💰 Who Pays the Money? Market and Pricing Analysis
To fully understand where real money comes from in the system, it is enough to look at the price lists of classic centralized giants and decentralized DePIN platforms. We compare ourselves to the Great and Terrible Google Cloud or Amazon AWS—and the dry economic figures speak for themselves.
📊 Comparative Analysis of Computing Power Rental Costs
| Resource Rental Terms | Google Cloud / AWS | DePIN Network (Our Anthill) |
|---|---|---|
| Price for Equivalent Computing Power | $3.50–$4.50 / hour | $1.00–$1.20 / hour (3-4 times cheaper!) |
| Bureaucracy, KYC, and Access | Strict contracts, verification, sanctions | Complete anonymity, launch in 2 clicks |
| Availability of Free Resources | Queues weeks ahead for small firms | Real-time pool availability |
🔌 Through Whom Does the Money Flow? Major DePIN Aggregators
| Platform | What the Server Actually Does | What Resource Clients Pay For |
|---|---|---|
| io.net | Combines servers into clusters for AI/ML tasks | Hourly rental of GPU tensor cores |
| Render Network | Processes heavy 3D graphics, special effects, cinema | Pure rendering through video memory (VRAM) |
| Akash Network 🌟 | Decentralized hosting for websites, databases, and VPS | Multi-core CPU and RAM (Works WITHOUT GPUs!) |
🛡️ Why Google Will Not Destroy Us? Sleep Peacefully
Investors have a reasonable fear: if corporations see a decentralized network, will they not want to destroy it to remain monopolists? The answer is no. There is no war or direct competition here. We and the corporate giants are parallel worlds performing fundamentally different tasks.
» Google’s Task (AI Training): Training a new heavy neural network from scratch is a titanic super-task. It requires gigantic data centers where thousands of computing nodes are tightly bound together by physical infrastructure into one monolithic supercomputer. Our distributed “anthill” is not designed for this, and we do not venture there. Google builds factories.
» Our Task (Execution and Inference): But once the neural network is TRAINED, it needs to simply deliver answers to millions of users every day (process requests, generate images, render graphics, or host applications). And this daily work consists of billions of small, isolated tasks. For these, Google’s data centers are excessive and wildly expensive. This niche is perfectly filled by us with our independent nodes, taking this huge, lucrative pie for ourselves.
Corporations will continue to hold a monopoly on global model training, while DePIN takes over the mass consumer market for execution. We are not at war—we are dividing spheres of influence, guaranteeing stability, business security, and peaceful sleep for every server owner.