Max

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Max

@MaxScore

co-founder and ceo @manakoai | core-contributor @webuildscore subnet 44 & @sire_agent ⎸ prev: @crunchdao ⎸ opinions are my own

Paris, France Присоединился Ağustos 2017
2.5K Подписки4.9K Подписчики
Max
Max@MaxScore·
"now, in every human question, there is something more powerful than strength, than courage, than genius itself: it is the idea whose τime has come."
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Max
Max@MaxScore·
@arnod3f nah... no cars involved
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Arno
Arno@arnod3f·
@MaxScore it’s about your new bigger car. much bigger. 😄
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Max
Max@MaxScore·
@80085anon @webuildscore need a comms & legal sign off first, i'm as impatient as you are
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Max
Max@MaxScore·
@TlTtry @MilkRoadAI vision ai applications are vast and will help unlocking new growth opportunities for companies while collecting critical data (human policies) to train new type of models
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Milk Road AI
Milk Road AI@MilkRoadAI·
If you think AI collars on cows are wild, wait until you see what happens when the animals reach the kill floor. Cargill is the world’s largest private company, pulling in over $160 billion a year. It just wired its slaughterhouses with AI cameras that watch every single cut a worker makes. And the system is already running across multiple plants. The software is called CarVe and it uses computer vision to scan every carcass on the line in real time. Each worker gets an instant score on their screen such as green, yellow, red. Red means meat was left on the bone and it means you failed. Zoom out and look at the timing. The US cattle herd just hit its lowest level since 1951, down to about 86 million head. Ground beef just hit a record high near $6.70 a pound, up more than 70% since 2020, setting fresh records for months. There is not enough beef. So the biggest meat company on earth turned to AI to squeeze every last ounce from every animal that does come through. Cargill says a 1% improvement in yield equals roughly 200 million more pounds of beef a year. They are already clawing back about half a percent on certain cuts. That is worth hundreds of millions of dollars and here is where it gets dark. The cameras are not just tracking the meat. Reporting from the Colorado Sun says CarVe also monitors how fast an employee works, how sharp their knife is, even their emotional behavior. This is not a Silicon Valley lab, it's a slaughterhouse, scoring human emotions with AI. Cargill poured around $90 million into expanding this system at a single plant in Fort Morgan, Colorado, after first deploying it in Friona, Texas, and is rolling it across all eight of its US and Canadian beef plants. And the industry gave it a 2026 “Big Innovation” award.
Milk Road AI@MilkRoadAI

This is WILD. Peter Thiel just bet $2 billion on a collar that wraps around a cow’s neck. The company is called Halter and it has a proprietary algorithm that runs the entire operation. They actually trademarked the name for it and called it the Cowgorithm and here's how it works. A farmer opens an app, taps a button, and 600,000 cows across three countries start walking toward the milking station on their own. No farm dogs, fences or physical labor, it's just a solar-powered GPS collar sending sound and vibration cues to each animal. The collar does more than move cows around. It monitors digestion, fertility cycles, and health patterns in real time, 24 hours a day, using machine learning trained on the behavior of hundreds of thousands of animals. Halter was founded by a rocket engineer who built spacecraft at Rocket Lab before deciding that farming was the bigger unsolved problem. US ranchers alone have already used the technology to build over 11,000 miles of virtual fencing, roughly the full perimeter of the continental United States, saving an estimated $220 million in physical fencing costs. Halter's previous funding round valued the company at $1 billion. This new round, led by Thiel's Founders Fund, doubles that valuation to $2 billion before the new money even hits the account. And they charge farmers between $5 and $8 per animal per month on a subscription model, meaning the more cows they collar, the more locked-in the revenue becomes. The most powerful venture capitalist on earth just decided that the future of food and farming runs through an algorithm named after a cow. He might be right.

