There are plenty of veterans in the crypto space that view the AI and DePIN (Decentralized Physical Infrastructure) sectors as revolutionary asset classes with the potential to push mass blockchain utility and adoption forward. There are also veterans in the space who view these new blockchain asset classes as no better than meme coins for a few reasons:

• Crypto markets are known for rapid shifts in trends and narratives and have seen their fair share of hype cycles, leading to skepticism about the long-term viability of new projects. AI and DePIN protocols are relatively new markets in the space and have gathered a lot of attention. In the crypto space, attention drives returns and once projects in these markets started seeing outsized returns, new projects started dropping with AI/DePIN buzzwords used to attract attention but had no true utility - effectively pump and dump schemes.

• The alignment of economic incentives is crucial for the success of any crypto project. However, some newer AI/DePIN protocols struggle to truly align these incentives in a way that demands a token, which can cast doubt on their long-term viability. This leads some to compare them to meme coins, which are often viewed as speculative plays with limited utility.

I consider both the AI/DePIN sectors to have long-term staying power potential and important for pushing the legitimacy of blockchain adoption forward. The most successful projects to survive multiple cycles will be those that provide real utility with true use cases, and aren’t simply using buzzwords to pump a native token. The projects that have utility and offer real use cases justify having native tokens, if not just to interact with the protocol but to be able to offer supporters a way to invest in the protocol.

Now, let’s detail one project in the AI/DePIN space I’ve identified that is attempting to provide real utility to the sectors, the Destra Network

Destra Network

The Destra Network has been created to solve a number of problems that can be categorized under three main pillars:

• Destra GPU Network

• AI Computing Solutions

• Destra Cloud Solutions

Destra GPU Network

The biggest bottlenecks for anyone creating their own AI/LLM models is the accessibility and cost of GPU processing power. The Destra GPU Network incentivizes users to contribute otherwise idle GPU processing power to run nodes and receive rewards for doing so.

When users run nodes with their GPU power, Destra’s AI traffic resource management algorithms receives the GPU computing power and distributes that power toward end users in the necessary batches required by the end user, assuring that no processing power is wasted (management of available processing power can be observed live 24/7 via the Destra Unified Platform, the one stop shop for all solutions offered by Destra)

Summary: A user with GPU processing power runs a node offering their processing power to end users who pay to use the available GPU processing power, all observable on the Destra Unified Platform.

Per Destra’s website, decentralized GPU processing power have had the following real life use cases:

• Bio Simulations - simulating microorganisms RNS structures is otherwise impossible to do from a single centralized source of computing power.

• Rendering graphical media such as games, videos, and other content.

• Training LLM (more on this in the next section)

AI Computing Solutions

Large language models (LLMs) are the set of code that allows AI models such as ChatGPT, Grok, Llama, etc to be capable of understanding and generating human-like text.

Destra’s goal is to make AI and Large Language Models (LLMs) accessible to everyone at the click of a button, powered by the Destra GPU Network.

As posted on Destra’s X account, “the following are core features of [Destra’s] AI/LLM training platform:

• Pay only for actual usage

  Unlike GPU rentals in either centralized or decentralized platforms, where users have to pay per hour, irrespective of the utilization, on our platform users only pay for the compute power their models utilize for training, reducing costs on idling.

• Dynamic GPU allocation

  Our platform features dynamic GPU resource allocation, allowing optimal distribution of GPU power based on specific training needs. This flexibility ensures that LLM training tasks are completed efficiently, minimizing downtime and maximizing performance.

• Scalability

  Scalability is at the core of the Destra LLM Training Platform. Whether you're running a small-scale experiment or a large-scale deployment, our platform can handle it. As your needs grow, the platform seamlessly scales to accommodate increased demand, ensuring that you have the necessary GPU power to train even the most complex models.

• Privacy and Security

  All the data related to training jobs, including datasets, are encrypted and securely stored on the Destra Decentralized File Storage Network. This ensures that your data remains private and protected while leveraging the powerful, decentralized infrastructure of Destra for your AI and LLM training needs.

