[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  τao sτacker ☯️ [@TaoStacker](/creator/twitter/TaoStacker) on x XXX followers Created: 2025-07-16 16:43:41 UTC I originally wrote this with the $SOL community in mind, as the @V0idAI bridge opens up tomorrow and will enable them to purchase $TAO and subnet dTAO from the SOL chain - and I expect a good deal of new investors soon as a result. However I realize this may be a good intro to subnets for anyone new to Bittensor in general. I've taken the approach of identifying some key subnets for you to begin - definitely a "Subnet Primer 101" cheat sheet - I don't plan to introduce all XXX here, but rather, XX interesting subnets that showcase what the subnets can do across several categories. As of XX July 2025, here are some of the key players in the ecosystem to know. I've provided a category, a brief description, and then some comparable services (external to Bittensor and crypto/blockchain) so you can visualize and compare what these actually do (but remember, Bittensor serves these in a decentralized/distributed manner, and often at a far lower price point to the end customer). One last note before I share my "getting started" list - if you want more information about any of these subnets, or to learn about all 128, you can find information on each of them at both and There are currently subnets that cover purposes ranging from trading and prediction markets and sports betting, through marketing, financial, and all foundational aspects of AI infrastructure, security, and foundational training and inference services. CHUTES (SUBNET 64) @chutes_ai Category: AI Infrastructure Description: Serverless AI Compute at massive scale - Deploy your LLM/AI Model, and let it run. Comparables: AWS SageMaker (deploy feature), Google Cloud AI Platform (deploy feature), Microsoft Azure Machine Learning (deploy feature) GRADIENTS (SUBNET 56) @gradients_ai Category: LLM Training Description: Makes AI model training accessible to end users without deep technical knowledge Comparables: Google Cloud Vertex AI, AWS SageMaker (training feature), Hugging Face AutoTrain METANOVA (SUBNET 68) @metanova_labs Category: DeSci Description: Automates early-stage drug discovery at massive scale Comparables: Atomwise, Exscientia, Schrödinger RIDGES AI (SUBNET 62) @ridges_ai Category: AI Agents Description: Marketplace for autonomous software (coding) agents, to build, test, and deploy custom software and applications Comparables: GitHub Copilot, Cursor, Codeium READY AI (SUBNET 33) @ReadyAI_ Category: Data Description: Transforms unstructured data (PDFS and documents, social media posts, transcripts) into structured AI-ready datasets Comparables: Scale AI, AWS SageMaker Data Labelling 404-GEN (SUBNET 17) @404gen_ Category: 3D/Video Description: Generates 3D models from text-based input, used as game assets, virtual worlds, and AR/VR/XR experiences Comparables: NVidia Omniverse, Synthetik Studio, Unity SCORE VISION (SUBNET 44) @webuildscore Category: Sports Description: Computer vision platform focused on sports analytics, specifically Game State Recognition, tracking player movements, ball positions, and game events in real-time using object detection and keypoint analysis, with the goal of reducing the cost of video analysis by 10x to 100x compared to traditional methods Comparables: Sportradar, Genius Sports, Stats Perform Opta HIPPIUS (SUBNET 75) @hippius_subnet Category: Storage Description: Decentralized data storage platform, focused on providing censorship-resistant, AI-ready storage for data, applications, and AI models with a user-friendly UI for customers Comparables: DropBox, Box, OneDrive, Filecoin (crypto), Storj (crypto) GAIA (SUBNET 57) @Gaia_AI_ Category: DeSci Description: Provides services focused on geospatial intelligence and environmental forecasting, leveraging satellite imagery, weather data, and crowdsourced inputs Comparables: Google Earth Engine, Planet Labs, Descartes Labs, Orbital Insight SYNTH (SUBNET 50) @SynthdataCo Category: Prediction Description: Generates high-fidelity synthetic price data for a wide range of financial assets (including crypto) by creating a probabilistic time-series of price data Comparables: Numerai, Chainlink CCIP + data feeds (Crypto) XXXXX engagements  **Related Topics** [tao](/topic/tao) [sol](/topic/sol) [$tao](/topic/$tao) [$sol](/topic/$sol) [solana](/topic/solana) [coins layer 1](/topic/coins-layer-1) [coins defi](/topic/coins-defi) [coins made in usa](/topic/coins-made-in-usa) [Post Link](https://x.com/TaoStacker/status/1945524751520481615)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
τao sτacker ☯️ @TaoStacker on x XXX followers
Created: 2025-07-16 16:43:41 UTC
I originally wrote this with the $SOL community in mind, as the @V0idAI bridge opens up tomorrow and will enable them to purchase $TAO and subnet dTAO from the SOL chain - and I expect a good deal of new investors soon as a result. However I realize this may be a good intro to subnets for anyone new to Bittensor in general.
