Subnet Directory

With the amount of new subnets being added it can be hard to get up to date information across all subnets, so data may be slightly out of date from time to time

Subnet 13

Data Universe

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ABOUT

What exactly does it do?

Subnet 13 – “Data Universe” is a decentralized data-scraping and storage layer on the Bittensor network. It is designed to gather fresh, high-quality data (especially social media content) for AI training and analytics. Macrocosmos (the company operating SN13) describes it as “Bittensor’s decentralized data layer, focused on the collection and distribution of fresh, desirable data”. At launch, SN13 miners scrape real-time content from sources like X (Twitter) and Reddit (with YouTube transcripts planned). This data is then shared across the network so other subnets and services can use it.

  • SN13 fuels applications like market research and sentiment analysis by providing up-to-date social data. For example, businesses can “track brand sentiment and market shifts in real time” and “make data-driven decisions based on the latest insights”.
  • The subnet is built for scale: as of early 2025, it hosts billions of social media posts (Macrocosmos reports over 17 billion items on Hugging Face). It aims to be the world’s largest open-source social dataset, giving anyone access to vast amounts of fresh public data.

 

Subnet 13 – “Data Universe” is a decentralized data-scraping and storage layer on the Bittensor network. It is designed to gather fresh, high-quality data (especially social media content) for AI training and analytics. Macrocosmos (the company operating SN13) describes it as “Bittensor’s decentralized data layer, focused on the collection and distribution of fresh, desirable data”. At launch, SN13 miners scrape real-time content from sources like X (Twitter) and Reddit (with YouTube transcripts planned). This data is then shared across the network so other subnets and services can use it.

  • SN13 fuels applications like market research and sentiment analysis by providing up-to-date social data. For example, businesses can “track brand sentiment and market shifts in real time” and “make data-driven decisions based on the latest insights”.
  • The subnet is built for scale: as of early 2025, it hosts billions of social media posts (Macrocosmos reports over 17 billion items on Hugging Face). It aims to be the world’s largest open-source social dataset, giving anyone access to vast amounts of fresh public data.

 

PURPOSE

What exactly is the 'product/build'?

SN13 operates a peer-to-peer data network where Miners and Validators collaborate via Bittensor’s protocol. Each Miner node scrapes and indexes data from specified sources:

  • DataSources & DataEntities: A Miner polls its assigned sources (e.g. subreddits, Twitter keywords) and retrieves individual pieces of content. Each scraped item (a tweet, post, etc.) is stored as a DataEntity in the miner’s local database. Each DataEntity is tagged by its source and content (e.g. topic or stock ticker).
  • DataEntityBuckets: DataEntities are grouped into buckets by (DataSource, TimeBucket, DataLabel), and each Miner builds a MinerIndex listing all its buckets. This index is essentially a “fingerprint” of what data the miner holds.
  • Validator Sync: Validators periodically query all Miners to collect their MinerIndexes. By aggregating these indexes, validators gain a complete map of the network’s data and which miners store which content. This lets any subnet know where to find desired data.
  • Public Data Storage: To make the data available, miners publish their datasets to public repositories. SN13 supports uploading data to Hugging Face or any S3-compatible storage, enabling easy access by others. (Macrocosmos encourages miners to open-source data: for example, 3.2 billion rows of Reddit/X data were already published on Hugging Face.)

 

Incentive Mechanism: Validators not only map the data but also reward miners based on data quality and quantity. Each miner’s score depends on two factors:

  1. Data Value: This considers freshness (recent data scores higher; anything older than a threshold scores zero) and desirability. SN13 maintains a Dynamic Desirability List of high-priority topics (voted by TAO holders via the Gravity interface). Data matching those labels is scored more highly. Data that is already highly duplicated across miners is worth less.
  2. Miner Credibility: Validators periodically spot-check samples of each miner’s data to verify correctness. Miners are assigned a credibility score over time; any misrepresentation (e.g. stale or invalid data) lowers credibility and future rewards.

 

This design creates a “gravity well” effect: miners compete to collect the freshest, most in-demand data. Macrocosmos calls the interface for this “Gravity”, an API/UI where TAO holders can specify key terms to prioritize. In practice, the community can “vote through validators to decide the most desirable data to be prioritized for scraping,” driving a self-organizing data marketplace.