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Max
Max@MaxScore·
@sneworoverteel imagine they have a $tao wallet address
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eeL
eeL@sneworoverteel·
@MaxScore Is it Pep or Klopp? 😀
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Max
Max@MaxScore·
“hey manako, create an ai scout that will find the next Messi. make no mistakes”
Score - Subnet 44@webuildscore

Score x @Eyeballfootball We're partnering with Eyeball to bring Vision AI to youth football, turning match footage into real-time player development intelligence that helps identify and grow talent from grassroots pitches to elite academies.

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eeL
eeL@sneworoverteel·
@MaxScore It can’t be that good…?
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Max
Max@MaxScore·
@ProfesorTAO @webuildscore We’re about to launch a private track on the subnet to handle private data
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El Profesor de TAO
El Profesor de TAO@ProfesorTAO·
Enhorabuena equipo, creo de verdad que estáis construyendo algo increíble y que vais ser una pieza importante en el éxito de Bittensor. Sí me surge una duda que creo que será clave para la adopción empresarial: la privacidad. ¿Cómo lo estáis planteando en @webuildscore? Me refiero a si el tratamiento del vídeo puede ser una barrera a la hora de escalar en determinados sectores.
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Max
Max@MaxScore·
evolving from sports analytics to general-purpose vision AI was one of the most ambitious moves we’ve made so far. our first test after launching our new manifest generator workflow and our new evaluation framework is a clear success now it’s time to accelerate, like proper.
RVCrypto@RvCrypto

The first signs of how fast Score’s Vision AI on Manako is scaling are already here. In just 7 days, miners on $TAO Subnet 44 have already hit the 85% target for person detection. I’ll call it: with the new Manako infrastructure, Score is about to redefine what’s possible in Vision AI.

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Max
Max@MaxScore·
@RvCrypto faster
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RVCrypto
RVCrypto@RvCrypto·
The first signs of how fast Score’s Vision AI on Manako is scaling are already here. In just 7 days, miners on $TAO Subnet 44 have already hit the 85% target for person detection. I’ll call it: with the new Manako infrastructure, Score is about to redefine what’s possible in Vision AI.
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Tyler DurdΞth
Tyler DurdΞth@tylerdurdeth·
This is incredible. Every business operating CCTV is gonna want to use this tool to turn thousands of hours of passive recordings into useful information that can triggers action. IMO, @webuildscore is about to have a Templar moment. Built on Bittensor ($TAO)
Max@MaxScore

open router for vision ai, built on bittensor subnet 44 devs, ai agents, operators will use @manakoai to deploy vision ai pipelines via prompts, no infrastructure required $TAO sn44 builds and routes to the best available vision elements, updating as the network improves

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Max
Max@MaxScore·
open router for vision ai, built on bittensor subnet 44 devs, ai agents, operators will use @manakoai to deploy vision ai pipelines via prompts, no infrastructure required $TAO sn44 builds and routes to the best available vision elements, updating as the network improves
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Alex DRocks
Alex DRocks@DrocksAlex2·
$TAO in one picture
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Max
Max@MaxScore·
@RvCrypto good morning my friend
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RVCrypto
RVCrypto@RvCrypto·
Good morning $TAO fam
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Max
Max@MaxScore·
“the victors write it, the vanquished tell the story.” this is the signal you were waiting for to be on the right side of history.
Openτensor Foundaτion@opentensor

The largest decentralised LLM pre-training run in history. SN3 @tplr_ai trained Covenant-72B across 70+ contributors on open internet infrastructure. Now it’s being discussed by @chamath with @nvidia CEO Jensen Huang. Distributed, open-weight model training on Bittensor is getting started.

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Vidaio
Vidaio@vidaio_·
"Please fasten your seatbelts and ensure your seatback and tray tables are in their full upright position." From groundbreaking tools... To a complete intelligent ecosystem... "LADIES AND GENTLEMEN, PREPARE FOR TAKEOFF" Introducing: VidaioOS The next dimension in enterprise video management. $TAO @vidaio_
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Mark Jeffrey
Mark Jeffrey@markjeffrey·
Bittensor peeps: check out 31:44 - Templar sn3 discussed. @chamath -- they've achieved a *72* billion parameter model with decentralized training, not a 4 billion parameter model :)
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