What is Mind Language?

Mind Language is an agnostic graph-based meta-programming language designed to enable easy program creation and modification through natural language or a drag-and-drop editor. Mind Language hopes to revolutionize programming by bridging the gap between human creativity and AI innovation.

Mind Language offers an intelligent tool that can turn natural language into a program. It uses an approach known as graph programming, where tasks are represented by visual nodes on a graph so non-programmer users can visualize what is happening on the back end. Mind Language hopes to be the next iteration of programming, equipping both traditional developers and regular users.

Graph-based structures are particularly adept at handling complex, interconnected data, making them ideal for other applications. An AI-powered language can optimize data queries and manipulations on the fly, providing significant performance benefits over traditional approaches.

The key elements of Mind Language include:

• Nodes: each node is representative of a task or function. There are different types, including start, middle, and end nodes, each playing a specific role in the application’s flow.
• Scope: the overarching environment that holds all information pertaining to nodes.
• Graph: the entire structure of a program, showing how different nodes are connected.
• Controller: This manages how the program runs, handles tasks, and makes sure everything works smoothly.
• Executor: the executor performs the tasks defined in the nodes.

Mind Language is Turing complete, meaning it can solve any problem a Turing machine could, including required computations like if-else conditions, returns statements, retrieving data, looping, etc. Most modern programming languages like Python, Java, and C++ are all considered Turing complete.

Mind Language is also equipped with an AI agent allowing users to use regular language to help build functionalities. Mind Language’s AI agent leverages multiple of the most popular natural language processing (NLP) tools like OpenAI, Bittensor, and LangChain, in addition to Mind Language fine-tuning an open-source model for their own use. Users can prompt the Mind Language AI agent to build nodes for them, or they can manually use the drag-and-drop functionality.

MindTrade

The first product being developed via Mind Language is MindTrade, a solution for building custom trading strategies. MindTrade is expected to launch its private minimum viable product (MVP) within the next two weeks, with public access following shortly after. As mentioned, users will be able to prompt Mind Language’s AI agent to generate nodes.

Once created and users confirm that everything is correct, they can save the entire functionality within the Mind Language library to be added to future graphs as a sub-application. Together Mind creates an easy, intuitive, and efficient programming environment with composability to build complex modular applications.

Beyond prompting Mind Language to create nodes there is also the ability to create AI-powered nodes. For example, a user can create a node with a prompt like, “purchase this token if XYZ tweets something positive about it” and Mind Language’s AI agent will perform a sentiment analysis on the fly. Other use cases include extracting information from a video or article and performing conditional actions. A proof-of-concept demo of Mind Language can be viewed here.

Investment Thesis:

The investment case for Mind Language is predicated on two major points:

• MindTrade Utility.
• Broad growth of low-code/no-code (LCNC) and AI solutions combined with a wide array of potential use cases.

MindTrade Utility

As traders try to find an edge across markets, strategies are becoming more custom, complex, and leveraging trading algorithms. Algorithmic trading is the deployment of computer programs designed to follow specific conditions and rules for executing trades. Trading algorithms are based on numerous variables including price, time, mathematical computations, correlations, and others to create predetermined trading rules.  The global algorithmic trading market was valued at $13 billion in 2022 and is expected to grow at a CAGR of 11% from 2023 to 2032, reaching $37 billion by 2032.

Algorithmic trading has a lot of benefits for investors looking for trades that would be difficult to execute manually, such as small arbitrage opportunities that only last for a brief amount of time. Mind Language will give crypto traders an easy and intuitive tool for creating algorithmic strategies that would otherwise require more comprehensive technical knowledge.

Copy trading has become more prevalent within crypto as users like to track specific wallets that they believe have an edge in trading. According to Bitget’s copy trading report, 93% of futures copy traders and 82% of copy spot traders have achieved profitability, demonstrating the technique’s effectiveness. STFX, a social trading platform that allows users to publicly copy trade has seen impressive growth in its trading volumes in recent months, displaying the growing popularity.

MindTrade will make copy trading extremely simple and can even enable users to nest copy trading techniques into larger trading strategies. MindTrade is well positioned to become a disruptor in the trading space as it enables users to create new strategies from scratch with drop-and-click functionality or using normal English with Mind Language’s AI agent.

