Bittensor can be hard to understand if you only look at it through code and technical terms. On this page, we’ll explain it using two simple mental models: a growing forest and a world of cities. Both are ways to look at the same system from different angles. The forest helps you understand how the ecosystem grows and stores value over time. The city helps you understand how people, work, and money flow through it. Together, they make the Bittensor ecosystem much easier to grasp.
Planet Bittensor: From Bare Planet to Living Forest
To really understand the Bittensor ecosystem, imagine a bare, rocky planet — empty, quiet, and full of potential. It’s called ‘Bittensor’. At first nothing grows. But slowly, life begins to appear:
Tiny mosses sprout — early experiments and first subnet activity.
Ferns and grasses take hold — smaller subnets with specific tasks begin to emerge.
Trees grow tall over time — major subnets become established, shaping the landscape of the network.
This growing landscape becomes an emerging forest: a dynamic, evolving ecosystem where many different plants (called subnets) share the same ground (planet Bittensor). Each tree hosts many lifeforms (miners, validators, stakers), competing for sunlight — the TAO emissions that help them grow and thrive — and sharing nutrients through underground networks of collaboration.
In Bittensor, this forest is alive with competition and cooperation. Each subnet specializes in a type of work (for example cloud storage, video compression, AI detection) but contributes to the health of the network as a whole. The more diverse and strong the forest becomes, the more resilient and useful the entire ecosystem is to participants and users.
Bittensor Subnets: Trees and Shrubs in the Forest
Imagine the Bittensor network as a forest. Each subnet is a tree or shrub in this forest. Some are tall and strong, reaching for the sunlight, while others are smaller but play very important roles. Life in this forest — miners, validators, and AI models — lives on and around these trees, helping them grow and thrive.
Big Trees — The Powerhouses of the Forest
Some trees dominate the canopy and capture the most sunlight (TAO energy). These are the major subnets, and they help shape the ecosystem.
Chutes — The Tall Oak of Compute
Chutes is a big, strong tree that provides serverless compute. It lets models run without needing their own infrastructure. Many lifeforms live here because it captures lot of sunlight (TAO) and resources. Chutes helps the forest grow by powering heavy tasks for other subnets.
Targon — The Sturdy Redwood of GPU Power
Targon is like a redwood tree. It focuses on GPU rental and infrastructure, making computing power available across the forest. Its deep roots stabilize the ecosystem and allow many models to flourish even if the environment is tough.
Hippius — The Fruitful Apple Tree of Storage
Hippius provides decentralized storage. Think of it as a tree with lots of fruit — it stores data, model checkpoints, and important resources for the rest of the forest. Smaller trees rely on Hippius for sustenance, making it a key part of the ecosystem.
Smaller Trees & Shrubs — Specialized Helpers
Not every tree is huge. Some are smaller, but they do very specialized and important work.
ITS AI — The Versatile Shrub
ITS AI is a smaller shrub, not capturing that much sunlight. It supports many other subnets by verifying if text is AI generated or not. While smaller than Chutes or Hippius, it keeps the forest active and productive and helps everyone separate truth from lies.
Bitmind — The Watchful Bush
Bitmind is like another smaller bush. It focuses on AI video and image detection tasks, preventing the spread of misinformation.
Yanez MIID — The Niche Fern
MIID is a fern that thrives in a shady corner. It focuses on fake identity simulation and testing.
How Subnets Interact
In the forest:
Competition for sunlight (TAO) keeps the ecosystem strong. The most useful trees get more energy. In Bittensor, this means that subnets compete for emissions. The more emissions they can get, the more resources they have available to distribute amongst its miners and the easier it is to attract top quality miners.
Collaboration strengthens the forest. Subnets share signals and knowledge, like trees sharing nutrients through underground networks. Many of Bittensor’s subnets are ‘the cheapest, the best in the world’ in their specific niche. For example, a subnet like Yanez MIID could store its data on Hippius and use compute from Chutes.
Every tree matters. Even the smallest shrubs add to the forest’s diversity and resilience.
Why This Helps You Understand Bittensor
Using the forest analogy makes it easy to see:
Bittensor is not a single AI — it’s a whole ecosystem. The rails. The base layer.
Like our planet, it’s the diversity of lifeforms that shape its beauty, productivity and resilience against stressors. Subnets are individual trees or shrubs, each with their own role. Together, they colonize planet Bittensor and have the potential to create an abundance of intelligence.
TAO is the energy that drives growth, and both competition and collaboration keep the forest thriving.
