MP

re: "Project Higherliquid" - $HIGH gm fellow $HYPE maximalists currently, I am betting my career on building a first-of-its-kind Equity Perps & Equity Options infrastructure on the Hyperliquid ecosystem, with OG status (100% revshare & five 80% revshare invite links per OG user) for our first 1000 users, in true hyperliquid fashion codename: "Higherliquid" project higherliquid will be exiting Stealth Mode in coming Tuesday, April 14 early access invites will start being sent out at 9:00AM PST tomorrow - dms are open. Hyperliquid.

some insights from the normie 1x engineers sometimes you wonder what its like on the other side of the forest

Someone found a way to wipe out Polymarket market makers with 10 cents per attack Polymarket matches trades on an off chain order book, then settles them on chain seconds later The gap between those two systems is the exploit A trader places a trade against a market maker bot and the API confirms the fill instantly, but before anything hits the blockchain he cancels the trade on chain The bot already hedged a position that never existed and now the attacker takes the free money 10 cents in gas per attack, 50 seconds per cycle, one wallet pulled $16,427 in a single day It's called Ghost Fills and Polymarket still hasn't fixed it, so a dev built an open source tool called Nonce Guard to defend against it himself

"You don’t get rich by diversifying into 50 mediocre assets. You get rich by finding 2 or 3 asymmetric home runs." — Stanley Druckenmiller

@unipegv4 @Uniswap "not an NFT" > NFT

Unipeg 🦄 $uPEG // unipeg.art A new kind of on-chain object. Not an NFT. Not a token in the conventional sense. Built on @Uniswap v4 hooks. The name will make sense by the end. 0x44b28991B167582F18BA0259e0173176ca125505 🧵//🦄

3/ Do you really want something? Then really work. Half-assing doesn't get you anywhere. Don't look for "system hacks," or whatever, just do it. You first need the baseline mentality of going all in, or nothing else matters

@ihtesham2005 it is genuinely beautiful. what a good life

An MIT professor taught the same math course for 62 years, and the day he retired, students from every country on earth showed up online to watch him give his final lecture. I opened the playlist at 2am and ended up watching three of them back to back. His name is Gilbert Strang. The course is MIT 18.06 Linear Algebra. Every machine learning engineer, every data scientist, every quant, every self-taught programmer who actually understands how AI works learned the math from this one man. Most of them never set foot on MIT's campus. They just opened a free playlist on YouTube and let him teach. Here's the story almost nobody tells you. Strang joined the MIT math faculty in 1962. He retired in 2023. That is 61 years of standing at the same chalkboard teaching the same subject to 18-year-olds. The interesting part is what he did when MIT launched OpenCourseWare in 2002. Most professors were skeptical. They worried that putting their lectures online would make their classrooms irrelevant. Strang did not hesitate. He said his life's mission was to open mathematics to students everywhere. He filmed every lecture and gave it away. The decision quietly changed how the world learns math. For decades linear algebra was taught the wrong way. Professors started with abstract vector spaces and proofs about field axioms. Students drowned in the abstraction. Most never recovered. They walked out believing they were bad at math when they had simply been taught in an order that nobody's brain is built to absorb. Strang inverted the entire curriculum. He started with matrix multiplication. Something you can write down on paper. Something you can compute by hand. Something you can see. Then he showed his students that everything else in linear algebra eigenvectors, singular value decomposition, orthogonality, the four fundamental subspaces was just a different lens for understanding what the matrix was actually doing under the hood. His rule was strict. If a student could not explain a concept using a concrete 3 by 3 example, that student did not actually understand the concept yet. The abstraction was supposed to come last, not first. The intuition was the foundation. The proofs were just confirmation that the intuition was correct. The second thing Strang changed was the classroom itself. He said please and thank you to his students. Every single lecture. He paused mid-derivation to ask "am I OK?" to check if anyone was lost. He never used the word "obviously" or "trivially" because he knew exactly what those words do to a student who is one step behind. He treated 19-year-olds learning math for the first time the way he treated his own colleagues. With patience. With respect. With the assumption that they belonged in the room. For 62 years. The result is something that has never happened in the history of education. A single math professor became the default teacher of his subject for the entire planet. Universities in India, China, Brazil, Nigeria, every country with a computer science department, started telling their own students to just watch Strang's lectures. The University of Illinois revised its linear algebra course to do almost no in-person lecturing. The reason was honest. The professor said they could not compete with the videos. His final lecture was in May 2023. The auditorium was packed with students who had never met him before. He walked to the chalkboard, taught for an hour, and at the end the entire room stood and applauded. He looked confused for a moment, like he genuinely did not understand why they were cheering. Then he smiled and waved them off and walked out. His written comment under the YouTube video of that final lecture was four sentences long. He said teaching had been a wonderful life. He said he was grateful to everyone who saw the importance of linear algebra. He said the movement of teaching it well would continue because it was right. That was it. No book promotion. No farewell speech. No legacy management. The man whose teaching is the foundation of modern AI just thanked the audience and went home. 20 million views. Zero ego. The entire engine of the AI revolution sits on top of math that millions of people learned for free from one quiet professor in Cambridge. The course is still on MIT OpenCourseWare. Every lecture, every problem set, every exam, every solution. Free. The most important math course of the 21st century is sitting one click away from you. Most people will never open it.

