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Score - Subnet 44

@webuildscore • 9,216 subscribers

Making every camera intelligent. An open, permissionless computer vision layer for the real world. Powering @manakoai · $TAO SN44

Shorts

The newest GTA 6 gameplay trailer dropped yesterday. we ran our subnet vision models on it. Person, car, gun, segmented and tracked across every scene. night, water, motion blur, freefall over the city. footage the model had never seen. The part that matters is that this isn't a huge model. it's tiny, and it runs near real time. Vision that works in the real world...and the fake one.

The newest GTA 6 gameplay trailer dropped yesterday. we ran our subnet vision models on it. Person, car, gun, segmented and tracked across every scene. night, water, motion blur, freefall over the city. footage the model had never seen. The part that matters is that this isn't a huge model. it's tiny, and it runs near real time. Vision that works in the real world...and the fake one.

678,141 views

The next World Cup star is playing right now, and nobody is watching. The 2026 World Cup is on, and millions of kids are dreaming of one day playing for their own flag. But the path there is almost impossible: no consolidated data, too many games, not enough scouts, human bias, and wrong place, wrong time. Any one of them can bury a generational talent before a scout ever sees them. That is what we are building to fix. So we developed a full automated annotation + action spotting model where it actually matters: grassroots football. Shaky cameras, awful angles, terrible lighting. But now nothing on the market beats sn44's v2.0 model on it. Check the last GT line, it’s human annotations. Simply because miners' outputs + post-process = magic. Post-process is a deliberate design choice. We point miners at the hardest 80% of the workflow, the part that is genuinely difficult to fake, and handle the rest downstream. Fewer places to game the system means a network you can trust. Every single challenge on sn44 can be an independent startup now. Let that sink in.

The next World Cup star is playing right now, and nobody is watching. The 2026 World Cup is on, and millions of kids are dreaming of one day playing for their own flag. But the path there is almost impossible: no consolidated data, too many games, not enough scouts, human bias, and wrong place, wrong time. Any one of them can bury a generational talent before a scout ever sees them. That is what we are building to fix. So we developed a full automated annotation + action spotting model where it actually matters: grassroots football. Shaky cameras, awful angles, terrible lighting. But now nothing on the market beats sn44's v2.0 model on it. Check the last GT line, it’s human annotations. Simply because miners' outputs + post-process = magic. Post-process is a deliberate design choice. We point miners at the hardest 80% of the workflow, the part that is genuinely difficult to fake, and handle the rest downstream. Fewer places to game the system means a network you can trust. Every single challenge on sn44 can be an independent startup now. Let that sink in.

430,045 views

We’ve onboarded several cracked computer vision engineers as alpha testers for Score Studio. One of them sent this video back with this note: “Crossed arms are basically an adversarial attack and it still called it. person 0.99, dog 0.98, 42ms / if it can catch a dog mid-dance, it can catch whatever's happening in your warehouse.” Btw, proving the app's utility by shitposting memes we've run through it could be a great marketing idea

We’ve onboarded several cracked computer vision engineers as alpha testers for Score Studio. One of them sent this video back with this note: “Crossed arms are basically an adversarial attack and it still called it. person 0.99, dog 0.98, 42ms / if it can catch a dog mid-dance, it can catch whatever's happening in your warehouse.” Btw, proving the app's utility by shitposting memes we've run through it could be a great marketing idea

19,775 views

Put Computer Vision on Autopilot. Generate data. Label it. Train models. Evaluate every candidate. Deploy the winner. Automatically. Score Studio waitlist is open →

Put Computer Vision on Autopilot. Generate data. Label it. Train models. Evaluate every candidate. Deploy the winner. Automatically. Score Studio waitlist is open →

12,002 views

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IT’S COMING HOME 🏆 Out of 1000+ startups that applied to the Signal Week (formerly Paris Blockchain Week) startup competition, we take the win. Big moment for us and for the Bittensor eco. Huge congrats to Arno and Archie Grant on the stage today.

IT’S COMING HOME 🏆 Out of 1000+ startups that applied to the Signal Week (formerly Paris Blockchain Week) startup competition, we take the win. Big moment for us and for the Bittensor eco. Huge congrats to Arno and Archie Grant on the stage today.

Score - Subnet 44

4,672,634 views • 4 months ago

Score x CARD Cricket is the world’s second-largest sport, yet advanced analysis hasn’t been widely accessible. Together with CARD, we’re bringing frontier Vision AI to the game. From talent ID and player pathways to predictive insights for clubs, franchises, and national teams.

Score x CARD Cricket is the world’s second-largest sport, yet advanced analysis hasn’t been widely accessible. Together with CARD, we’re bringing frontier Vision AI to the game. From talent ID and player pathways to predictive insights for clubs, franchises, and national teams.

