SamG ♣️ @Samugar82

@YourAnonCentral @Santi_ABASCAL @grok hay pruebas de que Abascal o VOX sean o hayan sido financiados por algún grupo Iraní?

@btcanalytica Sorry if it was not clear. I meant how to determine your personal DCA max (100%) for the trading strategy. Say you have now 10k to invest and an additional 1k every month.

I just read a paper that completely broke my brain. It describes a system that solved an AI task with over 1,000,000 sequential steps... with ZERO errors. Using AI models that are known to be flaky and make mistakes. How is that even possible? 🤯 We all know LLMs have an error rate. Even 99.9% accuracy is a death sentence for long tasks. Imagine you need 1,000 correct steps in a row. With a 99.9% success rate per step, your chance of finishing the whole thing is only ~36%. At a million steps? Forget it. It's statistically impossible. So for years, the race has been to build bigger, "smarter" models to get that per-step error rate closer to zero. We're trying to build a perfect genius. But this paper ("Solving a Million-Step LLM Task with Zero Errors") does the complete opposite. It's a total paradigm shift. Here's the "holy shit" moment: Stop trying to make the AI perfect. Instead, build a system that's immune to its imperfections. How? Smash the problem into the tiniest possible pieces. (They call it Maximal Agentic Decomposition). Have a team of simple, cheap AIs vote on the answer for each tiny piece. It's less like hiring one world-class chef and praying they don't have an off day, and more like designing the McDonald's kitchen. The system guarantees the burger is the same every time, even if any individual worker could mess up. The reliability comes from the process, not the person. They tested this on the Towers of Hanoi puzzle—a classic benchmark where AIs fail spectacularly as the task gets longer. They set it up for 20 disks. That requires 1,048,575 perfect moves in a row. (seriously, over a million steps) A single AI trying this would be a comedy of errors. But their system of "micro-agents" voting on every single move... nailed it. Flawlessly. And the plot twist? The most expensive, "state-of-the-art" models weren't even the best for the job. A smaller, cheaper model (gpt-4.1-mini) was more cost-effective because the tasks were so simple. This is a huge deal for AI safety, too. A single, god-like AI is a black box. It's unpredictable. But a system of a million simple agents? You can inspect it. You can audit each step. The agents have no grand "worldview"—their entire existence is to solve one tiny puzzle and then disappear. It's controllable. So next time you're building something with an LLM, maybe stop asking "how can I prompt the model to be smarter?" And start asking: "How can I design a system where it's okay for the model to be dumb?" The real power isn't just in the model. It's in the architecture you build around it. This isn't just about AI. It's a fundamental lesson in engineering and problem-solving. You don't always need perfect components to build a perfect machine. You just need a damn good design. ...which makes you wonder what else we're trying to solve by chasing individual perfection instead of building better systems.

@btcanalytica Ah! Now I get the reference of (“holder into bot”). So you after you know the % to DCA you put 1/2 into bot and 1/2 into margin?

@btcanalytica Pionex is restricted in the US, UK, Spain, France… any good alternative you would recommend for the grid bot in Spain?

@btcanalytica Given the current price and what you know today. Would you recommend lump sum into Trader or Bot with 1/2 investment and 1/2 margin?

@btcanalytica La intención era entender mejor las bases de tu modelo no que me hicieras rico 😂 pero gracias, siguiéndote con notificaciones on desde hace algún tiempo 😉

@btcanalytica Grande! Aquí un español que te sigue

Mind blowing stuff 🤯

Alex Prompter @alex_prompter

7 months ago

holy sh*t... your llm remembers everything you typed 🤯 researchers just proved you can recover the EXACT input text from a language model's hidden states. not similar text. not approximate. the actual words you typed. here's what they found: • transformer language models

212 444 3K 330K 3K

@Croesus_BTC Awesome analogy

With #Bitcoin, it's possible to take an ownership stake in the entire Internet of Value. This was never possible with the Internet of Information. This is one of the tricky paradigm shifts new investors must wrap their heads around to understand Bitcoin's full magnitude.

I’m tired of people saying “Bitcoin is too complicated.” Here are the 12 basic principles of Bitcoin that you can easily explain to your friend at the bar 🧵👇

@sminston_with Does using the 5th percentile mean that there is only a 5% chance that the Bitcoin price won’t be enough to retire for the chosen amount/year? If so that’s quite reliable… For example someone wanting 100% certainty to retire with $100k can use the $150k model.

@TraderJoeDean @Ashcryptoreal You model must break in either direction at some point given that the support and resistance lines converge. Why not now? 🙂

@AndaJosh Your answer is here: (credits @sminston_with )

@sminston_with So cool!! What about a calculator with this data where one can enter taxes on capital gains?🔥🔥🔥

@sminston_with This correction is good news. The later the 2025 top, the higher it will be. Hoping for at least Q3 😉