Destra Cloud Solutions

All decentralized applications built on the ethereum network, despite their “decentralized” prefix, still rely on a centralized web2 infrastructure. Destra is creating a truly decentralized web3 network where reliance on web2 infrastructure will not be needed through the following Destra Cloud Solutions:

• Decentralized web hosting

• Decentralized domain names, removing the need for centralized platforms such as DNS and ICANN.

• Decentralized object storage services for items such as NFTs

• Decentralized ENS gateway, allowing Ethereum Name Service domains to be accessed via a format that can be understood by conventional web browsers through Destra’s gateway.

• Decentralized DNS.

All of these services are supported by Destra Network’s node operators via a “Proof of Sync” consensus mechanism to ensure efficient operation and security.

Destra Network Economics - $DSYNC

In order to interact with, or invest in, the Destra Network, you will be utilizing Destra’s native token - $DSYNC.

Per Destra’s white papers, $DSYNC has the following use cases/properties:

• Payment for Services

  Users consuming network resources for purposes like hosting dApps, storing data, or using computational power pay for these services in Destra tokens ($DSYNC). This demand for tokens drives their economic value and utility within the ecosystem.

• Decentralized Governance

  Token holders are empowered to influence the governance of the network, making decisions on protocol updates, resource allocation, and economic policies. This model ensures the network evolves in alignment with user interests and adapts to changing demands.

• Transparent and Fair Allocation

  Algorithms and smart contracts are employed to guarantee a transparent and equitable distribution of rewards based on actual resource contributions and service demand, preventing centralization and ensuring no single entity can dominate the network’s economy.

• Staking and Security

  Network validators and governance participants can stake Destra tokens as a security measure. This staking mechanism discourages malicious behavior by imposing penalties for dishonest actions, thus enhancing the network's security and integrity.

$DSYNC tokenomics are inherently deflationary and integrated with network operations through deposit requirements, penalties, service charge buybacks, enterprise registration fees, and transactional burns.

The following deep dive posted on Destra’s X account describes the specifics behind $DSYNC’s deflationary nature -

• Node Operator Deposits and Penalties

  • Node operators register GPU or Storage Nodes with a deposit of DSync tokens.

  • Deposits are locked for terms based on contribution level.

  • Early deregistration results in a penalty amount of DSync which is burned

• Buyback and Burn Mechanism

  • Users pay fees for services like LLM training with a percentage of fees allocated for buying back and burning DSync tokens.

• Destra Enterprise Solutions - Destra Subnets

  • Enterprises acquiring subnets must pay registration fees and deposit DSync tokens. Registration fees are used to buy back and burn DSync tokens.

  • Each subnet operates its own Layer 3 (L3) chain with DSync as the gas token. Every transaction on these subnets burns DSync. This transactional burn rate ensures increased network activity permanently removes more tokens from circulation.

Conclusion

Despite the promise of AI, many projects in the cryptocurrency space are little more than wrappers around existing generative AI models or image generators. These projects often lack true innovation and merely capitalize on the hype surrounding AI. They present themselves as groundbreaking but fail to deliver any technological advancements, offering nothing more than superficial integrations of existing AI frameworks.

Destra is taking a different approach and building a truly Decentralized AI Training Network. Unlike other AI projects, Destra’s network is grounded in technological innovation and practical utility.

Leveraging Destra Network’s decentralized GPU technology allows individuals to contribute idle GPU power from their personal computers and laptops, creating an incentivized, decentralized ecosystem of GPU power. This approach democratizes access to GPU resources, allowing users to train AI models and LLMs without the need for expensive, centralized cloud services.

Destra is still a new project, and has a long way to go before it generates a large enough adoption to warrant permanent staying power, however, Destra is proving to be a reliable project continuously delivering on platform developments.

With the current AI revolution just beginning both inside and outside of blockchain technology, Destra is on pace to be a leader in the industry and offer a full suite of products to catalyze mass adoption GPU processing power and AI model creation.