# DePIN: Cryptocurrency Dynex (DNX): What it is, history, uses and outlook

**What is Dynex (DNX)?**

Dynex (DNX) is a peer-2-peer, open-source **cryptocurrency in the DePIN** (Decentralised Physical Infrastructure) narrative. It is considered an altcoin and was launched in September 2022 with the goal of reinventing the cryptographic puzzle to make mining more meaningful by applying a **Proof-of-Useful-Work (PoUW) **mining algorithm. It is using the combined power of participating GPU miners to provide **supercomputing capabilities for everyone**. Notable features of Dynex — which uses the DynexSolve PoUW algorithm — are its **quantum computing efficacy** and **limited supply**.

**Tokenomics of Dynex**

Dynex’ supply is capped with a maximum supply of 110 million coins. At the day of writing this article, 82,632,695 DNX (75.13%) are in circulation. Given the published emission schedule, which is following a smooth emission curve, all coins will be mined within around four years. Dynex`s launch was 100% fair, with no ICO, no pre-mine or pre-allocation to investors.

**History of Dynex**

The team initially set out to create the Dynex-Chip, a neuromorphic chip, to address the limitations of Moore’s law. They conducted extensive research and explored various approaches in neuromorphic computing. Their first chip design, implemented using Raspberry Pis connected on breadboards, successfully solved problems with up to eight variables. Although the design was large and impractical, it achieved its intended purpose of in-memory processing, instantonic behavior, and exhibited long-range order **similar to quantum machines**.

**2020–2021**The early years of Dynex were destined to research & prototyping, where the developers reviewed hundreds of research papers in the are of alternative computing paradigms to narrow down the most feasible approaches and started experimenting. Their first chip design solved problems with up to eight variables and was implemented on breadboards with a number of Raspberry Pis connected. With the theories proved in practice, Dynex, a decentralised platform with a blockchain and coin was created, aiming to construct the world’s largest neuromorphic supercomputing platform.

**2022**

The Dynex main-net was launched in September 2022, alongside mobile, desktop and command line interface (CLI) wallets. Dynex was listed on first exchanges such as Txbit, Xeggex and Tradeogre and attracted the first mining pools to support their PoUW mining algorithm DynexSolve.

**2023**

A comprehensive testing period of the computing platform followed the launch of Dynex’ Proof-of-Useful-Work algorithm, eventually leading to the public launch of the Dynex Marketplace in December 2023, opening **computing on the Dynex platform to everyone**. Since then, customers have been confirming Dynex’ superior computing performance: “*Dynex is 867% faster than our local computing*”, sayd Weixin Lin from China Unicom, the worlds sixth largest mobile provider in the world. Samer Rahme, CTO of Cali Global, found: “*It took Dynex 1 minute to compute an architectural problem, which usually takes days*”. The efficacy of Dynex has also been independently evaluated by measuring the Q-Score of Dynex’ computing cloud, which outperforms existing quantum computers by orders of magnitude. With gaining more attraction, Dynex was listed on a number of larger exchanges like Lbank, Bitmart and MEXC.

**2024 and beyond**Dynex is gaining more and more

**recognition in the academic space**, with multiple research papers being published (Advancements in Unsupervised Learning: Mode-Assisted Quantum Restricted Boltzmann Machines Leveraging Neuromorphic Computing on the Dynex Platform, HUBO & QUBO and Prime Factorization, or Framework for Solving Harrow-Hassidim-Lloyd Problems with Neuromorphic Computing using the Dynex Cloud Computing Platform) as well as the official launch of the Dynex

**reference book**on Amazon (Neuromorphic Computing for Computer Scientists: A complete guide to Neuromorphic Computing on the Dynex Neuromorphic Cloud Computing Platform).

Bolstered by academic recognition, Dynex was covered in Interviews performed at the Nasdaq MarketSite Studio and aired on television by Fox News or Bloomberg amongst a variety of notable online media channels. In addition, the launch of Dynex Moonshots Foundation was announced, which is an entity to invest in projects using Dynex technology to solve societal challenges in the areas of health, nature, space and society.

Given the technological and economic benefits of the Dynex Computing Platform, it is expected that Dynex will become one of the **leading DePIN providers** in the near future, and is also providing the tools to **solve societal challenges**.

**Where Is Dynex Traded?**

Dynex (DNX) can be purchased by establishing an account with one of many cryptocurrency exchanges including Gate.io, MEXC, Bitmart and LBank.

**What Is Dynex Used for?**

Dynex (DNX) is a **utility coin** and the cryptocurrency used to pay for computations performed on the Dynex Cloud Platform, which is capable of performing quantum computing based algorithms without their limitations, significantly accelerating machine learning training, optimising feature selection and improving model accuracy. It also addresses optimization challenges faced by Fin-Tech, Pharmaceutical, Genomics, Smart Cities and Global-2000 companies.

Dynex` compatibility with Google TensorFlow, PyTorch, Scikit-Learn, IBM Qiskit and others allow applications in **artificial intelligence** to set new benchmarks. **Quantum computing algorithms for machine learning** harness the power of quantum mechanics to enhance various aspects of machine learning tasks. As both, quantum computing and neuromorphic computing are sharing similar features, these algorithms can also be computed efficiently on the Dynex platform — but without the limitations of limited qubits, error correction or availability. These quantum based AI/ML algorithms are providing **faster model training and greater accuracy** of machine learning models. Training processes, which usually takes thousands of training operations can be computed in a few batches. In Advancements in Unsupervised Learning: Mode-Assisted Quantum Restricted Boltzmann Machines Leveraging Neuromorphic Computing on the Dynex Platform, the authors are reporting significant improvements over traditional training methods.

