Open Vision AI for everyone. Score Studio + SN44
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We are ready to build worlds.
Currently fire-testing the new incentive mechanism that will get miners to build our first ever generative world model, capturing real physics, long-term consistency, and true interactivity.
This is the unreal next chapter for vision AI: from understanding scenes to generating entire, livable realities.
This 👇 is a sneak peek of the subnet’s console, where users will be able to create worlds from a single prompt and very soon explore them right in their browsers.
This will also 100x our ability to train better vision models by providing unlimited simulated scenarios.
44 we go.
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Tune in
🚨 Subnet Summer TAO X Spaces - October 28, 2026 | Wednesday at 5PM GMT
𝗧𝗼𝗽𝗶𝗰: 𝗧𝗵𝗲 𝗙𝗶𝗿𝘀𝘁 𝗣𝗼𝘀𝘁-𝗛𝗮𝗹𝘃𝗶𝗻𝗴 𝗬𝗲𝗮𝗿: 𝗪𝗵𝗮𝘁 𝗜𝘁 𝗥𝗲𝘃𝗲𝗮𝗹𝗲𝗱 𝗔𝗯𝗼𝘂𝘁 𝗧𝗔𝗢’𝘀 𝗣𝗮𝘁𝗵 𝘁𝗼 𝟮𝟬𝟮𝟳
The halving didn’t just cut emissions. It stress-tested every part of Bittensor at once.
Four voices, four angles: capital, on-chain data, building, and validating.
Speakers:
• Mark Jeffrey (@markjeffrey) - @stillcorecap
• Mog (@mogmachine) - @taostats | @hippius_cloud | @vidaio_ | @blockmachine_io | @say_gm_
• Max Sebti (@MaxSebti) - @webuildscore (SN44)
• Tribit (@iamtheloraxnow) - Medulla Labs | @subnetsummerTAO
• Bryden (@SubnetSummerT) - @subnetsummerTAO
Join us this Wednesday for a high-signal conversation on what the first post-halving year means for Bittensor’s path to 2027.
Set your reminder and join the discussion.
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John Wick with wall hacks
The overhead hallway fight in John Wick 4 has the best choreography I’ve ever seen in an action movie. One unbroken shot, dozens of people, smoke, muzzle flashes, bodies everywhere.
So I made it my stress test. Raw run, misses and all. Dark corners and people on the floor are where it struggles.
What scene should I break it on next?
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Last week on SN44
2 tasks more than doubled their baseline, fallen person detection and beverage detection. cricket delivery stayed the most contested all week and went from 62 miners to 80
We’ll keep raising the bar
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We’ve been busy
One of the things I’ve been testing at @webuildscore. Can’t say much yet, but you can see the difference.
On top, the boxes jump around and miss half of what happens between frames. Below, they just stay locked on.
It’s a small thing until you’ve watched the choppy version for a few weeks. More soon.
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He woke up like this
computer vision companies are dying from long use-case → model → deploy feedback loops.
they run out of runway before they can even find the right use case.
meanwhile CV is being commoditised in real time on sn44.
every niche will be covered.
if you run a computer vision company, the miners are coming for you or are here to help depending on how you want to approach this.
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Orange juice production line, tracked end to end 🍊
On a food production line, every unit that passes the camera matters. What goes in, what jams or falls off, and what comes out at the end usually gets checked by eye, or not at all.
Our vision models can handle it. Track every orange from the sorting line to the juicer, and any gap can be flagged before it turns into waste.
Pulp fiction, now with bounding boxes.
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We set the target at 90%. Miners came back with 98%.
Fallen person detection on SN44 went from a 43.6% baseline to 98% on crowded street footage, scored in public every hour. Open weights.
So we're raising the bar. Harder footage goes in next, and the difficulty keeps climbing from here.
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We got flying cars before GTA 6.
Model said "vehicle", but was wrong. Tesla Roadster it is. one sentence later it was tracking it through the whole showcase.
A first look at the new Studio. More soon.
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Haters will say it’s AI, our detector didn’t ask though.
Building your own is about to get a lot easier. More soon.
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A farmer drove his tractor into his neighbor's burning field and cut a firebreak while the fire was coming straight at him.
Not every field has a guy with a tractor next door. Our Fire and Smoke Detector is open source. Put it on a drone or a helicopter cam and it flags the smoke way before it gets to this point.
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We ran a GTA 6 "leaked" dirt race through Score Studio.
Every rider, every bike, every truck kicking up dust got picked up, the model didn’t miss a single overtake.
Rockstar, if you’re reading this, we’d like early access purely for research purposes.
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We can’t wait to see miners obliterate this baseline
this short clip is a big moment for us.
we generated it with our world-model baseline, marking a first tangible step in our journey from computer vision toward spatial intelligence.
recognizing an aisle is familiar territory. generating what that place could look like as a camera moves through it opens a different set of possibilities.
we supplied one AI-generated store image and a camera path and our baseline, produced 49 frames at 512×512, alongside an estimate of the visible 3D surfaces.
artifacts are obvious. unseen views are predictions, and reliable physical simulation remains ahead of us.
but seeing this first walkthrough emerge from our own pipeline feels amazing.
it’s a glimpse of what we’re building toward: worlds we can explore, layouts we can test, and environments where cameras and robots can learn before deployment.
imagine where miners will take this.
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They said Studio was too complex, a bit boring, and too much like the competition.
So we’ve torn it apart to build the smartest Vision AI companion powered by Bittensor: Nokta.
It will make old Vision AI tools look like what they are…old.
NEWS: @webuildscore is rebuilding Score Studio on Subnet 44 around early-user feedback, with a relaunch planned across main platforms. The team reports 143 individual free users and a 3% conversion rate, excluding B2B partners.
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