foster a more diverse and innovative community, leading to the development of novel solutions and advancements in various fields of research.
These measures are realistic as they are based on the unique value proposition of the platform and its potential to cater to a wide range of research needs. The successful testing of the CLI version of the CellModeller framework on the NuNet platform further supports the feasibility of these measures.
Some of the direct benefits to the Cardano ecosystem are:
Some of the indirect benefits to the Cardano ecosystem are:
Spreading Outputs Over a Timescale
Our project plan includes clear milestones and deliverables, which will be shared publicly as they are completed. This incremental release of outputs will ensure a continuous stream of updates for the community.
This approach lets us provide updates on a regular basis, and offers users the chance to provide feedback that we can use to guide subsequent development.
Sharing Outputs, Impacts, and Opportunities
We intend to leverage various communication channels to share our project's outputs, impacts, and opportunities:
Testing and further research
As an open-source project, our outputs will be freely accessible for further research and development. We encourage the community's involvement in testing our solutions to enhance their real-world performance.
Community Testing: We'll invite our users to participate in alpha and beta testing phases, where they can help identify bugs and suggest improvements. We'll use GitLab's issue tracking for managing feedback and provide guidelines for issue reporting and feature suggestions.
Internally, we'll use project insights and community feedback to guide our future work, optimize performance, and prioritize new features. Our aim is to foster a collaborative development ecosystem that is robust, relevant, and of high quality.
Illustration of Capacity:
Our organization comes with a history of successfully bringing intricate technology projects to fruition. The pillars of our success lie in our deep-rooted technical understanding, stringent project management practices, and an unwavering focus on transparency and responsibility.
At NuNet we have employed a PhD candidate who is performing this kind of research in particular - GPU based Bioinformatics and is the lead on this proposal. The draft publication of his work is publicly available here:
https://peerj.com/preprints/26920/
NuNet is committed to Open Source Software development from the inception. Therefore, all our development and progress is available for public scrutiny at all times as well as open collaboration with the community. We actively invite and work with the community in regards to contribution, usage, work and testing of the platform codebase.
Link: https://gitlab.com/nunet
NuNet licencing policy:
https://docs.nunet.io/nunet-licensing-policy/
Openness and Responsibility:
We have established a robust framework to ensure openness and responsibility in the execution of the project and the management of finances:
1. Elaborate Budgeting: We present an exhaustive budget layout at the start of the project that details the fund allocation across various tasks. This leaves no room for ambiguity regarding the utilization of funds.
2. Periodic Reporting: Regular updates regarding the project and financial statements will be shared, offering complete transparency into the progression of the project and the use of funds.
3. External Auditing: We are open to audits conducted by independent third parties at regular intervals. This ensures responsibility and openness in our financial management.
4. Escrow Mechanisms: To further reassure proper use of funds, we can utilize an escrow service. This arrangement ensures that the project funds are held by a third party and released according to pre-set milestones. This provides an extra layer of assurance for the funds.
5. Payment Based on Milestones: Our payment structure is built around specific, agreed-upon milestones. This ensures that funds are released as we achieve these milestones. The completion of each milestone can be verified, ensuring you pay only for verifiable progress.
These measures reflect our commitment to openness, responsibility, and proper management of funds. We believe that these factors, along with our technical capabilities, make us an ideal choice to successfully execute this project.
We understand that not all steps we have implemented are valid for the Catalyst proposal but it demonstrates the internal working procedures we have in place.
Catalyst Experience
NuNet also has received the funding for proposals in Fund7 and Fund8. One proposal is successfully closed and the other is close to completion with one technical obstacle left to be solved. Overall, the funds were spent as intended on the development which can be monitored on Gitlab with daily commits since the award.
https://gitlab.com/groups/nunet/-/milestones/19#tab-issues
https://gitlab.com/groups/nunet/-/milestones/20#tab-issues
Financial Stability
As a 28+ strong team, we have independent funding to develop the core platform with a cash runway for at least 1-1.5 years. Cardano Catalyst proposals are used to extend the functionality and add features to the platform in order to enrich the possible use cases.
The financial report is publicly available and can be reviewed here:
https://medium.com/nunet/nunet-financial-report-2022-and-outlook-for-2023-405d38397629
Introduction:
The primary goal of this project is to enhance the NuNet platform's capabilities by integrating data science platform (Anaconda containers), thereby expanding its use-cases to include both STEM and non-STEM research. This section outlines the specific objectives of the project and the methods for validating their achievement.
Main Goals:
1. Technical Integration: The first objective is to successfully integrate Anaconda containers into the NuNet platform. This will be validated by testing the platform's ability to handle a range of computational tasks, beyond machine learning, using Anaconda containers.
