Max

@MaxScore • 5,624 subscribers

building machines that understand what they see | @manakoai | @webuildscore ⎸ sire ⎸ opinions are my own

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Anya Rossi

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companies are paying 6 figures per month to get footage like this annotated by humans miners on SN44 are cracking it in real time on our private track building vision agents that can watch and understand sport

companies are paying 6 figures per month to get footage like this annotated by humans miners on SN44 are cracking it in real time on our private track building vision agents that can watch and understand sport

23,886 views • 3 months ago

tired but happy onwards and upwards

tired but happy onwards and upwards

14,498 views • 2 months ago

this will be our first $TAO sub-subnet 44 a neural-architecture competition to measure how position and movement patterns drive specific outcomes (here: a goal) built to supercharge our TurboVision model with action-prompting abilities, using probabilities inferred from miners’ outputs

this will be our first $TAO sub-subnet 44 a neural-architecture competition to measure how position and movement patterns drive specific outcomes (here: a goal) built to supercharge our TurboVision model with action-prompting abilities, using probabilities inferred from miners’ outputs

26,989 views • 11 months ago

on the left: SAM3 on the right: Manako's base model with our new workflow, it takes us 15 minutes to go from left to right AND THEN we get miners to improve the base model, making it more accurate, faster, and cheaper via a fully automated manifest generating process i don't know about you but i love this game

on the left: SAM3 on the right: Manako's base model with our new workflow, it takes us 15 minutes to go from left to right AND THEN we get miners to improve the base model, making it more accurate, faster, and cheaper via a fully automated manifest generating process i don't know about you but i love this game

16,011 views • 5 months ago

we live in a $TAO simulation in a few months we went from a whitepaper, a concept, a dream (kinda) to now generating 3d simulations based on our own neural network (that we’re training using Celium btw) this is what Score - Subnet 44 is about: > collecting visual data > creating visual models > generating a ‘real time’ positional value function aren’t you entertained? I love this game!

we live in a $TAO simulation in a few months we went from a whitepaper, a concept, a dream (kinda) to now generating 3d simulations based on our own neural network (that we’re training using Celium btw) this is what Score - Subnet 44 is about: > collecting visual data > creating visual models > generating a ‘real time’ positional value function aren’t you entertained? I love this game!

19,378 views • 1 year ago

one of the biggest hurdles in computer vision is that the front end actually matters. you can’t just build models and call it a product. that’s why we’re building Manako. we see it as a “control plane” for visual intelligence. where data, policies, and operators meet. where vision stops being research and starts having real impact in the physical world. this is built for people running real systems. operators who can do 1,000x more when vision is packaged as a real ai product from a dev perspective, we’re already 2 months ahead of plan. now the focus is polish, usability, and connecting it directly into the subnet. build with vision.

one of the biggest hurdles in computer vision is that the front end actually matters. you can’t just build models and call it a product. that’s why we’re building Manako. we see it as a “control plane” for visual intelligence. where data, policies, and operators meet. where vision stops being research and starts having real impact in the physical world. this is built for people running real systems. operators who can do 1,000x more when vision is packaged as a real ai product from a dev perspective, we’re already 2 months ahead of plan. now the focus is polish, usability, and connecting it directly into the subnet. build with vision.

10,537 views • 6 months ago

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