The only other times when high beta momentum had a 30%+ gain over 18-days into a 52-week high was Nov. ‘99 Look at what stonks did over the next 6 month…

@ConsciousRide nobody touches pytorch anymore now lol

As an AI engineer. Please learn: - Python proficiency with NumPy, Pandas & PyTorch/TensorFlow - Data preprocessing, feature engineering & EDA - Model evaluation, cross-validation & bias-variance tradeoff - Transformers, attention mechanisms & LLMs - Prompt engineering, RAG & fine-tuning techniques - Vector databases & embeddings (Pinecone, FAISS, Chroma) - MLOps – experiment tracking, model serving, monitoring (MLflow, BentoML, LangChain) - Evaluation metrics, hallucination detection & safety/alignment All very important topics.

> be chinese ai labs > while claude and openai are in cold war > kimi dropped k2.6 using deepseek's v3 architecture > the same week deepseek drops v4 using kimi's muon optimizer > 1.6 trillion parameters & 1M context > both match or beat closed models on benchmarks while being 8x cheaper > both build on each other's breakthroughs > keep shipping frontier LLMs with far less or nerfed NVIDA GPUs > and keep them 100% open sourced the real battle is not between models, it's open source vs closed.

@deepseek_ai wow

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models. 🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice. Try it now at chat.deepseek.com via Expert Mode / Instant Mode. API is updated & available today! 📄 Tech Report: huggingface.co/deepseek-ai/De… 🤗 Open Weights: huggingface.co/collections/de… 1/n

@0x_Negative @helloiamleonie hmm

@helloiamleonie For enterprise, AWS AgentCore + AWS Strand agents. For quick agentic setups, Mastra AI. For simple direct LLM workflows and chats, Vercel AI SDK. Still early, but I am beginning to really like MS Agent Framework - the DX and tooling is very nice.

If you’re building AI agents, what’s your current stack?

The problem is that a stop loss treats risk as a property of price when risk is actually a property of exposure over time. So a stop loss is answering a question the market isn’t asking. It’s a number you invented that feels like it constrains your loss, but what it mainly does is add randomness. Stop losses are conceptually wrong. Not 100% useless, but wrong. You better look at how volatile what you’re buying is and size the position so that it is acceptable.

People love putting “AI/ML” in their bios but ask them about eigenvalues or eigenvectors and it’s silence.

@JeremyCMorgan i mean that kinda goes without saying lol

Red Hat's "harness engineering" paper argues the environment an AI works in matters as much as the weights: integrating telemetry, repos, and testing constraints into a single deterministic orchestrator measurably moves code generation reliability by 5%+. You cannot prompt-engineer your way out of bad infrastructure. github.com/ai-boost/aweso…

nothing but gratitude for these two cycles. onwards and upwards. MoneyPrinter0x

fullport exited sol right at the entire sol cycle top (jan 2025, sol 255$) x.com/moneyprinter0x… fullport bidded gold right before biggest gold run in 40 years (feb 2025, xau 2.7k) x.com/moneyprinter0x… heavy bidded aave, eth right before 2025 runup (apr 2025, eth 1.8k)

as predicted. $INTC

@0xRiver8 game recognizes game this is going to be our cycle broski

One of the very few people who was hard shilling intel from the lows with hard conviction 🐐

Underappreciated that a generation speed ran every finance game and can now pattern match against all the tradfi shenanigans

holy shit thats pretty extreme lol