Decentralized Physics Tokenomics

[IMPACT]

Overview

A myriad of sectors are heavily dependent on large simulations of physical systems based primarily on traditional methods like Molecular Dynamics, and Density Functional Theory. Such sectors include Pharmaceutical, energy, semiconductors, etc. For example, in the recent Covid-times, millions of Molecular Dynamics simulations have been run, largely independently, related to the ACE receptor and spike protein to better understand the binding mechanisms[3]. Currently, most of this information is dormant, redundant, and inconclusive. The data is frequently dormant as the simulation data is analyzed for publications or industrial applications and then held on local data storage units, redundant as there are often teams around the world doing highly similar simulations, and inconclusive because often single simulations lack enough information to lead to conclusive results. Thus, centralized infrastructures are rather limiting in developing AI-centric frameworks for improving the efficiency and accuracy of physics computation and knowledge extraction. As bad as this is, this is only the surface of the problem. The larger problem is that there is no natural way to incorporate vast and diverse amounts of physics information (experiments, quarks, chemicals, proteins), data, knowledge , and algorithms in a cohesive and synergetic manner.

Objectives and Goals

Our end goal is clear. We hope to create the correct infrastructure to incentive mass adoption of cardano-based protocols in the computationally oriented scientific communities including academia, industry, start-ups, and individual community members.

We are creating a decentralized protocol for the simulation of physical systems while leveraging Nunet for computational resources and SingularityNet for AI enhancements with open ended improvements using anything from Deep Learning [1], to neuro-symbolic AI [2], quantum chemistry [4], cognitive architectures[5], etc. Additionally, we are building a tokemonics system to incentive computation, data, algorithm development, mining, and community rewards for collaborations and support from individual community members, academics, and even corporations. One of our driving principles is the coupling of advancements in artificial intelligence to advancements in functional near-term technologies.

Our solutions will be useful in markets like Biotechnology, Artificial Intelligence, Chemical Synthesis, and many more. These are quickly growing markets, and would be absolutely amazing for the health of the cardano ecosystem to bridge the market demand home. Take for instance just the Biotechnology market; it is expected to surpass 1.5 Trillion by 2030 and growing at nearly ten percent per year [6].

The paradigm shift we are creating with SNet and Nunet stems from creating a computational and algorithm environment for end-to-end integration of multi-scale simulations for developing and employing theoretical and AI algorithms built up from heterogeneous data sources, symbolic knowledge extraction, and cognitive principles to lead to the most interconnected framework for self-consistent computations in the physical sciences. This will all be done to mimic the use of High Performance Computing infrastructures, and in principle, we should be able to simulate molecular systems faster than many of the top supercomputer when Nunet is fully developed with a large enough ecosystem. All of our code will be developed for parallelized, multi-virtual node CPUs/GPUs. By using AI integration, we should also be able to surpass many of the conventional bottlenecks of such computations.

Industry and community

From an industry perspective, users (entities taking advantage of our computational protocol) can exchange tokens for theoretical computations of a particular system of study and/or private/public algorithms developed by various entities (individuals, research labs, corporations, community members). From the community perspective they will get rewarded for the contribution to data, computation, algorithm development (to name a few).

Rewards are mostly obtained from the following procedures: physics data (experiments, simulation data, theory), computational resources and storage, algorithm developments (developing new algorithms, training neural networks, improving existing networks), mining, and technology development. The first two are rather clear. In short, mining is the eventually-automated process of performing specific computations as suggested by community members or recommended by an AI agent that anyone can partake in by staking or resource allocation. As well, entities that develop on the protocol (via any of the above including mining) can obtain rewards via a predetermined ratio of tokens paid by industrial entities using smart contracts.

In this proposal, we are developing smart contract applications to have basic calls to different computational algorithms, the number of GPUs, CPUs, and terminating conditions of the computation. This requires minting test tokens for our project, and using them to request computations.

By creating this feature, we will be able to eventually attract academic and industry users to Cardano via our computational infrastructure. Thereby increasing adoption via growing the ecosystem with academic and industry collaborations and by increasing the number of transactions on Cardano and automating the process of mainnet transactions with academic/industrial institutions.