Dynex use-case “AI based security auditing”: The seamless integration of the AI Security auditing tool with the Neuromorphic Network marks a pivotal advancement in the realm of Neuromorphic Computing. This integration empowers the auditing tool with the capability of transfer learning enabling the AI construct to share insights gained since its last transfer learning session with the Neuromorphic Network. This process facilitates the adaptation and integration of the AI’s ”short-term memory” into the network’s ”long-term memory.” The AI’s inherent ability to learn and adapt dynamically finds new dimensions when coupled with the Neuromorphic Network. This symbiotic relationship provides the AI with access to a substantial computational power reservoir enabling it to learn in a manner reminiscent of human cognition in the real world. The synergy between the AI Model and the Neuromorphic Network is a key enabler for the application. This allows the system to continually refine its understanding of the auditing requirements. This remarkable development in Neuromorphic Computing introduces the concept of parallel auditing wherein the system can concurrently assess multiple aspects akin to the multitasking capabilities of the human brain. This not only enhances the efficiency of the auditing process but also mirrors the complex and parallel nature of human thought processes.

In the **healthcare** domain, Dynex is making strides by enhancing drug discovery. For example, RNA folding of viruses or prediction of enzymes are amongst the applications on the Dynex platform, with results outperforming every traditional computation method today. Simulation of clinical-trials are reducing time-to-market of new medications.

Dynex use-case “Quantum RNA Folding”: In biology and chemistry, the properties of a molecule are not solely determined by a set of atoms but also by the shape of the molecule. In genetics, the shape of an RNA molecule is largely determined by how it bends back on itself. The sequence of A’s, U’s, G’s, and C’s that make up RNA has certain pairs that are drawn together to form hydrogen bonds. A sequence of several bonds in a row is called a stem, and a stem provides sufficient force to keep the molecule folded together. RNA molecules naturally form some stems while avoiding others in a manner that minimises the free energy of the system. This use-case takes an RNA sequence and applies a quadratic model in pursuit of the optimal stem configuration. Predicting the existence of stems is important to predicting the properties of the RNA molecule.

The impact of Dynex in the realm of **scientific research** is equally profound; by providing a platform to perform quantum algorithms, it facilitates exploration of yet undiscovered areas of research. One example is research of **post-quantum cryptographic schemes:** In HUBO & QUBO and Prime Factorization, the authors demonstrate the effectiveness of prime factorisation, a foundational mathematical concept at the core of many cryptographic schemes. It is evident that new cryptographic methods, which are resistant against potential quantum or neuromorphic attacks, will be required in the near future.

Dynex use-case “Quantum Prime factorisation”: Prime factorisation is a mathematical process that involves breaking down a composite number into its prime number factors. A prime number is a natural number greater than 1 that is not a product of two smaller natural numbers. The prime factorisation of a composite number is unique, meaning that it is expressed as a product of prime numbers in a specific way. Prime factorisation has several important use cases across various mathematical and computational domains. One of its primary applications is in cryptography, where large prime numbers are crucial for the security of certain encryption algorithms. The difficulty of factoring large composite numbers into their prime factors forms the basis of some encryption methods, such as RSA (Rivest-Shamir-Adleman), which relies on the challenge of factoring the product of two large prime numbers. In light of these developments, there is an increasing necessity for quantum-resistant algorithms that can withstand attacks from quantum computers.

In the **architectural** industry, Dynex is redefining traditional practices. Its blockchain technology brings unprecedented precision and efficiency to design processes and project management, heralding a new era in construction and design. Perhaps one of the most significant contributions of Dynex is in the development of **smart cities**. By incorporating its blockchain solutions, Dynex is enabling cities to become more efficient, responsive, and sustainable, enhancing urban living experiences through improved governance and public service management.

Dynex use-case “Smart Cities”: Determining optimal locations to build new electric vehicle charging stations is a complex optimization problem. Many factors should be taken into consideration, like existing charger locations, points of interest (POIs), quantity to build, etc. In this example, we take a look at how we might formulate this optimization problem and solve it using the Dynex Neuromorphic Platform.

For **Global 2000 companies**, Dynex acts as a catalyst for digital transformation, helping them **optimise operations** and stay ahead in a rapidly evolving digital world. Computations can be performed at a fraction of traditional costs, and can be **seamlessly integrated** in existing computational workflows. As an example, Dynex’ research of Quantum-Computational-Fluid-Dynamics (QCFD), offers customers the possibility to entirely outsource **wind-tunnel simulations** and save millions of potential investments in infrastructure: In Framework for Solving Harrow-Hassidim-Lloyd Problems with Neuromorphic Computing using the Dynex Cloud Computing Platform, the authors are demonstrating the superior computing quality of wind tunnel simulations in practice.

Dynex use-case “Virtual Wind Tunnel”: Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that employs numerical methods and algorithms to simulate and analyse the behaviour of fluid flows. It plays a crucial role in understanding complex fluid dynamics phenomena by solving mathematical equations governing fluid motion. CFD encompasses a wide range of applications, from aerodynamics and heat transfer to chemical reactions in fluid environments. CFD is also applied in environmental studies to analyse air and water pollution dispersion, as well as in the pharmaceutical and biomedical fields to study blood flow, drug delivery, and physiological fluid dynamics. Quantum-CFD (QCFD), utilises quantum effects to accelerate and improve the CFD calculations and can be used on the Dynex platform.

**The Bottom Line**

Dynex operates a supercomputing cloud platform enabling everyone to perform computing with quantum level efficiency, but without its limitations. Customer traction, academic recognition and tokenomics are supporting the potential for Dynex to become one of the leading cryptocurrencies and also creating a positive impact on our society by solving societal challenges.

**Further reading:**