mmmatt retweeted
Ansem, you’re flexing $12.6 million in annualized Pump rewards. Show us how the followers generating that activity performed.
When followers become exit liquidity while the promoter keeps collecting, the slaughterhouse comparison writes itself.
Call it what you want. I call it blood money. Monetizing people’s trust and then bragging about the payout is fucking soulless.
Alon, where’s the promised Pump airdrop? Publish the allocations. Show what goes to users and what goes to promoters.
And the Kimchi idea you guys promoted raises the same question: what lasting value did buyers receive? If literal teenagers are part of the audience, explain the safeguards, the disclosures and who got paid.
Selling inexperienced people a future while treating them as a revenue stream is parasitic.
Stop funding these guys’ lifestyles with your money.
In my view, Alon and the people enabling this culture have helped ruin crypto. We need better leaders. A generation of young people deserves more than becoming someone else’s most profitable audience.
what the actual fuck
** IMMINENT STOCK MARKET CRASH OCTOBER 26, 2026-NOVEMBER 9, 2026 **
I am writing this message to give a detailed analysis, as to what I believe will be happening starting Monday October 26, 2026, and the main event to take place the following Monday November 2-3, 2026, with the bottom of the crash coming on November 9. I also want to explain what I believe the Federal Reserve is going to do as a means of trying to fix the crisis, and how it is going to lead to the end of the U.S dollar, bringing about a sovereign debt and currency crisis. This crisis will be the main focal point and issue that the Democratic Party is going to run on in the 26' midterms and the 28' elections, undermining the Republican Party and Donald Trump's populism, and eventually using it to try to usher in Communism, via a World Economic Forum/Black Rock policy and vision.
mmmatt retweeted
Gradient Boosting is an ensemble learning algorithm that constructs a powerful predictor by sequentially adding many weak learners, typically shallow decision trees. Starting with an initial model F₀(x), the algorithm iteratively updates
Fₘ(x) = Fₘ₋₁(x) + ηhₘ(x),
where hₘ is trained to approximate the negative gradient of the chosen loss function and η > 0 is the learning rate. For squared-error regression, this gradient corresponds to the residuals yᵢ − Fₘ₋₁(xᵢ), so each new tree attempts to correct the errors of the existing model.
From a statistical perspective, gradient boosting can be interpreted as functional gradient descent: instead of optimizing a finite-dimensional parameter vector, it performs optimization directly in a space of functions. Regularization through learning-rate shrinkage, tree depth, subsampling and early stopping helps control overfitting.
Gradient boosting is widely used in statistical machine learning for regression, classification, ranking and risk prediction. Modern implementations such as XGBoost, LightGBM and CatBoost have become important in structured and tabular-data problems. The method also connects statistical concepts such as empirical risk minimization and additive models with modern computational optimization, making it a particularly useful bridge between classical statistics and machine learning.
mmmatt retweeted
i'm baffled and disgusted by what pumpfun is doing. they're in a dominant position, but they keep trashing their own reputation with stupid marketing. partnering with a scammer, mocking their own users while profiting off them. it's just awful and gross.🤮
teapawt.org/Pumpfun/status/2116609…
mmmatt retweeted
Replying to @hean_ll
It's not always haram. Liberals definition is very narrow. They don't consider Husband emergency need. Also in war its is allowed.
mmmatt retweeted
In the 8 minutes before XPL dropped 18% today, 11 Hyperliquid accounts pulled $1.62M of margin out of their XPL longs.
Then they let the $12M position get liquidated into HLP at mark price.
HLP ate ~$0.6M.
Fresh accounts funded via CCTP. Test withdrawals 20-50 min before. 7 rejected withdrawals while scraping the margin to the limit. $0 left after.
Looks planned. Whether the same operator was short on Binance, I can't see.
Timeline (Nov 1, UTC) 👇
Oct 29-31
9 of the 10 largest accounts are created, each funded once via CCTP with $145k-$243k. On Hyperliquid the sender only shows as Circle's deposit wallet.
03:45-04:15
10 of the 11 make test withdrawals of $500-$1.6k.
04:24-04:32
10 accounts withdraw $98k-$232k each, $1.62M total.
7 more attempts get rejected: "Insufficient balance for withdrawal".
Every dollar the margin check allows comes out. The longs stay open.
04:32
XPL -18% in 1 minute, 0.086 to 0.0705.
$11.2M (144M XPL) trades on Binance perps in that minute.
Hyperliquid itself barely trades.
04:32:50-04:32:59
All 11 get liquidated into the HLP backstop vault, plus 19 small accounts.
160M XPL / $12.2M taken over at avg 0.0759, in a minute that printed a 0.0705 low.
After
All 11 accounts: $0.
Backstop vault: $1.00M to $0.44M while unwinding.
HLP daily PnL: +$21k to -$655k (~0.4% of the vault).
Why it works
Dumping $12M of XPL into the HL book would wreck your own exit.
Drain the margin first, and a small move is enough to trigger liquidation.
Liquidation hands the whole position to HLP at mark with zero slippage. HLP eats the drop after.
Same playbook as the Mar 2025 ETH whale that cost HLP $4M.
If they were also short on Binance, the crash itself was the profit.
Addresses + fills in the reply.
$HYPE $XPL









