• General technical research and development uncertainties and complexities
• Delays on Nunet's development
• Not receiving funding for the development of the algorithms (in Mics. challenge setting)

Of course, we are working with Nunet, and any delays on their side could be near-term problematic, but can be circumvented by focusing on the details that can be directly implemented at current times. They are a well-proven team, and delays may happen, but they build great code.

As well, it will be inconvenient to not receive funding for the algorithm development, but we will continue to build regardless of the current funding state. So, without funding of other proposals, we will be delayed, but our development will continue.

[FEASIBILITY]

• At one month we will have a feasibility analysis to determine if it is possible to develop basic tokenomic features at the current stage of Nunet.
• At two months, we will either have basic working features, or consider alternative ways to integrate these features, either developed independently or with SingularityNet

Miscellaneous Hardware for local testing and development is not needed as we currently have self-owned servers. Any additional resources will be obtained out-of-pocket to improve our chances of obtaining funding.

Function Person/months People Salary Cost

Blockchain Development (Plutus) 2 1 $3,500 $7000

Miscellaneous consulting fees $1000

Justin Diamond - PhD Candidate - AI Researcher in Physics, Chemistry, Pharma, Bioinformatics at academic institutions including University of Michigan, Toyota Technological Institute of Chicago, Boston University, University of Luxembourg, and University of Basel.

Years of experience in academic settings studying machine learning related to chemistry, physics, bioinforamtics, and drug development. Some examples are at the University of Michigan I worked on Machine Learning for Protein Structure Prediction (working with Dr. Jinbo Xu, one of the inspirations for DeepMind's AlphaFold ) and at the University of Luxembourg I worked on generative machine learning models for calculating thermodynamic properties of small molecules as well as quantum mechanical and Molecular Dynamics to study the Spike Protein in the corona-virus in a highly parallelized and distributed fashion on a HPC.

https://www.linkedin.com/in/justin-sidney-diamond-881798193

https://github.com/blindcharzard

Floriane LeFloch - Foudning Member in lili.ai AI startup and Web3 Consultant

https://fr.linkedin.com/in/floriane-le-floch-678391a4

[AUDITABILITY]

This Catalyst proposal will aid Hetzerk in prototyping large scale computations of physical systems using SingularityNet and Nunet allowing for the continued growth and progressive development with further funding.

Increased number of transactions on Cardano due to SingularityNET AI service calls.

We have various algorithms in development (see our proposal in Miscellaneous Category for details) that need to be interacted with from Cardano's mainnet in order for Companies to begin to use our solutions. Thus, our progress will be measured by integration of basic tokenomics into our platform.

Our end goal is simple, we are building computational infrastructure on Cardano, in collaboration with Nunet and SingularityNet, to create the correct incentive structures and a recursive cycle of development, roll-out, rewards, and increased efficiency and increasing user-base to obtain a decentralized platform of simulation based solutions for academic and industry related problems like AI based drug development or simulations of bio-molecules with Quantum Mechanical algorithms.

One of the key mechanisms of incentives is to allow, at least, academic groups free computational resources. We can do this, by coupling the loss of value due to computational usage to the gain of actionable knowledge, data, and algorithms to solve some of the most computationally demanding problems in dramatic need of better data, algorithms, knowledge, and efficient and connected solutions. To create a net profitable cycle will take time and a growing ecosystem of partnerships and solutions, but by building now we create the future infrastructure to naturally and with decentralized protocols create more opportunities and participation in the future of beneficial technological and materials development. 

These are medium to long term goals that we hope to accomplish in the next three to five years.

In contrast, at the end of the two months of funding, we will have prototypes to call specific computational algorithms, the number of CPUs, GPUs, and virtual nodes from the Cardano mainnet.

Entirely new proposal

SDG Rating

References:

[1] https://pubs.acs.org/doi/10.1021/acs.accounts.0c00472

[2] https://arxiv.org/abs/2006.11287

[3] https://pubs.acs.org/doi/10.1021/acscentsci.0c01236

[4] http://quantum-machine.org/gdml/

[5] https://arxiv.org/abs/1410.5401

[6] https://www.globenewswire.com//news-release/2022/01/18/2368681/0/en/Biotechnology-Market-Size-to-Surpass-US-1-683-52-Bn-by-2030.html