Broad Growth of LCNC & AI Agent Solutions

Beyond MindTrade, the potential for Mind Language is much bigger. Gartner is predicting that LCNC development platforms will account for more than 65% of application development in 2024. Combined with the fact that an estimated 0.5% of the world’s population knows how to code, Mind Language has the potential to attract an enormous user-base. Due to gaps in technical knowledge and the productivity increases of LCNC platforms, the LCNC market is forecasted to become a $187 billion market by 2030, growing at a CAGR of 31.1%. Similarly, the AI agent market is forecasted to grow extremely quickly. The global AI agent market was valued at $4.8 billion in 2022 and is expected to grow at a CAGR of 43% through 2028, expanding to $28.5 billion by 2028.

Mind Language sits at the intersection of two large markets with significant forecasted growth. Due to its versatile nature, Mind Language should find applications across various industries—from finance and healthcare to cybersecurity and beyond. This cross-domain applicability broadens its market potential, with obvious use cases including analytics, IoT, process automation, and smart-contract development.

Mind Language will be inherently flexible and able to adapt to new technologies and paradigms more easily than more rigid programming frameworks. This adaptability makes it a forward-looking product that can evolve with crypto and other sectors. Mind Language has already teased some plans for future products:

• Mind Language Marketplace – Users can buy and sell applications and data sets created with Mind. It will become an open marketplace for strategy and development needs.
• Mind Language Feature Store – Purchase advanced tools and functionality within Mind Language.
• Mind Language SDK – dApps will be able to integrate Mind Language technology into their products natively.

Given the large TAM and broad range of directions that Mind Language can go, in our view, MND has a lot of room to expand from a $10 million circulating market cap. It is difficult to pinpoint a quantitative valuation without the specifics of fee structure and no reference point for product demand yet. For comparison, Mind Language’s closest competitor would be Graphlinq (GLQ 1.32% ), which currently has a circulating market capitalization of $60.9 million and an FDV of $89.6 million.

Tokenomics / Team

Mind Language’s native token is MND, which will be used as a utility token to pay for Mind Language services. Users will need to deposit credit to use Mind Language products and will incur charges according to usage. Users will also have the ability to deposit ETH, USDT, and USDC, which will be used to buyback MND tokens on the open market. Mind Language will also support a burn program where a percentage of charges will be used to buy and burn MND tokens. The program will start at 0% and increase by 10% each following week, with a cap of 50%. Therefore, token buy and burns will scale with product usage. Additionally, holding MND will be required to access premium features within Mind Language, although specific details have yet to be released.

There is a total of 100 million MND tokens. 20% have been allocated to the team, with 3% unlocked and 17% locked for one year, after which they will vest linearly over one year. The remaining 80 million tokens were allocated to the liquidity pool. At a price of $0.124, Mind Language has a circulating market capitalization of $10.3 million, and an FDV of $12.4 million.

Mind Language has no investors, and the team is made up of two anonymous developers: a theoretical physicist who was reportedly an AI/ML engineer for a well-known bank and a senior full-stack computer scientist.

Risks

The biggest risk with Mind Language is whether or not the product will live up to expectations. MindTrade will be released before the end of the month, and we will see if it finds product market fit. For more weary investors, it could be prudent to wait until the product is released. Additionally, smart contract risk remains relevant as any trading applications utilized by MindTrade will rely on the competence of Mind Language’s development. MindTrade users will need to grant access to their funds to utilize trading functionality which presents another risk. Lastly, there is a chance that more traditional programming languages maintain their staying power compared to LCNC solutions as they are battle-tested and well-known.

Conclusion

Mind Language operates in a unique space, trying to revolutionize the programming market with its no-code graph-based language. Mind Language’s first product is MindTrade, a minimum viable product that will allow users to create their own trading functions by using natural language. The increased demand for technical products and applications has left many people unequipped to produce code-based applications. As an AI-powered graph-based programming language, Mind Language presents a compelling mix of innovation, market potential, and adaptability. In our view, Mind Language should find a wide range of applications and use cases, driving demand for the MND token and fueling price appreciation.