
Freedom and Liberty. @chutes_ai full-port
Joined February 2021
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- Following875
- Followers280
- Likes6.6K
CryptoTrigger retweeted
SN 64 @chutes_ai with 800k users, phD research level papers on AI bottlenecks, real world implications, combatting hardware shortages with smart training systems, is valued half of a gpu rental marketplace SN 51 @lium_io.
HALF BROTHER, we're talking HALF. Something that adresses global, real world commodity bottlenecks.
I am feeling refreshed and confidently holding. I want to part take in this movement. Everything will fall into place.
The future of inference in processing efficiently, not processing volume
$TAO @chutes_ai
.@chutes_ai: purposely cuts low end models reducing volume but upping revenue per token, highlight this as a key metric in their structure
Some particular people: Hah! Volume is down, Chutes is dying 🤓
$TAO
CryptoTrigger retweeted
The problem is not pow registration. It's Null Consensus. This is the culmination of the unresolved Validator weight-copying problem.
Whether const mines or not i dont even care because even if he says he doesnt, nobody can prove it.
Null Consensus means Yuma Consens is not useful all the time and that the purpose of Validators is not as relevant as it should.
It's admitting that the incentive system is flawed at the validation level and that it needs to be bypassed in some cases.
So Yuma Consensus, which was the moat of Bittensor because it was meant to make products trustless and miner scoring fair, is now openly declared irrelevant on-demand. Why do you think there are even big entities using the Yuma name in their brand? because it was a central aspect that made Bittensor uniquely positioned to be a legit decentralized network where proof of useful work is verified mathematically instead of using trust me bro.
With this admission comes eTao next which will allow subnet owners to make the emissions split different than 41% valis / 41% miners / 18% subnet owners... yeah i fucking hope the subnets with no validator purpose will reduce the 41% sent for validators, no shit
Im tired of all these wild swings that look like yolo decisions to test results in production
Nobody can say anything really, it just happens and we must adapt. Fair. But this isn't a 1000-year decentralized federation lol
This is a cool database that Const can shut down when he wants, with ponzi-like micro companies within a niche of another niche (crypto)
Kinda crazy how @chutes_ai is doing the most “if this succeeds the world changes” stuff in crypto right now and has the least amount of bid among the top subnets
$TAO $dTAO
CryptoTrigger retweeted
github.com/chutesai/epigenes…
Still experimenting, but seems to check out. Smaller, faster, better? Models that grow with you (or your repo, or proprietary company docs, etc.)
Short term exact recall is the context window.
Context window feeds training continuously, binary optimizer.
This becomes stored knowledge and higher order perceptual understanding over time, not just RAG.
Sparse MSA global attention already selects most important tokens to attend to in longer context, so you can reinforce those parts more.
🤖 Made with AI
There's another magic trick (aka cool math) I believe this parallax enforced sparsity enables by the way...
arxiv.org/abs/1711.05769 <- prune weights, adapt the pruned weights, sharply cuts catastrophic forgetting risk.
If you have a model with the enforced sparsity, 50% of the weights are locked in to particular patterns. What if you mask the other expert weights leaving only those sparse contiguous weights to learn new data?
That's the intuition, perhaps it works, perhaps not. But... if it does, it would make the base model significantly more malleable for new domains/tasks/whatever. SFT/continued pretraining with less risk of catastrophic forgetting and without lots of magic tricks and RL and re-sampling in your own words etc.
CryptoTrigger retweeted
271 views, zero likes, what? Pretty neat. arxiv.org/html/2506.13771v1
[Tech Blog] LittleBit revolutionizes LLM compression with ultra-low bit-widths, enabling powerful models to run on tiny memory budgets while maintaining top-tier performance.
#AI #LittleBit #LLMCompression #EfficientAI
research.samsung.com/blog/Li…
$TAO in a tight range of $304.1-$304.3. Break above and I expect a revisit to $305, below and I expect us to drop to $303 again
Mammoth $TAO breakout to $307, but don’t be surprised if we see a major correction back to $306.5 here
CryptoTrigger retweeted
The last Bittensor decentralized training algo that pumped $TAO to 350$ was worse than Parallax and its founder was motivated by greed (exited to cash out 10m $)
Parallax is better on every levels and @jon_durbin is doing it for his kids future
Not the same kind of pump ahead of us