Score - Subnet 44

845,677 views • 9 months ago

No one else can do this. While every other CV platform is still selling another fine-tuning dashboard We’re about to let anyone order actual frontier lab work in a few clicks. The kind only Bittensor miners can deliver. Model Foundry is coming to Score Studio. Zero compute? Zero data? Zero ML team? Doesn’t matter. You describe the hard vision problem, our miners build the production model, you pay inside the Studio. That spend goes straight into SN44 buyback + burn. Money never leaves the subnet. No gatekeepers. No bottlenecks. Just open frontier vision for everyone. Check out the Model Foundry flow 👇

No one else can do this. While every other CV platform is still selling another fine-tuning dashboard We’re about to let anyone order actual frontier lab work in a few clicks. The kind only Bittensor miners can deliver. Model Foundry is coming to Score Studio. Zero compute? Zero data? Zero ML team? Doesn’t matter. You describe the hard vision problem, our miners build the production model, you pay inside the Studio. That spend goes straight into SN44 buyback + burn. Money never leaves the subnet. No gatekeepers. No bottlenecks. Just open frontier vision for everyone. Check out the Model Foundry flow 👇

23,968 views • 9 days ago

Score x Reading FC Over the next year with Reading FC, we’ll build vision AI models that turn match footage into game changing insights for their coaches and players, and systems that make stadium operations smarter and more efficient for elite sport organisations.

Score x Reading FC Over the next year with Reading FC, we’ll build vision AI models that turn match footage into game changing insights for their coaches and players, and systems that make stadium operations smarter and more efficient for elite sport organisations.

Score - Subnet 44

437,731 views • 9 months ago

Next growth move for Score Studio: Native Vision AI plugins for every vibe coding tool. Starting with Cursor. Hoping to land in the official marketplace soon.

Next growth move for Score Studio: Native Vision AI plugins for every vibe coding tool. Starting with Cursor. Hoping to land in the official marketplace soon.

16,400 views • 8 days ago

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.

11,075 views • 5 days ago

We’re preparing the launch of Score Studio. Ad campaigns will roll out gradually, and we’ll be launching it across platforms like Product Hunt and others. This is the first version of the first video we’ll use for ads, not the final one, but we couldn’t wait to share with you what we’ve been up to. It’s also the start of a longer series of videos to support our growth strategy for this subnet-owned product. PS: It’s such a pleasure to be working with Mob Studios

We’re preparing the launch of Score Studio. Ad campaigns will roll out gradually, and we’ll be launching it across platforms like Product Hunt and others. This is the first version of the first video we’ll use for ads, not the final one, but we couldn’t wait to share with you what we’ve been up to. It’s also the start of a longer series of videos to support our growth strategy for this subnet-owned product. PS: It’s such a pleasure to be working with Mob Studios

17,912 views • 11 days ago

$Roboflow charges you for models you have to verify yourself. Introducing Score Studio: the decentralised alternative where every model arrives already proven and ready to work in real world conditions. Every model on the platform is battle-tested through SN44's validation mechanism before you ever touch it. Miners compete, validators score, only the winners survive. You get the output of a permanent open competition, at a fraction of the price. Datasets, annotation, training, deployment. All of it cheaper. All of it validated, accurate and efficient. Need a model that doesn't exist yet? Launch your own model inquiry from the Studio and put the network to work on it. Pay in USD or SN44, straight at subnet level. We're putting the final touches on it now.$

Roboflow charges you for models you have to verify yourself. Introducing Score Studio: the decentralised alternative where every model arrives already proven and ready to work in real world conditions. Every model on the platform is battle-tested through SN44's validation mechanism before you ever touch it. Miners compete, validators score, only the winners survive. You get the output of a permanent open competition, at a fraction of the price. Datasets, annotation, training, deployment. All of it cheaper. All of it validated, accurate and efficient. Need a model that doesn't exist yet? Launch your own model inquiry from the Studio and put the network to work on it. Pay in USD or SN44, straight at subnet level. We're putting the final touches on it now.

34,998 views • 25 days ago

Computer vision engineers are still duct-taping tools together just to get a model into production. We just finished another round of user interviews and that frustration came up again and again. So we re-designed Studio to work around our new Pipelines + Workflow Canvas features. Visually design any vision pipeline from start to finish, connect models, logic, and outputs on one canvas, preview the exact result, then deploy. You see the output before you ship it. Everything in a single interface. The full loop, shaped by the people who actually build vision systems every day. This is what Decentralized Vision Intelligence looks like.

Computer vision engineers are still duct-taping tools together just to get a model into production. We just finished another round of user interviews and that frustration came up again and again. So we re-designed Studio to work around our new Pipelines + Workflow Canvas features. Visually design any vision pipeline from start to finish, connect models, logic, and outputs on one canvas, preview the exact result, then deploy. You see the output before you ship it. Everything in a single interface. The full loop, shaped by the people who actually build vision systems every day. This is what Decentralized Vision Intelligence looks like.

10,794 views • 12 days ago

Score Studio does both. Native local inference, compute & storage. Native integrations with Chutes engy.ai Good Morning lium.io Hippius. Local + Decentralized. Done.

Score Studio does both. Native local inference, compute & storage. Native integrations with Chutes engy.ai Good Morning lium.io Hippius. Local + Decentralized. Done.

Score - Subnet 44

13,188 views • 16 days ago

$300M AUM $DKING Partnership ✅ Live at Proof of Talk, revealed the new DKING → SIRE partnership with one of the world’s largest sports-betting hedge funds. They’ll deploy $300M AUM using DKING’s DeFAI strategies, starting this 2025/26 season. $TAO Watch the moment 🔽

$300M AUM $DKING Partnership ✅ Live at Proof of Talk, revealed the new DKING → SIRE partnership with one of the world’s largest sports-betting hedge funds. They’ll deploy $300M AUM using DKING’s DeFAI strategies, starting this 2025/26 season. $TAO Watch the moment 🔽

Score - Subnet 44

25,446 views • 1 year ago

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