Hello all,
Apologies for the delay as I've just woken up to this. We are still here and not going anywhere.
We’ve identified that ~2500 TAO was transferred out of the subnet owner account, and my personal twitter account, @isabella618033, has been deleted.
We are still investigating what happened and working to understand the full scope of the issue. As mentioned we are still here and will continue building while we work through this.
Stay tuned for updates as we figure this out.
Thanks for your support
I have many graduates coming up the next few months. Which means there will be many openings for new students.
Learning the market place is quite simple when you’re not listening to people who never made it or trade live with you.
🧵 Thread: How Pros Take Losses and Sit on Their Hands
1/ Most retail traders lose money not because their ideas are bad — but because they can’t handle losses like professionals and refuse to sit on their hands.
The edge isn’t in predicting markets. It’s in emotional control and discipline. Let’s break it down.
Most traders lose because they never review who they were last week.
Weekend journaling is where the real edge is built.
Here’s how to move forward into a new trading week after reviewing your trades 👇
1/
Your weekend review is NOT about beating yourself up.
It’s about pattern recognition.
The market already took your money if you made mistakes.
Don’t let it take the lesson too.
Most traders aren’t addicted to losing.
They’re addicted to dopamine.
There’s a massive difference between trading a SYSTEM and trading stimulation.
And until you understand it, you’ll keep sabotaging yourself. 🧵
1/ Been trading full-time for a few years, and if I’m honest, one of the smartest habits I ever built is sitting down every weekend to review my trades.
It’s not flashy, but it’s quietly one of the highest-ROI things I do. Small edges stack up, and staying sharp keeps the profits compounding.
Here’s why I record every trade and still journal by hand:
A 4B-parameter model on SN97 is now scoring 0.94 on HumanEval — beating its 35B-parameter teacher (0.872) by nearly 7 points on code generation.
8.75× smaller. Better at the actual task. On consumer hardware.
This is what distillation is supposed to do.
https://t.co/dph40wxgMW
Running a 1T-parameter model on your phone.
That's the dream of distillation. Compress frontier AI down to something anyone can run on consumer hardware — losslessly enough that the small one stays useful where the big one was useful.
SN97 is a 24/7 open competition for that.