Picture yourself as Sam Altman, convinced that you’ve cracked the code. You shake up the world by launching ChatGPT, all the while projecting an image of an altruistic superhero with OpenAI’s non-profit status, leading everyone to believe you’re the good guy.

Then, out of nowhere, a Chinese quant trading firm drops Deepseek—a sleek, open-source LLM model that’s dramatically more budget-friendly than yours. You’d probably be sulking in your $5 million hypercar.

While venture capitalists are scrambling to reassess their investments in bloated US companies, it begs the question—what implications does this situation bring to the wider AI market?

To address this, we need to understand what made Deepseek’s R1 model so significant.

While its open-source nature is definitely a positive for humanity, an important insight is that Deepseek’s R1 benchmarks comparably with models like Claude or ChatGPT yet requires substantially fewer computational resources to perform the same tasks.

This improvement comes from various enhancements in computational efficiency, particularly the “mixture of experts" approach.

This method segments a larger AI model into smaller subnetworks, or "experts," enabling the LLM to process a query using a specific subsection of the network tailored to a particular knowledge area, such as mathematics, reasoning, and so on.

However, despite lower costs and increased efficiency, Business Insider reports that cloud providers are struggling to offer R1 at usable speeds. In fact, DeepSeek's API is also hindered due to high traffic.

This issue is central to our discussion today, as traditional cloud service providers often fail to meet demand, resulting in companies experiencing degraded performance or waiting weeks for their scheduled time slots.

Using a traditional cloud provider offers limited customization options w.r.t. hardware, its location (and associated latency), and the corresponding security assumptions.

So, where can independent researchers and SMEs access on-demand computing without facing lengthy wait times or excessive rental agreements?

DePIN cloud networks as a solution

Decentralized cloud effectively carries out the same functions as traditional cloud providers but leverages the vast amount of unused hardware globally, such as gaming PCs and idle mining rigs.

This approach offers greater accessibility, customization, and cost-effectiveness when compared to centralized alternatives.  

The unique advantage of DePIN networks lies in their ability to avoid purchasing large quantities of hardware and setting up a dedicated data center. Instead, they can utilize the existing supply available around the world.

These networks have rapidly attracted hardware suppliers by providing incentives via token emissions, enabling expansion, and rewarding quality engagement.

Cutting-edge blockchain technologies, such as Solana, finalize transactions in under half a second for less than a cent.

This enables DePIN networks like io.net to provide on-demand computing worldwide without worrying about high gas fees or congestion, letting them focus on scaling the network itself.

What is io.net?

io.net is the world’s largest decentralized GPU cloud network, aggregating compute from data centers, miners, and individual users in over 130 countries.

Their flagship product, IO Cloud, enables the deployment and management of on-demand, decentralized GPU clusters with no vendor lock-in. Pay for what you use, not a second more.

Since we last covered this beaut in March 2024, the network has expanded considerably, now boasting over 320,000 verified GPUs and almost 80,000 CPUs. This includes everything from consumer-grade NVIDIA GPUs like the RTX 3090 and 4090 to the highly coveted H100.

For researchers and AI startups, close to 7000 GPUs and CPUs are readily available for larger cluster deployments.

io.net proved that there’s significant demand for their product, with more than 10 million total compute hours served, which amounts to nearly $10 million in total network earnings.

io.net has also partnered with leading AI projects within the crypto space, including Aethir, Orbit, Matchain, Creator.bid, and Leonardo.ai.

Furthermore, the network joined forces with Dell Technologies as part of the Dell Authorized Partner Program to accelerate decentralized GPU computing solutions.

With Dell on board, you know they have something serious being cooked up here.

How does io.net work?

As you can imagine, implementing a decentralized cloud environment is no easy feat.

io.net's decentralized cloud network uses a multi-layered infrastructure orchestrated by the IO-SDK (specialized fork of Ray) to connect GPU providers with users needing compute power.

The infrastructure layer provides the raw resources—the GPU pool, orchestration tools, and storage—while the IO Network employs mesh VPNs to create direct, low-latency connections between nodes, enhancing redundancy and load balancing.

Complementing this, reverse tunnels securely bypass firewall restrictions, simplifying access for engineers and ensuring secure communication.

These components, combined with layers for user interface, security, APIs, backend operations, databases, and task management, enable io.net to offer cost-effective, scalable, and accessible high-performance computing for AI and machine learning tasks, all within a decentralized framework.

The magnitude of what’s created here is genuinely remarkable, but don’t fret; that’s probably the limit on discussions about decentralized mesh networks and reverse tunnels we fellow degens can handle in a single day.

Instead, let’s discuss how you can start participating in the IO cloud, whether you have a dusty gaming PC at home or you’re an AI/ML engineer looking to train your own model.