2. User Adoption: The second objective is to increase the user base of the platform. This will be measured quantitatively by tracking the number of new users and qualitatively by collecting user feedback.
3. Transaction Volume: The third objective is to increase the number of transactions on the platform. This will be measured by tracking the transaction volume before and after the integration of Anaconda containers.
4. Community Engagement: The fourth objective is to foster a more diverse and engaged Cardano community. This will be measured qualitatively by monitoring discussions about the platform on community forums and social media.
5. Research Outcomes: The final objective is to facilitate innovative research outcomes. This will be measured qualitatively by tracking the research conducted using the platform and its impact.
Validation of Feasibility:
The feasibility of the approach will be validated through a combination of technical testing and user feedback. The successful testing of the CellModeller CLI on NuNet’s GPU platform provides a strong indication of the technical feasibility of the approach. Further validation will be obtained by deploying other research tools using Anaconda containers and assessing their performance.
User feedback will provide valuable insights into the usability and utility of the platform. By collecting feedback from users, we can assess whether the platform meets their research needs and identify areas for improvement.
In conclusion, the goals of the project are aligned with the needs of the Cardano ecosystem and the broader research community. The validation methods outlined above will ensure that these goals are achieved and that the project delivers a significant impact.
Introduction:
The project of integrating data science platform (Anaconda) into the NuNet platform will be executed in a phased manner, with each phase marked by a specific milestone. The following is a detailed breakdown of the project's milestones, the main tasks or activities to reach each milestone, and the expected timeline for delivery.
Milestone 1: Project Commencement and detailed architecture blueprints
Milestone 2: Technical Integration of Anaconda Containers for DeSci
Milestone 3: Marketing and community development strategy
Milestone 4: Implementation of marketing and community development and testing strategy
Milestone 5: Dissemination and identified additional documentation
The project will be managed using a combination of agile and waterfall project management approaches. The technical integration will follow a waterfall approach, with each task being completed before the next one begins. The user adoption, transaction volume, community engagement, and research outcomes will follow an agile approach, with tasks being executed concurrently and adjustments being made based on feedback and data.
The projected cost to achieve each milestone will depend on various factors, including the resources required, the complexity of the tasks, and the market conditions. However, a detailed budget plan will be developed and shared with the stakeholders to ensure transparency and accountability.
Introduction:
Each milestone in the project of integrating Anaconda containers into the NuNet platform will result in specific deliverables and outputs, leading to intended outcomes that contribute to the overall project goals. Here's a detailed description of what to expect from each milestone.
Milestone 1: Project Commencement and detailed architecture blueprints
Milestone 2: Technical Integration of Anaconda Containers for DeSci
Milestone 3: Marketing and community development strategy
Milestone 4: Implementation of marketing and community development and testing strategy
Milestone 5: Dissemination and identified additional documentation
Each milestone’s progress will be tracked through the completion of the stated expected results and the achievement of the anticipated impact. Regular project update meetings and reports will provide visibility into the project's progress, and any issues or delays will be addressed through the project's risk management process. The overall project management methodology will be agile, with regular sprint planning, daily stand-up meetings, and retrospective meetings. Key performance indicators will be defined to track the progress and success of the project. The team will regularly communicate with stakeholders and the Cardano community to keep them updated on the progress and gather feedback.
Each project is examined in great detail which can be seen in the proposed budgeting sheet. This results in pre-feasibility and feasibility studies which minimize the risk of budget overruns.
Project management in NuNet is on a high level with employed techniques such as Agile, Scrum, CCPM and others resulting in a good daily overview of the project progress.
The project is complex and involves research and development uncertainties however, NuNet is a well funded deep tech startup and in case of budget overruns will continue to develop until delivered due to this being a critical part of the overall NuNet development plan. This is evidenced by the funding received in Cardano Catalyst Fund 7 and 8 where NuNet has continued the work despite the substantial unexpected technical roadblocks and time impact.
The costs of the project are based on the average salary levels of engineers currently employed by NuNet. Since the team is fully distributed and remote, it is challenging to have a suitable median cost that covers the range of countries (India, Pakistan, Ethiopia, Brasil, Egypt, UAE, UK, Italy and others).
We believe that the costs are reasonable and reflect the seniority and knowledge of various positions involved in the delivering of the proposal.
In line of full openness, in the budget table can be seen the very granular distribution of costs, all the way to the hours of each position for each milestone.
In addition, fully remote workers can compete for jobs in Western countries driving the individual compensation levels much higher than in their native countries.
