💰 Who Pays? An Analysis of the Market and Pricing
To fully understand where the real money in the system comes from, all you need to do is look at the price lists of the traditional centralized giants and decentralized DePIN platforms. We compare ourselves to the mighty and formidable Google Cloud or Amazon AWS—and the cold, hard economic numbers speak for themselves.
📊 Comparative Analysis of Capacity Rental Costs
| Terms and Conditions for Resource Rental | Google Cloud / AWS | The DePIN Network (Our Anthill) |
|---|---|---|
| Price for a comparable amount of capacity | $3.50 – $4.50 per hour | $1.00 – $1.20 per hour (3–4 times cheaper!) |
| Bureaucracy, KYC, and Access | Strict contracts, inspections, sanctions | Complete anonymity, launch in 2 clicks |
| Availability of resources | Waiting lists stretching weeks in advance for small firms | Real-Time Pool Availability |
🔌 Who handles the money? The largest DePIN aggregators
| Platform | What exactly does the server do? | What service do customers pay for? |
|---|---|---|
| io.net | Groups servers into clusters for AI/ML tasks | Hourly Rental of GPU Tensor Cores |
| Render Network | Handles complex 3D graphics, special effects, and film production | Direct rendering via video memory (VRAM) |
| Akash Network 🌟 | Decentralized hosting for websites, databases, and VPS | Multi-core CPUs and RAM (Works WITHOUT graphics cards!) |
🛡️ Why Won't Google Destroy Us? Sleep Soundly
Investors have a legitimate fear: if corporations see a decentralized network, won’t they want to destroy it so they can remain monopolists? The answer is no. There is no war or direct competition here. We and the corporate giants exist in parallel worlds that serve fundamentally different purposes.
"Google's Challenge (AI Training): Training a new, complex neural network from scratch is a titanic undertaking. It requires gigantic data centers where thousands of computing nodes are tightly interconnected via physical infrastructure into a single monolithic supercomputer. Our distributed “anthill” isn’t designed for this, and we’re not getting involved in that. Google builds factories.
"Our Task (Execution and Inference): But once a neural network is TRAINED, it simply needs to provide answers to millions of users every day (processing requests, generating images, rendering graphics, or hosting applications). And this daily work consists of billions of small, isolated tasks. For these tasks, Google’s data centers are overkill and wildly expensive. We fit perfectly into this niche with our independent nodes, claiming this huge, lucrative slice of the pie for ourselves.
Corporations will continue to hold a monopoly on global model training, while DePIN takes over the mass consumer market for model deployment. We’re not at war—we’re dividing up our spheres of influence, ensuring stability, business security, and peace of mind for every server owner.