 

Technical Architecture and Tools

SN13 is built as a Bittensor-native subnet (Subnetwork 13) with a fully decentralized architecture. Key components include:

  • Miners and Validators: These are special nodes running the SN13 protocol on top of Bittensor. Miners scrape and store data, while Validators index and verify it. All communication (index reporting, validation proofs) happens via the Bittensor blockchain consensus layer.
  • Data Universe Dashboard: Macrocosmos hosts an interactive dashboard (e.g. at sn13-dashboard.api.macrocosmos.ai) that shows the distribution of data across the subnet. Miners use this to tune their configurations and maximize rewards.
  • Data Storage: As noted, scraped data is offloaded to external storage. By storing on Hugging Face or S3, SN13 can manage terabytes or petabytes of data: the protocol allows ~200 miners to collectively hold ~50 PB, while a Validator needs only a few GB.
  • APIs and SDKs: Macrocosmos provides developer tools for SN13. The Gravity API/SDK lets anyone “launch scraping tasks and get structured datasets built by miners”. For example, the GravityClient in the Macrocosmos SDK can programmatically start jobs and fetch results. An official Gravity API is also planned for validators and partners.
  • Visualization & Integration: In addition to Gravity, Macrocosmos built Nebula, a 3D data-visualizer for SN13 datasets, and MCP (Macrocosmos Control Panel) to query SN13 from external apps (e.g. Claude AI).

 

These elements work together to form a scalable data supply chain: miners continuously scrape and upload content, validators curate and reward it, and external users query the subnet via APIs and dashboards
macrocosmos.ai.

 

Products and Use Cases

Macrocosmos has launched several products on SN13:

  • Gravity: A user-friendly interface (web and API) for on-demand scraping. Users select keywords or topics, and Gravity dispatches jobs to the network. It covers platforms like Reddit and X (with YouTube support coming soon). Gravity also includes Mission Commander, an AI agent that suggests search terms (built on Subnet 1, Apex).
  • Nebula: A 3D visualization tool for exploring scraped data. Nebula plots posts and comments by content and sentiment, helping users find trends visually.
  • MCP (Macrocosmos Control Panel): An integration layer that lets applications (e.g. LLMs like Claude) query SN13 data via Bittensor, instead of only via the web UI.

 

These tools translate SN13’s raw data into actionable use cases. For example, organizations can deploy Gravity to collect customer sentiment on a product launch, or use Nebula to visualize emerging topics. As Macrocosmos notes, SN13’s data has powered use cases ranging from social media market research to sports analytics (e.g. Subnet 44 “Score”) and financial forecasting (e.g. Subnet 64 “Chutes” via Squad.ai).

 

SN13 operates a peer-to-peer data network where Miners and Validators collaborate via Bittensor’s protocol. Each Miner node scrapes and indexes data from specified sources:

  • DataSources & DataEntities: A Miner polls its assigned sources (e.g. subreddits, Twitter keywords) and retrieves individual pieces of content. Each scraped item (a tweet, post, etc.) is stored as a DataEntity in the miner’s local database. Each DataEntity is tagged by its source and content (e.g. topic or stock ticker).
  • DataEntityBuckets: DataEntities are grouped into buckets by (DataSource, TimeBucket, DataLabel), and each Miner builds a MinerIndex listing all its buckets. This index is essentially a “fingerprint” of what data the miner holds.
  • Validator Sync: Validators periodically query all Miners to collect their MinerIndexes. By aggregating these indexes, validators gain a complete map of the network’s data and which miners store which content. This lets any subnet know where to find desired data.
  • Public Data Storage: To make the data available, miners publish their datasets to public repositories. SN13 supports uploading data to Hugging Face or any S3-compatible storage, enabling easy access by others. (Macrocosmos encourages miners to open-source data: for example, 3.2 billion rows of Reddit/X data were already published on Hugging Face.)