I've taken the approach of identifying some key subnets for you to begin - definitely a "Subnet Primer 101" cheat sheet - I don't plan to introduce all XXX here, but rather, XX interesting subnets that showcase what the subnets can do across several categories. As of XX July 2025, here are some of the key players in the ecosystem to know. I've provided a category, a brief description, and then some comparable services (external to Bittensor and crypto/blockchain) so you can visualize and compare what these actually do (but remember, Bittensor serves these in a decentralized/distributed manner, and often at a far lower price point to the end customer).
One last note before I share my "getting started" list - if you want more information about any of these subnets, or to learn about all 128, you can find information on each of them at both and There are currently subnets that cover purposes ranging from trading and prediction markets and sports betting, through marketing, financial, and all foundational aspects of AI infrastructure, security, and foundational training and inference services.
CHUTES (SUBNET 64) @chutes_ai Category: AI Infrastructure Description: Serverless AI Compute at massive scale - Deploy your LLM/AI Model, and let it run. Comparables: AWS SageMaker (deploy feature), Google Cloud AI Platform (deploy feature), Microsoft Azure Machine Learning (deploy feature)
GRADIENTS (SUBNET 56) @gradients_ai Category: LLM Training Description: Makes AI model training accessible to end users without deep technical knowledge Comparables: Google Cloud Vertex AI, AWS SageMaker (training feature), Hugging Face AutoTrain
METANOVA (SUBNET 68) @metanova_labs Category: DeSci Description: Automates early-stage drug discovery at massive scale Comparables: Atomwise, Exscientia, Schrödinger
RIDGES AI (SUBNET 62) @ridges_ai Category: AI Agents Description: Marketplace for autonomous software (coding) agents, to build, test, and deploy custom software and applications Comparables: GitHub Copilot, Cursor, Codeium
READY AI (SUBNET 33) @ReadyAI_ Category: Data Description: Transforms unstructured data (PDFS and documents, social media posts, transcripts) into structured AI-ready datasets Comparables: Scale AI, AWS SageMaker Data Labelling
404-GEN (SUBNET 17) @404gen_ Category: 3D/Video Description: Generates 3D models from text-based input, used as game assets, virtual worlds, and AR/VR/XR experiences Comparables: NVidia Omniverse, Synthetik Studio, Unity
SCORE VISION (SUBNET 44) @webuildscore Category: Sports Description: Computer vision platform focused on sports analytics, specifically Game State Recognition, tracking player movements, ball positions, and game events in real-time using object detection and keypoint analysis, with the goal of reducing the cost of video analysis by 10x to 100x compared to traditional methods Comparables: Sportradar, Genius Sports, Stats Perform Opta
HIPPIUS (SUBNET 75) @hippius_subnet Category: Storage Description: Decentralized data storage platform, focused on providing censorship-resistant, AI-ready storage for data, applications, and AI models with a user-friendly UI for customers Comparables: DropBox, Box, OneDrive, Filecoin (crypto), Storj (crypto)
GAIA (SUBNET 57) @Gaia_AI_ Category: DeSci Description: Provides services focused on geospatial intelligence and environmental forecasting, leveraging satellite imagery, weather data, and crowdsourced inputs Comparables: Google Earth Engine, Planet Labs, Descartes Labs, Orbital Insight
SYNTH (SUBNET 50) @SynthdataCo Category: Prediction Description: Generates high-fidelity synthetic price data for a wide range of financial assets (including crypto) by creating a probabilistic time-series of price data Comparables: Numerai, Chainlink CCIP + data feeds (Crypto)
XXXXX engagements
Related Topics tao sol $tao $sol solana coins layer 1 coins defi coins made in usa