By thinking of Bittensor as a forest, you can visualize how different subnets work together and independently, and how the entire ecosystem grows over time.
A Second Look: Bittensor as a Planet of Cities
If the forest helps you feel how the ecosystem grows and stores energy, the city analogy helps you understand the economy of Bittensor.
Instead of thinking in trees, think of Planet Bittensor as a world of interconnected cities, each with its own specialization:
Chutes City — a hub of compute power and services
Targon City — where GPU resources are rented and shared
Hippius City — the data storage capital
Smaller towns like Its AI, Bitmind, and Yanez MIID — niche innovators contributing specialist capabilities
Each city:
employs workers (miners) who produce useful outputs,
gets inspected by regulators (validators) who judge quality,
uses the local currency (TAO) to pay workers,
and invests in better infrastructure when it earns more.
TAO, in this metaphor, is like a shared global currency across all these cities.
By holding TAO you own part of the planet’s economic output, not just one city’s success.
Unlike most places in tech, where:
only big companies decide what gets built,
only insiders get rewarded,
the economy of Planet Bittensor lets anyone contribute, earn, and benefit, no matter where they live.
Example Subnets
Below are some more examples of interesting and diverse subnets — what they are and why they matter
You can use dedicated websites like https://subnetalpha.ai for more detailed information and updates on all the subnets and click on the SubNet (SN) number behind the subnet name in the examples below, to find more detailed information.
🔥 1) Chutes (SN64) — Decentralized AI Compute
What it does:
Chutes enables serverless AI compute — meaning developers can deploy and run AI models across thousands of distributed GPUs without owning the hardware.
Why it’s fascinating:
It functions like a decentralized AWS for AI — connecting users to scalable compute that competitively rewards miners for providing inference power. This helps decentralize one of the most expensive pieces of AI infrastructure.
🗄️ 2) Hippius (SN75) — Decentralized Storage Layer
What it does:
Hippius provides decentralized, blockchain‑backed storage for AI data and models — similar to Filecoin/Arweave but natively part of the Bittensor ecosystem.
Why it’s fascinating:
Storage is essential for distributed AI. Hippius makes it secure, censorship‑resistant, and economically incentivized — so models and data aren’t tied to centralized cloud providers.
🧬 3) Safe Scan (SN76) — Open Medical AI Screening
What it does:
Safe Scan is a subnet focused on medical AI inference, especially early cancer detection models. It invites the global community to improve and validate these models using decentralized compute and rewards.
Why it’s fascinating:
It demonstrates how decentralized intelligence can be applied to critical real‑world problems, not just chat or images — making complex diagnostics more accessible and community‑driven.
🧠 4) It’s AI (SN32) — AI Content Verification
What it does:
Designed to detect AI‑generated content, providing tools to verify whether text was created by AI or humans. This is an important service in the age of misinformation and generative AI.
Why it’s fascinating:
It creates trust infrastructure for digital content — something increasingly vital across journalism, social platforms, and knowledge integrity.
🟣 5) TAO Private Network (SN65) — Decentralized Privacy/IP Access
What it does:
This subnet supports privacy‑focused networks, like decentralized VPN and censorship‑resistant routing over the Bittensor system.
Why it’s fascinating:
It shows how Bittensor’s model expands beyond AI into internet infrastructure, enabling private and global access without centralized bottlenecks.
🛡️ 6) Bitsec (SN60) — Security & Vulnerability Detection
What it does:
Bitsec focuses on detecting vulnerabilities and security risks in code and systems using decentralized AI models. It works with validators and miners to continuously improve security insights.
Why it’s fascinating:
Security is crucial for any digital network. Bitsec creates a community‑driven defense layer, making Bittensor stronger and safer through shared intelligence.
🤖 7) Affine (SN120) — Reinforcement Learning Platform
What it does:
Affine is a subnet focused on reinforcement learning (RL) tasks, using decentralized feedback loops to improve AI models through competition and refinement.
Why it’s fascinating:
RL has applications from autonomous agents to game‑playing AI. Affine pushes this beyond centralized labs into a distributed, participant‑driven ecosystem.
🧠 8) Bitcast (SN93) — Creator Economy Intelligence
What it does:
Bitcast is focused on rewarding creators, distributing TAO to contributors who generate valuable content, stories, and insights. Content makers on X and Youtube are briefed by Bitcast. They make content which is then checked by AI, and earn rewards (Bitcast alphatokens).
Why it’s fascinating:
This hybrid of AI + creator economics disrupts how content is valued and distributed, with meritocratic rewards instead of platform‑controlled distribution.