 

Incentive Mechanism: Validators not only map the data but also reward miners based on data quality and quantity. Each miner’s score depends on two factors:

  1. Data Value: This considers freshness (recent data scores higher; anything older than a threshold scores zero) and desirability. SN13 maintains a Dynamic Desirability List of high-priority topics (voted by TAO holders via the Gravity interface). Data matching those labels is scored more highly. Data that is already highly duplicated across miners is worth less.
  2. Miner Credibility: Validators periodically spot-check samples of each miner’s data to verify correctness. Miners are assigned a credibility score over time; any misrepresentation (e.g. stale or invalid data) lowers credibility and future rewards.

 

This design creates a “gravity well” effect: miners compete to collect the freshest, most in-demand data. Macrocosmos calls the interface for this “Gravity”, an API/UI where TAO holders can specify key terms to prioritize. In practice, the community can “vote through validators to decide the most desirable data to be prioritized for scraping,” driving a self-organizing data marketplace.

 

Technical Architecture and Tools

SN13 is built as a Bittensor-native subnet (Subnetwork 13) with a fully decentralized architecture. Key components include:

  • Miners and Validators: These are special nodes running the SN13 protocol on top of Bittensor. Miners scrape and store data, while Validators index and verify it. All communication (index reporting, validation proofs) happens via the Bittensor blockchain consensus layer.
  • Data Universe Dashboard: Macrocosmos hosts an interactive dashboard (e.g. at sn13-dashboard.api.macrocosmos.ai) that shows the distribution of data across the subnet. Miners use this to tune their configurations and maximize rewards.
  • Data Storage: As noted, scraped data is offloaded to external storage. By storing on Hugging Face or S3, SN13 can manage terabytes or petabytes of data: the protocol allows ~200 miners to collectively hold ~50 PB, while a Validator needs only a few GB.
  • APIs and SDKs: Macrocosmos provides developer tools for SN13. The Gravity API/SDK lets anyone “launch scraping tasks and get structured datasets built by miners”. For example, the GravityClient in the Macrocosmos SDK can programmatically start jobs and fetch results. An official Gravity API is also planned for validators and partners.
  • Visualization & Integration: In addition to Gravity, Macrocosmos built Nebula, a 3D data-visualizer for SN13 datasets, and MCP (Macrocosmos Control Panel) to query SN13 from external apps (e.g. Claude AI).

 

These elements work together to form a scalable data supply chain: miners continuously scrape and upload content, validators curate and reward it, and external users query the subnet via APIs and dashboards
macrocosmos.ai.

 

Products and Use Cases

Macrocosmos has launched several products on SN13:

  • Gravity: A user-friendly interface (web and API) for on-demand scraping. Users select keywords or topics, and Gravity dispatches jobs to the network. It covers platforms like Reddit and X (with YouTube support coming soon). Gravity also includes Mission Commander, an AI agent that suggests search terms (built on Subnet 1, Apex).
  • Nebula: A 3D visualization tool for exploring scraped data. Nebula plots posts and comments by content and sentiment, helping users find trends visually.
  • MCP (Macrocosmos Control Panel): An integration layer that lets applications (e.g. LLMs like Claude) query SN13 data via Bittensor, instead of only via the web UI.

 

These tools translate SN13’s raw data into actionable use cases. For example, organizations can deploy Gravity to collect customer sentiment on a product launch, or use Nebula to visualize emerging topics. As Macrocosmos notes, SN13’s data has powered use cases ranging from social media market research to sports analytics (e.g. Subnet 44 “Score”) and financial forecasting (e.g. Subnet 64 “Chutes” via Squad.ai).

 

WHO

Team Info

Will Squires – CEO and Co-Founder

Will has dedicated his career to navigating complexity, spanning from designing and constructing significant infrastructure to spearheading the establishment of an AI accelerator. With a background in engineering, he made notable contributions to transport projects such as Crossrail and HS2. Will’s expertise led to an invitation to serve on the Mayor of London’s infrastructure advisory panel and to lecture at UCL’s Centre for Advanced Spatial Analysis (CASA). He was appointed by AtkinsRéalis to develop an AI accelerator, which expanded to encompass over 60 staff members globally. At XYZ Reality, a company specializing in augmented reality headsets, Will played a pivotal role in product and software development, focusing on holographic technology. Since 2023, Will has provided advisory services for the Opentensor Foundation, contributing to the launch of Revolution.