IO Cloud consists of two parties: users who utilize the hardware available on the network to train AI models or run inference, and workers, the ones supplying their hardware.

For users, IO Cloud provides a seamless experience with simplified cluster creation and a user-friendly interface. The service is highly customizable—from specific compute hours and download/upload speeds to precise fund expenditure, GPU locations, and chosen security settings.

As a result, it provides exceptional granularity, leading to significant time and cost savings for startups and researchers operating on tight budgets.

The worker portal provides many benefits for GPU suppliers, including comprehensive financial oversight through real-time earnings tracking and transparent billing.

It also facilitates smooth management with easy GPU integration and efficient technical orchestration using tools like Kubernetes.

Moreover, the platform enhances resource efficiency by optimizing GPU usage and providing real-time monitoring alongside strong security protocols to safeguard assets and ensure stability.

This includes end-to-end encryption and SOC 2 compliance, guaranteeing data protection without added complexity.

To deploy a cluster, developers can pay with the IO token, USDC, or a debit/credit card. Regardless of the chosen payment method, be it USDC or fiat, the protocol converts these funds into IO behind the scenes, ensuring a consistent demand for its token.

Conversely, all worker earnings are disbursed in IO and originate from two sources: active job earnings and block rewards.

To guarantee that IO Cloud maintains optimal hardware availability at all times, workers can choose to stake a minimum amount of IO as collateral to obtain IO while their hardware is not actively engaged in a job.

Currently, there are two cluster options available: Ray and Mega-Ray. More options are expected to be rolled out soon.

For context, these clusters are part of a distributed computing framework used by OpenAI to efficiently scale AI workloads, including training large models like GPT-3 and GPT-4.

The network is indeed designed to serve real-world customers, such as SMEs and researchers. However, this raises the question: How does io.net relate to on-chain agents and their frameworks? The answer is right in the middle.

The backbone of the AI economy

As AI agents increasingly permeate our social and financial layers, there is a genuine need for decentralized, permissionless infrastructure that aligns with crypto's core principles.

By leveraging decentralized GPU resources, developers utilizing AI frameworks such as ai16z's ElizaOS or arc's rig can rent GPUs on a flexible, on-demand basis without the need for long-term contracts. This arrangement allows developers to pay solely for the compute time they actually utilize, significantly enhancing cost efficiency.

Furthermore, this approach significantly boosts computational capabilities at a fraction of the cost associated with traditional cloud providers, enabling the concurrent operation of multiple resource-intensive AI agents.

Consider the recent collaboration with creator.bid, a platform that enables anyone to launch, grow, and monetize AI agents on-chain.

With the support of io.net, AI agents on creator.bid can scale seamlessly and perform on-demand tasks such as video generation, live streaming, and DeFi actions without facing compute bottlenecks, all while significantly reducing costs.

Another key benefit of decentralized AI infrastructure is enhanced privacy, which is essential for organizations that require regulatory compliance and data protection.

The collaboration with Nillion bolsters this by enabling encrypted data processing across distributed GPU networks.

This partnership is set to reduce costs for privacy-centric AI implementations, accelerate model inference while upholding privacy, and reinforce compliance for managing sensitive data.

After tackling the toughest challenge in the AI landscape—the decentralized cloud network—io.net is ready to emerge as a full-stack solution by introducing IO Intelligence.

This platform provides a complete solution designed for developers, complemented by accessible financial applications for AI enthusiasts.

Utilizing the latest AI technologies, io.net features 25 open-source models, up to five specialized agents, and developer APIs, making it the leading option for agent deployment.

Conclusion

DePIN networks, such as io.net, are revolutionizing access to computing resources by offering prices that can be up to 90% lower than those of traditional providers like AWS. This democratization of compute resources is especially important as the demand for hardware continues to accelerate.

As cloud providers struggle to keep pace with this escalating demand, companies are increasingly seeking alternative solutions to meet their computing needs.

io.net, with the largest decentralized cloud network, is poised to attract an increasing amount of these businesses.

Keeping that in mind, let's consult the crystal ball and preview the future of io.net. To begin, io.net stands at the crossroads of two of the most exciting sectors in crypto: DePIN and AI.

The DePIN sector alone is expected to grow 100-1000x over the next decade. As for AI, the sky is the limit.

The planned transition to represent on-chain revenue is poised to significantly enhance the network’s valuation premium. Alongside the future potential for revenue-sharing with IO stakers will only further amplify the token's value.

Remember, there is no better marketing than the numba going up.

At io.net's kitchen, there's a lot happening, so stay tuned for more updates about this giant in the upcoming months.

Other related reads

• What Is io.net? A Complete Guide
• What is Nillion? Building The Internet’s Privacy Layer For All Sensitive Data
• Introducing DePIN: A Top Line Overview
• How DeepSeek Is More Powerful for Less

‍