The dark web has massive marketplaces like Amazon. Ratings, reviews, product listings — except the products are stolen identities and login details. Yours might be listed right now.
Serus scans dark web marketplaces for your data and alerts you if it surfaces.
Explore for free.
HOW NEURAL NETWORKS ACTUALLY SEE YOUR DRAWINGS
Spent the weekend building and training a custom neural network from scratch to recognize hand-drawn shapes.
What you are looking at:
1. Left side Training loss dropping & accuracy curve climbing per iteration.
2. Center Live weight updates across $4$ hidden layers.
3. Right side Final probability output for Circle vs. Square vs. Triangle.
No black-box APIs, just pure math and python running underneath.
जहाँ चार दीवारें शिक्षा का मंदिर होनी चाहिए थीं, वहाँ नकल माफिया का बोलबाला था। परीक्षा केंद्रों पर छतों और रोशनदानों के सहारे चीटिंग कराने का खेल सपा शासन की असली पहचान बन चुका था।
#SPExposed#UttarPradesh
💰 $2,500 Activity Giveaway
We're running it back this month with an even bigger prize pool of $2,500!
The more you engage with our posts throughout the month, the better your chances of winning
🏆 5 Winners
💵 $500 each
How to enter?
1. Stay active all month by liking, retweeting, and commenting on our posts
2. Like & Retweet this post
3. Tag someone you'd share the prize with
4. Follow @swappedcom on Instagram for a bonus entry
Winners will be selected randomly based on activity across all of our posts throughout the month and announced on August 20, 2026
Good luck!
THIS IS F*CKING DANGEROUS INFO AT THE END
a 31-year-old actuary beat quant funds last year on a government file nobody reads anymore
Marcus, minneapolis - no bloomberg, no fund, one free csv every friday at 3:30pm
he didn't find a new signal. he found cftc's commitment of traders - public, weekly, free, and almost nobody reads past the headline
he went to "leveraged funds" net long on ES futures, normalized to a rolling 2-year range
late 2023 that column hit the 94th percentile
historical 3-month returns at that extreme: ~1.2% average, baseline is ~2.9%
january 2024 nearly ended it - crowding held extreme 6 weeks past any prior backtest, bleeding gains the whole stretch. week 5 he almost quit
then it cleared. best run that quarter hit ~7%, most months edge runs 1-2% per cycle
method:
download ES futures COT history at cftc[.]gov/dea/futures
look at "leveraged funds" net
normalize to 2-year range: (current - min) / (max - min)
above 0.85 or below 0.15 = crowding signal - market underperforms in crowd direction over next 4-6 weeks
save this, check the COT once. 10 minutes
data was never hidden. it just required reading past column 4
Everyone wants Claude to remember everything. That's exactly why their agents get dumber
A 200k-token window already holds a whole codebase, so recall was never the bottleneck - knowing what's worth keeping is.
The build I walked through above fixed drifting agents the opposite way a memory plugin does: it capped history at the last 20 messages on purpose, then leaned on checkpoint notes and rolling summaries. Not more memory. Compressed memory.
An agent that hoards every dead decision from three sessions ago doesn't get smarter. It reasons over garbage and confidently repeats mistakes it "remembers" making.
"Never forget" sounds like a brain. Real intelligence is knowing what to throw away - so what did your last agent actually need to forget?
Our newest game Western Wilds just dropped, this may be our most Volatile one yet
Gonna give away $1000 ($100 x 10) so you guys can try it
✅LIKE/RT
✅Follow us
✅Tag a friend
$2 500 GIVEAWAY 👇
How to enter:
✅ Follow @parimatch
✅ Repost this post
✅ Hit like
$1 000 if Yamal scores
$1 000 if Messi scores
$500 if they both find the net
After the match, we’ll choose 10 winners from everyone who predicted correctly and send out the prizes.
Drop your prediction in the comments 👇
#Parimatch #Giveaway
⚽️ QUICK REMINDER: @OneFootball is storing their entire football content library on Walrus.
@OneFootball is backed by elite clubs including Real Madrid, FC Barcelona, Bayern Munich, Liverpool, Arsenal, Chelsea, Manchester City, Juventus, and PSG. They partner with 200+ clubs, leagues, and federations across 194 markets, serving 200M+ monthly users.
Enterprise-grade data infrastructure that actually scales 🦭