NuNet is a deep tech startup that is developing cutting edge solutions in the decentralized open source space. Currently, there are 28+ people in NuNet working on delivering use cases, primarily for Cardano. On top of that,
As a SingularyNET spin-off, NuNet has access to 100+ AI and software engineers for support. Main team members responsible for this proposal are presented below.
The NuNet Team working on this project:
Name: Kabir Veitas, PhD AI, MBA
Location: Brussels, Belgium
LinkedIn: https://www.linkedin.com/in/vveitas/
Position: Co-Founder & CEO
Bio:
Working in the computer software, research and management consulting industries with demonstrated experience. Skilled in Artificial Intelligence, cognitive and computer sciences, systems thinking, technology strategy, strategic business planning, management and social science research. Strong operations professional with a Doctor of Philosophy - PhD focused in Multi/Interdisciplinary Studies from Vrije Universiteit Brussel.
Name: Janaina Senna, MSc CS, MBA
Location: Belo Horizonte, Brasil
LinkedIn: https://www.linkedin.com/in/janaina-farnese-senna/
Position: Product Owner
Bio:
Master's degree in computer science and played different roles over the past 20 years, such as development manager, tech lead, and system architect, helping organizations launch new software and hardware products in the telecommunication and energy areas. As a product owner, she has shaped the product vision into manageable tasks and constructed the bridge between developers and stakeholders. She enjoys seeing products coming to life!
Name: Avimanyu Bandyopadhyay, PhD Candidate, Bioinformatics, MTech CS
Location: Kolkata, India
LinkedIn: https://www.linkedin.com/in/iavimanyu/
Position: Systems Scientist
Bio:
Knowledge-driven PhD candidate who manages resources and technical skills to accelerate collaborative research with GPU-based Bioinformatics. He thrives in a fast-paced and cross-disciplinary team environment that challenges his capacity for problem-solving and troubleshooting. He’s very passionate about understanding how various open source software work and loves to design new deployment models for them. Furthermore, he also believes that any software is as good as its documentation.
Interest driven researcher and author of “Hands-On GPU Computing With Python”, he has produced several scientific articles in different areas of science and research, with an academic publication related to enhancing productivity while working with extensive data.
At NuNet, he works with the integration of GPUs, tools and mechanisms with the broader NuNet platform.
Name: Dagim Sisay Anbessie, BSc CS
Location: Addis Ababa, Ethiopia
LinkedIn: https://www.linkedin.com/in/dagim-sisay-7b4b05b8/
Position: Tech Lead
Bio:
Experience in projects in the areas of Robotics, Machine Learning, System Software Development and Server Application Deployment and Administration for several international clients. At SingularityNET he worked on AI and misc. software development. Main responsibilities lay in researching the development path, technology to be used and directing specific tasks to the dev team. Additionally, he has been involved in system development when circumstances demand it.
Name: Ilija Radeljic, MSc CE
Location: Oslo, Norway
LinkedIn: https://www.linkedin.com/in/dagim-sisay-7b4b05b8/
Position: Director of Operations and Business Development
Bio:
Corporate industry veteran and AI&Blockchain enthusiast. This combination brings a wealth of 15 years of experience managing major infrastructure, power and manufacturing projects to the emerging blockchain world and its applications.
15+ years of experience in business negotiation, partnerships, leads, market entry, project management, promotion and presentations worldwide.
Formal engineering education, MSc Civil Engineering + MIT Sloan Executive Management and Leadership certified.
Cardano Catalyst Community Advisor and Cardano Catalyst Veteran Community Advisor since the beginning (Fund2) and consulted several funded proposals in Cardano Catalyst.
Name: Jennifer Bourke, BA, MSc
Location: Dublin, Ireland
LinkedIn: https://www.linkedin.com/in/jennifer-bourke-1bb286158/
Position: Marketing and Community Lead
Bio:
A data-driven marketing expert with a postgraduate degree in digital marketing and data analytics. Currently pursuing a postgraduate degree in global leadership, she combines her strategic marketing skills with a global perspective. With over 6 years of experience, Jennifer has a proven track record of driving successful marketing campaigns.
External auditors:
NuNet is also collaborating with the external auditing company Obsidian (https://obsidian.systems/) which has been contracted to audit the core platform development as well as specific use case integrations such as this one.
We intend to extend their contract (or hire another suitable 3rd party auditor) for auditing the implementation of this research work as well.
External support:
NuNet has a capable team (28+) to tackle the project but sometimes some extra resources or skills might be needed outside of the available pool. This will be sourced either as additional employees or subcontracted depending on the size and length of the development.