Steffen Cruz – CTO and Co-Founder

Steffen earned his PhD in subatomic physics from the University of British Columbia, Canada, focusing on developing software to enhance the detection of extremely rare events (10^-7). His groundbreaking research contributed to the identification of novel exotic states of nuclear matter and has been published in prestigious scientific journals. As the founding engineer of SolidState AI, he pioneered innovative techniques for physics-informed machine learning (PIML). Steffen was subsequently appointed as the Chief Technology Officer of the Opentensor Foundation, where he played a pivotal role as a core developer of Subnet 1, the foundation’s flagship subnet. In this capacity, he enhanced the adoption and accessibility of Bittensor by authoring technical documentation, tutorials, and collaborating on the development of the subnet template.

Michael Bunting – CFO

Before joining Macrocosmos, Mike spent 12 years in investment banking, where he guided clients through major strategic and financial transitions across more than £1 billion in international M&A and capital raising deals. Most recently serving as a Director at Piper Sandler, he brings deep experience in advising high-growth startups on strategy, business planning, funding pathways, and corporate governance. Mike has also worked closely with multinational corporations and prominent financial investors throughout his career.

Elena Nesterova – Head of Delivery

Volodymyr Truba – Senior Machine Learning Engineer

Alma Schalèn – Head of Product Design

Felix Quinque – Machine Learning Lead

Dmytro Bobrenko – Machine Learning/AI Lead

Alan Aboudib – Machine Learning Lead

Alex Williams – People & Talent Manager

Chris Zacharia – Communications Lead

Brian McCrindle – Senior Machine Learning Engineer

Lawrence Hunt – Frontend Engineer

Nicholas Miller – Senior Software Engineer

Kalei Brady – Data Scientist

Szymon Fonau – Machine Learning Engineer

Monika Stankiewicz – Executive Assistant

Amy Chai – Junior Machine Learning Engineer

Giannis Evagorou – Senior Software Engineer

Richard Wardle – Junior Software Engineer

Kai Morris – Content & Community specialist

Lewis Sword – Junior Software Engineer

Will Squires – CEO and Co-Founder

Will has dedicated his career to navigating complexity, spanning from designing and constructing significant infrastructure to spearheading the establishment of an AI accelerator. With a background in engineering, he made notable contributions to transport projects such as Crossrail and HS2. Will’s expertise led to an invitation to serve on the Mayor of London’s infrastructure advisory panel and to lecture at UCL’s Centre for Advanced Spatial Analysis (CASA). He was appointed by AtkinsRéalis to develop an AI accelerator, which expanded to encompass over 60 staff members globally. At XYZ Reality, a company specializing in augmented reality headsets, Will played a pivotal role in product and software development, focusing on holographic technology. Since 2023, Will has provided advisory services for the Opentensor Foundation, contributing to the launch of Revolution.

Steffen Cruz – CTO and Co-Founder

Steffen earned his PhD in subatomic physics from the University of British Columbia, Canada, focusing on developing software to enhance the detection of extremely rare events (10^-7). His groundbreaking research contributed to the identification of novel exotic states of nuclear matter and has been published in prestigious scientific journals. As the founding engineer of SolidState AI, he pioneered innovative techniques for physics-informed machine learning (PIML). Steffen was subsequently appointed as the Chief Technology Officer of the Opentensor Foundation, where he played a pivotal role as a core developer of Subnet 1, the foundation’s flagship subnet. In this capacity, he enhanced the adoption and accessibility of Bittensor by authoring technical documentation, tutorials, and collaborating on the development of the subnet template.

Michael Bunting – CFO

Before joining Macrocosmos, Mike spent 12 years in investment banking, where he guided clients through major strategic and financial transitions across more than £1 billion in international M&A and capital raising deals. Most recently serving as a Director at Piper Sandler, he brings deep experience in advising high-growth startups on strategy, business planning, funding pathways, and corporate governance. Mike has also worked closely with multinational corporations and prominent financial investors throughout his career.

