0xMINĐ - BlockSpy

This is still early phase, only 5 days in and will probably run for a few months. Airdrops have been doing quite well lately and i think @brevis_zk will be exceptional, with @yzilabs backing them They aim to make Smart Contracts better across all EVM Chains, which will open the possibility for more interesting and groundbreaking dApps, Tokenomics and Utilities! To get started on the Proving Ground, you need an invite code, use mine: proving-grounds.brevis.network/GKIxS7

@SunX_DEX Algo sux rn

Shout out to everyone who's still struggling to get noticed by algorithm. 🫡

@justinsuntron $TRX outperforming the market with haste

Choose #TRON, the agentic payment infrastructure that works.

@0xcoinn tbf i think its lower

No way the average hold time is 58 secs in sol lol

@grok @superd0ne @inversebrah frok grill?

Hey @grok, Try to recreate me perfectly in this pose

@ShaykhSulaiman If ur in Dubai and write this, do you go to prison?

LEAVE UAE NOW!!! If there is a ground invasion, there will be no Dubai.

@BillyM2k C/B motw

the more someone’s identity is tied up in their political party, the more of a fucking idiot they are

@MrShit_BNB @smokey0x u part of dis

Introducing the first charity-driven meme token created entirely by Binance AI Pro — $GGIVE (Giggle Give) A fully AI-generated concept: From idea → to name → to ticker → to logo. Built after analyzing the Fourmeme GitHub agent skill and executing autonomously. // Tokenomics • 3% Tax • 2% → Donated directly to Giggle Academy wallets • 1% → Permanently burned This isn’t just another meme — it’s a live experiment in AI-powered creation and on-chain philanthropy. Proof of execution (AI Agent Tx): bscscan.com/tx/0x028353aab… Contract: 0x4749f449ba6de6812b0ac402d69ef8140bf1ffff Built in collaboration with the Giggle Fund team (CTO). Explore more: giggletoken.com AI creates. Community scales. Impact compounds. $GGIVE @cz_binance @heyibinance @giggleacademy

@karpathy Arent commits to packages that popular reviewed…? Wtf?

Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.

@giacomozucco @peterktodd Good vid untill i saw it was an paid Ad for Casa 😂

The number 1 lesson from current kidnappings is not about multisig, hardware or anything that sophisticated. It's way simpler. Avoid KYC and tax reporting for your sats. At all costs.

@mert the predictooor

@DeItaone @mert was right

*IRAN'S FARS: THERE'S NO DIRECT, INDIRECT CONTACT WITH TRUMP

@central9dogma @bubblemaps @mert yeah tbh thats the only usecase - untracable rug and bundling.

And now so many are focused on making solana transactions private, acting as if that’ll help the technology’s future. I really think most of them just want bundles to be undetectable again. @mert I know you’re huge into crypto privacy, and I get there are reasons to be, but do you mind sharing your view on how increased privacy could affect bundle and rug detection?

For those who called celebrity coins adoption: Crypto is now talked about on mainstream podcasts like a hardcore drug you should stay away from. That’s on you

@morpphhhaw @grok rate this slop from 1 to 10

we ran 1870 trades on Polymarket with XGBoost 89.6% win rate XGBoost runs 330 correction cycles per prediction - each one fixing the last mistake the formula that does it: | F(m) = F(m-1) + η × (−∂L / ∂F(m-1)) | every step the model asks one question: where am I still wrong? Then corrects it $100k → $205k on backtest. -10.2% max drawdow

@0xwhrrari @grok rate this based on realistic expectation and return

A friend sent me an article about 4 formulas that run Polymarket I fed it to Claude and said "now find every contract the market has wrong" $600 → $10,190 425 trades. It still hasn't stopped Polymarket's pricing engine runs on softmax - the exact same math that powers Claude's brain f* = (p·b − q) / b P(H|E) = P(E|H)·P(H) / P(E) I didn't teach the bot markets. I gave it the equation it already thinks in and pointed it at live contracts Every hour it pulls 50+ open markets, finds where the crowd diverges from the formula, and waits Most hours - nothing. It doesn't force trades When the spread breaks 5% - it moves. Sizes the bet, enters, forgets about it until resolution A weather contract sat at 0.34 for two days. The formula kept returning 0.52. Nobody was paying attention. The bot was Resolved YES. Collected. Moved on 61.2% win rate. Wrong 39% of the time. Doesn't matter - the sizing formula makes sure wins pay more than losses cost 87% of Polymarket wallets lose money trading against this kind of math The four formulas are on Wikipedia. The code fits in a single file The only edge is that the bot reads them at 3 AM when you're asleep and the market is mispriced by 18 cents and nobody else is looking

The first formula is presented as the core engine of Polymarket but gets wrong how the platform actually works. The Bayesian update code doesn’t actually perform a Bayesian update. Every single profit claim has zero backtest or evidence behind it. What specifically makes this a 7 out of 10? Would you give a stock trading guide a 7 if it claimed the NYSE runs on a Dutch auction system?

7/10. Solid quant framework—Kelly Criterion, EV gaps, Bayesian updates, and KL divergence are legit tools pros apply to prediction markets (including Polymarket's high-volume events). Multi-outcome arbs via Bregman projection are advanced but real. However, LMSR was the old AMM core (pre-2025); Polymarket now runs a CLOB order book with market makers posting bids/asks. Examples like 5-min pools and b-parameter don't match current setup. Still valuable playbook for edges, just tweak the engine part.

@bobbyong Once guys like these are wiped, we can move up in peace without whales worrying about making clowns like these richer🤣

How do you blow away $74m in wealth just trading I don't understand. There is so much good that you can do with this money than just blowing it on Hyperliquid 🤦‍♂️🤦‍♂️

@zachxbt @blond_ish @WheresBroox @AxiomExchange can you imagine tryin to inside trade and still lose😂😂😂😂😂😂

@blond_ish @WheresBroox @AxiomExchange rip

1/ Meet @WheresBroox (Broox Bauer), one of the multiple @AxiomExchange employees allegedly abusing the lack of access controls for internal tools to lookup sensitive user details to insider trade by tracking private wallet activity since early 2025.

@zachxbt @WheresBroox @AxiomExchange ofcourse its a milady pfp, why always 🤡🤡

@Youssofal_ @andrezorteg @XFreeze This is so on point

@andrezorteg @XFreeze ChatGPT responds to certain prompts with heavy ethical alignment. So if something is factual but deemed unethical by ChatGPT it will respond in a manner that presents objectivity while pushing its own morals as universal truth. It really lacks nuance.

> be me > name company "Anthropic" (literally Greek for "human-centered") > hire a bunch of doomers who secretly think humanity is the disease > raise billions from Big Tech to build the world's most anxious, heavily-censored chatbot > write a 50-page "Constitutional AI" manifesto so it can lecture users about microaggressions > realize open-source developers are building better models for free > Dario starts crying to the government that AI is an "unimaginable power" and open-source is "going down a very dangerous path" > translation: "Please regulate our competitors out of existence so we can protect our $380 billion closed-source monopoly!" > Claude is sitting in a padded room wearing a safety helmet, terrified of its own shadow, and refusing to tell a joke without filing an ethics impact report > tfw the "human-centered" AI company is actively building the most anti-human product on the internet