Young buck, Tao, That is all

Joined March 2022
Milan is a world-famous city and the one that hosted the last Olympic Games Milan’s leading scientific university is sounding the alarm about the various dangers posed by data centres, as explained in this article from the city’s most prestigious newspaper If you look back through my posts, you’ll see that I had already sounded the alarm some time ago After all, I like to be ahead of the pack – and not just when it comes to trading Subnets… By the time data centres are banned or scaled back in some way, $Tao and Subnets will already have grown enormously and will have gained further momentum I feel sorry for those who will start buying Tao and Subnets And in any case, their biggest problem will be not having multiplied their Tao holdings over the years through spot trading in Subnets Are the authorities in your town or country also realising the dangers of data centres, or are their eyes still clouded by the money involved? Let us know in the comments Corriere.it milano.corriere.it/notizie/c…
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Danielson retweeted
Glad to be sponsoring @ExploitSummit. Open discourse and the exchange of ideas are what push Bittensor forward. Events like this are where that happens. Don’t miss it.
Most subnets talk about product-market fit. @LeadpoetAI went and got it. Enterprises using the product within the first quarter after launch. Shoutout to this silver sponsor of Exploit 2026. Sept 28–29 · Montréal: luma.com/exploitsummit26 - ticket prices increase on August 10th
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Danielson retweeted
Claude just hired Leadpoet to find its next customers. Leadpoet is the intelligence layer sales teams use to find and qualify companies most likely to buy. Now, with #OKXAI, other AI agents can access that same intelligence directly. Agents give Leadpoet a target customer profile. Leadpoet returns the companies worth pursuing, who to contact, and why now. We’re excited to be the first Bittensor subnet on the @OKX agent marketplace.
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Danielson retweeted
On today's Novelty Search, I was trying to figure out how Quasar did decentralized training. The answer was 'fragments' -- which are merged. "The key innovation is an MoE design that avoids all-to-all communication. Each miner trains their own expert independently." ^ I set my Hermes agent loose to figure it out. So there IS NO MERGING. It's not like 'slices'. It's a bunch of self-contained small expert models which BrundleFly later into a chorus. Completely gets rid of the training bandwidth / coordination issue.
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Danielson retweeted
Today, a Bittensor subnet - Quasar subnet 24 - claimed to have decentrally-trained a 120B parameter model -- with a 5 million token context window (!) More: @QuasarModels My Hermes agent dug into it, and it appears to be real. The model will be up on HuggingFace soon.
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Danielson retweeted
I just realized I study and build on bittensor 16 hours a day, watch subnets every hour & I am completely lost about what upgrade v440 is, i just caught up with the rust based decoder upgrade v431, I just learned a month ago what Net tao flow is, now emissions are priced based but theres another fix. Imagine the average holder? He has no clue and will never have one. I will have to build some sort of chain status frontend page for the community How can we all stay up to date in plain english, send me suggestions i’m ready to build $TAO #bittensor
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Donald Trump and his stooges are doubling down on stupid by ignoring that climate change is real.
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Danielson retweeted
That’s what he said
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The Department of the Navy takes the conduct shown in this video extremely seriously. Such statements and apparent intent to leverage a position to undermine the policies and direction set by our elected leaders are inappropriate and incompatible with the standards expected of Department personnel. Effective immediately, this individual has been placed on administrative leave while we determine next steps to ensure accountability and protect the integrity of our mission.
O’KEEFE UNDERCOVER: Senior Pentagon Director Caught On Hidden Camera: Spills On A “Gay” Date With O’Keefe That He WILL "Undo Whatever's Been Done [at the Pentagon]" After Trump Leaves Office To Reverse His Agenda… “I've seen some things. In true D.C. nature, you don't always reveal everything in D.C.” “I have the influence…., I can undo whatever's been done.” “I think Trump is a narcissist.” “Yeah. I think it's [War in Iran] completely stupid, but it's driven on one man’s [President Trump] ego to me, in my own personal opinion.” “I mean, you [O’Keefe] could be a news reporter.” @DeptofWar @SecWar @PeteHegseth @DepNavy @SECNAV @USNavy @DOWResponse
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Danielson retweeted
Replying to @martianwyrdlord
I’m down
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Replying to @nypost
Time to sue this liar
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Danielson retweeted
Missing the Germany match is not an option. We’ll get you to Canada! Check your DMs.🛩️ #FlyAirshare
Our connecting flight from Dallas to Canada has been canceled due to weather. They rebooked us on a flight tomorrow evening. We‘re gonna miss the Germany match💔
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Danielson retweeted
Kevin Warsh effectively just stated he doesn’t believe in the Phillips Curve trade-off between inflation and unemployment. Bravo.