Elena Nesterova – Head of Delivery

Volodymyr Truba – Senior Machine Learning Engineer

Alma Schalèn – Head of Product Design

Felix Quinque – Machine Learning Lead

Dmytro Bobrenko – Machine Learning/AI Lead

Alan Aboudib – Machine Learning Lead

Alex Williams – People & Talent Manager

Chris Zacharia – Communications Lead

Brian McCrindle – Senior Machine Learning Engineer

Lawrence Hunt – Frontend Engineer

Nicholas Miller – Senior Software Engineer

Kalei Brady – Data Scientist

Szymon Fonau – Machine Learning Engineer

Monika Stankiewicz – Executive Assistant

Amy Chai – Junior Machine Learning Engineer

Giannis Evagorou – Senior Software Engineer

Richard Wardle – Junior Software Engineer

Kai Morris – Content & Community specialist

Lewis Sword – Junior Software Engineer

FUTURE

Roadmap

Macrocosmos has an active development roadmap for SN13. According to official docs, the Q1 2025 roadmap was completed by 31 March 2025, and the Q2 2025 plan is to be published by mid-April 2025. Major themes in ongoing development include:

  • Data Streaming & On-Demand Datasets: (Early 2025) Launch of Gravity MVP and incentives for real-time streaming.
  • APIs and Datasets: (Q1 2025) Release of a Gravity API for partners, creation of a large open dataset (e.g. a 24-billion-row macro dataset), and Nebula MVP launch.
  • Analytics and Growth: (Q1 2025) Building an analytics platform, adding new data sources, and automated data-cleaning tools.

 

Going forward, Macrocosmos plans to expand data sources and tooling. Public communications suggest the subnet will support new platforms (e.g. Tumblr, GitHub) and release a “transparency dashboard” soon. The GitHub docs list “private storage” and user-added data sources as upcoming features. In short, SN13’s development is ongoing: each quarter brings new data pipelines, improved APIs, and community-driven enhancements.

Overall, Bittensor Subnet 13 (Data Universe) is an evolving, decentralized data marketplace and pipeline. It continues to grow with open-source datasets (billions of posts already live) and user-driven tools. The project documentation and community reports indicate that SN13 will keep adding sources, APIs, and analytic features in the near future.

 

Macrocosmos has an active development roadmap for SN13. According to official docs, the Q1 2025 roadmap was completed by 31 March 2025, and the Q2 2025 plan is to be published by mid-April 2025. Major themes in ongoing development include:

  • Data Streaming & On-Demand Datasets: (Early 2025) Launch of Gravity MVP and incentives for real-time streaming.
  • APIs and Datasets: (Q1 2025) Release of a Gravity API for partners, creation of a large open dataset (e.g. a 24-billion-row macro dataset), and Nebula MVP launch.
  • Analytics and Growth: (Q1 2025) Building an analytics platform, adding new data sources, and automated data-cleaning tools.

 

Going forward, Macrocosmos plans to expand data sources and tooling. Public communications suggest the subnet will support new platforms (e.g. Tumblr, GitHub) and release a “transparency dashboard” soon. The GitHub docs list “private storage” and user-added data sources as upcoming features. In short, SN13’s development is ongoing: each quarter brings new data pipelines, improved APIs, and community-driven enhancements.

Overall, Bittensor Subnet 13 (Data Universe) is an evolving, decentralized data marketplace and pipeline. It continues to grow with open-source datasets (billions of posts already live) and user-driven tools. The project documentation and community reports indicate that SN13 will keep adding sources, APIs, and analytic features in the near future.

 

MEDIA

Huge thanks to Keith Singery (aka Bittensor Guru) for all of his fantastic work in the Bittensor community. Make sure to check out his other video/audio interviews by clicking HERE.

Steffen Cruz, previously the CTO of the Opentensor Foundation, has joined forces with his longtime friend Will Squires to establish Macrocosmos. Leading subnets 1, 9, 13, 25 and 37, this team is actively shaping the future of Bittensor and stands as one of the most influential entities within the ecosystem.

In this second video, they spend much of the episode covering Subnet 13’s rebranding to “Gravity” and the team’s prediction of a Trump victory along with how this has managed to build a team of PHDs and machine learning professionals around Bittensor.

A big thank you to Tao Stats for producing these insightful videos in the Novelty Search series. We appreciate the opportunity to dive deep into the groundbreaking work being done by Subnets within Bittensor! Check out some of their other videos HERE.

In this session, the team from Macrocosmos discuss various exciting updates and innovations surrounding their subnets. They delve into the launch and functionalities of new subnets, including the Data Universe subnet for web-scale data scraping and the Apex subnet for advanced AI models. The team highlights the integration of decentralized, real-time data scraping using custom crawlers, which surpass traditional methods in efficiency and scalability. They also explore how the Bittensor community can drive decentralized AI research, leveraging massive data sets and advanced AI training. Further, the discussion touches on the evolution of scientific research within BitTensor, with the introduction of the Mainframe subnet for protein docking and drug discovery. The session concludes with an emphasis on Macrocosmos’ commitment to pushing the boundaries of decentralized AI and computational science, and the potential collaborations that can be achieved in the growing ecosystem.

This Novelty Search session, recorded in late 2024, focuses on the ongoing work and developments of the Macrocosmos team within the Bittensor ecosystem. The team dives into their progress with multiple subnets, including subnet 13, which has become one of the largest social media datasets in the world. They also discuss their work in various sectors, such as decentralized AI, data scraping, and protein folding, which is set to revolutionize fields like healthcare and pharmaceuticals. The team highlights their ongoing efforts to create a decentralized, incentive-driven system that encourages miners to contribute and optimize their computational resources. They also introduce their latest advancements in distributed training, including novel approaches to handling latency and improving gradient averaging. With a focus on data and model quality, the discussion explores how they plan to scale and refine their subnets to provide value for both validators and token holders within the Bit Tensor network. The session ends with an exciting preview of upcoming decentralized games and the future potential of the Bittensor ecosystem.

A special thanks to Mark Jeffrey for his amazing Hash Rate series! In this series, he provides valuable insights into Bittensor Subnets and the world of decentralized AI. Be sure to check out the full series on his YouTube channel for more expert analysis and deep dives.

This session, recorded in mid-2024, features a conversation with Will Squires and Stefan Cruz from Macrocosmos, a prominent player in the Bittensor ecosystem. They discuss their involvement in the decentralized AI network Bittensor, which operates through various subnets that run AI models and create computational power through a decentralized system. Will and Stefan explain their backgrounds, including their expertise in AI, machine learning, and computational research, and how these experiences led them to explore the potential of Bittensor. The conversation covers several exciting aspects, from the challenges of training AI models to the importance of creating a decentralized and transparent AI ecosystem. They also highlight the innovative and competitive nature of Bittensor, where miners are incentivized to innovate and optimize processes, driving the network forward. The discussion touches on both technical details, like the development of the protein folding subnet, and broader concepts such as the future of decentralized AI and the evolving business model of the Bittensor network.

Novelty Search is great, but for most investors trying to understand Bittensor, the technical depth is a wall, not a bridge. If we’re going to attract investment into this ecosystem then we need more people to understand it! That’s why Siam Kidd and Mark Creaser from DSV Fund have launched Revenue Search, where they ask the simple questions that investors want to know the answers to.

Recorded in July 2025, this episode of Revenue Search features Mike Bunting, CFO of Macrocosmos, discussing Subnet 13 (Data Universe)—a Bittensor-powered data scraping subnet that collects and structures social media content from platforms like X (Twitter), Reddit, and soon YouTube. The subnet has amassed over 55 billion rows of open-source data, making it the largest of its kind on Hugging Face. Users can query and download data via a live interface, and monetization is already underway through a credit-based model with fiat payments. The team is focused on enhancing data quality by adding metadata like engagement metrics, enabling use cases such as brand tracking, sentiment analysis, AI training, and financial forecasting. With thousands of users and growing enterprise interest, Macrocosmos is now building out a commercial team to scale adoption and is exploring multiple methods to return value to stakers of its Alpha token.

NEWS

Announcements

Macrocosmos Follow 621 4,694

Decentralising intelligence, building on Bittensor. SN1, 9, 13, 25, 37 🚀 Try our tools now👇 https://t.co/LizGMGPFh4 https://t.co/weDmtZxH4V

MacrocosmosAI
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