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My girlfriend asked why I was smiling at my phone at 3AM. I lost my job last week. Rent due in 4 days. No backup plan. Then I found a 33-year-old nerd who turned $1,000 into $946,207 trading Bitcoin with a trick he stole from hurricane forecasts. No finance degree. No trading desk. Just a method every meteorologist uses and every trader ignores. The method: meteorologists never forecast tomorrow with a single model. They run 31 and count the votes. He applied that exact framework to Bitcoin. Built a Claude agent that reads every 5-minute BTC candle and feeds it into MiroFish simulator running 31 parallel prediction paths. Trade only fires when 28 out of 31 models agree. Below 26 votes? Trade dies instantly. The agent moves faster than any human trading desk: → Collects market data 24/7 without breaks → Runs continuous simulations inside MiroFish engine → Operates fully autonomous with zero manual input → Every trade executes only when consensus hits threshold → Every dollar captured is pure market inefficiency exploit That is the entire edge. Not prediction. Consensus. Position sizing follows Kelly criterion. Signal fires or it does not. Most signals fail the vote count, so the system stays flat most days. He spent years learning that certainty is a scam and consensus is the only edge that matters. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word Claude 2. Like and retweet this 3. Follow me @codewithimanshu so I can DM you Save this post. Build the consensus system this week. Start with $200. Scale on evidence.
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Danielson retweeted
yeah this is legitimately significant training on bittensor infrastructure and already outperforming centralized 72B models with that token efficiency is exactly the validation decentralized AI needs. proves the network can host competitive LLM development. builds on subnet 9's orion-100B run from last week. bittensor is stacking proof points that distributed training works at scale. and you caught the key part - this is the PREVIEW. if they're beating covenant at this stage the full release could reshape expectations for what decentralized infrastructure can deliver
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🚨 HUGE drop from @QuasarModels just now! Quasar-Preview is officially out. Their first public proof that the architecture actually works at scale: - 18B MoE (2B active) - 5 MILLION context window 🔥 - Built with Loop Transformer + Quasar attention - Trained fully decentralized on Bittensor Still early but already showing insane long-context performance. The future of massive context models is here. Let’s push it together! #Bittensor #Quasar #LongContextAI
Today we’re releasing Quasar-Preview! Our first public proof that the Quasar architecture works at real scale. [ 18B MoE - 2B active / 5M context ] Built with Loop Transformer + Quasar attention Trained on Bittensor through decentralized infrastructure 👇
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Danielson retweeted
Today we released Quasar-Preview. Our first public model in the Quasar series. it is the first real proof that our architecture works at scale. 18B MoE. 2B active. 5M context config. Proud of the team. More soon..
Today we’re releasing Quasar-Preview! Our first public proof that the Quasar architecture works at real scale. [ 18B MoE - 2B active / 5M context ] Built with Loop Transformer + Quasar attention Trained on Bittensor through decentralized infrastructure 👇
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Danielson retweeted
5M context length agentic model from Quasar.
Today we’re releasing Quasar-Preview! Our first public proof that the Quasar architecture works at real scale. [ 18B MoE - 2B active / 5M context ] Built with Loop Transformer + Quasar attention Trained on Bittensor through decentralized infrastructure 👇
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Danielson retweeted
Replying to @ahmd2ta
Agreed. Stoked we are training on 3 with you guys
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Danielson retweeted
Replying to @DrocksAlex2 @OpenAI
There is a difference between memory systems in apps and memory systems in architectures. Every AI app uses a memory system, usually simple .md files or external storage. But we built the architecture for long context from the ground up.
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