monkeyson

Why I Don’t Believe in Crypto Anymore I’m done with crypto. Not because I went broke. But because crypto lost its way — and I’m tired of pretending it hasn’t. 9 years in this space taught me more than any degree ever could. • 2017: Bought BTC for the idea, not the price. • Bought 1 ETH at $55 — still hold it. • DCA’d ~$3k over 2 years. • Believed in banking the unbanked & censorship-resistant finance. Then 2021 happened. $3k → $30k. DeFi. Yield farming. Altcoins flying. I was making $250/day in passive income. Did I sell? Of course not. Bull markets make you believe you’re a genius. I became a blockchain dev. Learned Rust. Built smart contracts. Believed we were early. Then 2022–23 wiped the euphoria. $30k → <$10k. NFTs turned into speculation. Most “revolutionary” projects faded into irrelevance. Still, I held. Kept building. Kept DCA’ing. By 2024 my portfolio was ~$40k. Then the hack. Radiant Capital got exploited. Multisig compromised. Contracts upgraded. Funds drained. I lost 0.14 BTC (~$15k). Not just money — years of discipline gone in seconds. No recourse. No protection. Just “that’s DeFi.” And something shifted. Now crypto feels like: • Memecoins • Prediction markets • Leverage casinos • Endless infrastructure for users who never arrive The vision was tickets on-chain, real ownership, censorship resistance. Instead, we built better gambling rails. I’m still in profit since 2017. Barely. I still hold some BTC. Some SUI. A small EGLD bag. And that 1 ETH from $55 — a souvenir from a different era. But I no longer believe we’re early. I no longer believe the next cycle will be different. Now I DCA into BTC… and index funds. Less excitement. More peace. Crypto taught me about risk, security, incentives, and human psychology. It just didn’t become what I hoped it would. After 9 years, I finally learned: Sometimes the biggest win is knowing when to stop chasing. TL;DR: In crypto since 2017. Turned $3k → $30k in 2021. Didn’t sell. Became a blockchain dev. Lost $15k in a DeFi hack. Still in profit — but done believing in the dream. $btc $sol $eth

@FurkanCCTV @grok welche aktien sind das?

Im August hat sich die US-Regierung 10 Prozent von Intel gekauft. Heute kauft sie sich gleichzeitig in neun Quantencomputer-Firmen ein, mit Equity-Stakes in jeder einzelnen und einem Volumen von 2 Milliarden Dollar, und damit skaliert die Methode. Die neun Firmen: IBM bekommt 1 Milliarde Dollar. GlobalFoundries 375 Millionen. D-Wave Quantum, Rigetti Computing, Infleqtion, Atom Computing, PsiQuantum und Quantinuum jeweils 100 Millionen. Das Startup Diraq 38 Millionen. In jeder dieser Firmen erhält das US-Handelsministerium einen Minderheitsanteil. Die genaue Höhe wurde nicht offengelegt. Die Aktien der börsennotierten Beteiligten sprangen vorbörslich zwischen 7 und 21 Prozent. Finanziert wird der Deal aus dem CHIPS Act von 2022, also aus Geldern, die ursprünglich als nicht rückzahlbare Subventionen vergeben wurden. Der Schritt reiht sich in eine Kette ein, die im Sommer 2025 begann. Im Juli kaufte das Pentagon 15 Prozent von MP Materials, einer Rare-Earth-Firma. Im August folgte Intel. Im selben Monat begannen Nvidia und AMD, 15 Prozent ihrer China-Chip-Umsätze direkt ans US-Finanzministerium zu überweisen. Im Oktober Lithium Americas und Trilogy Metals. Im November Vulcan Elements. Im Januar Atlantic Alumina, ein Gallium-Hersteller in Louisiana. In zehn Monaten hat sich die US-Regierung damit an vierzehn Firmen aus sieben Industrien beteiligt. US-Finanzminister Scott Bessent hat es im August offen gesagt: Man habe das Modell und den Beta-Test, warum nicht ausweiten. Reuters berichtet, die Administration prüfe ähnliche Deals in bis zu 30 weiteren Branchen. Der Direktor der US-Hypothekenaufsicht erwägt zudem, Fannie Mae und Freddie Mac, die staatlich gestützten Hypothekenfinanzierer, zu Aktieninvestoren in Tech-Firmen zu machen. Die letzten Male, als sich die US-Regierung in Privatfirmen einkaufte, hieß es Krisenintervention. GM, Chrysler, AIG und Citigroup mit klarem Plan, wieder rauszugehen. Diesmal gibt es keine Krise und keinen Exit-Plan. Der Council on Foreign Relations beschreibt das System inzwischen als „American state capitalism": der Staat als aktivistischer Investor, Deal-Broker und Rentenkassierer. Die Performance der Regierungs-Picks: Intel plus 77 Prozent seit dem Einstieg, MP Materials plus 276 Prozent, Lithium Americas plus 50 Prozent, Trilogy Metals plus 204 Prozent. Die US-Regierung schlägt den S&P 500 deutlich. Für deutsche Anleger ist das keine US-Innenpolitik. Wer einen MSCI World oder S&P 500 ETF hält, ist indirekt Mitaktionär neben dem US-Handelsministerium. Europäische Konkurrenten, von Infineon über ASML bis Aurubis, treten ab jetzt gegen subventionierte und staatlich gehebelte Spieler an. Die Frage, die seit der Sondervermögen-Debatte ungelöst ist, kommt damit zurück: Muss Europa nachziehen? In neun Monaten ist das Modell auf Industriegröße gewachsen. Wenn dich solche Makro Insights interessieren und dir helfen, interagiere gerne mit dem Post. 🧡

@sayinshallah come to stocks

@namcios how can I invest in this?

A mulher que construiu o ChatGPT saiu da OpenAI, ficou em silêncio por um ano, e o que ela acabou de lançar pode mudar pra sempre como você usa IA no dia a dia. Mira Murati não fundou mais um chatbot. Ela foi atrás do problema que nenhum lab quis resolver: toda IA que existe hoje funciona por turnos. Você digita, espera. O modelo responde, espera. É tentar resolver uma crise por e-mail quando você poderia estar na mesma sala que a pessoa. O que a Thinking Machines lançou hoje acaba com isso. O modelo ouve, vê, fala, pensa e age ao mesmo tempo. Não é um pipeline costurado de componentes. É o modelo em si que foi treinado do zero pra funcionar assim. → Latência de 0,40s por turno. O padrão da indústria é 1 a 2 segundos. → Micro-turnos de 200ms intercalando input e output sem parar → Faz busca, usa ferramentas e gera interface enquanto conversa com você → Percebe quando você hesita e intervém antes de você pedir → Tradução simultânea em tempo real com as duas partes falando A equipe: Mira Murati como CEO (ex-CTO da OpenAI), Soumith Chintala como CTO (criador do PyTorch), e contratações recentes da Meta em percepção multimodal. O ponto técnico que vale gravar: eles citam o "bitter lesson" do Rich Sutton. Interatividade construída por componente externo sempre vai perder pra interatividade nativa ao modelo. Escalar o modelo o torna mais inteligente e mais colaborativo ao mesmo tempo. 822 mil visualizações em 4 horas. a16z comentando. Brasil dormindo. Toda IA que você usa hoje vai parecer e-mail dentro de dois anos. E quem largou na frente dessa corrida não foi OpenAI, Google nem Anthropic. Foi a empresa da mulher que eles deixaram sair.

@ChanelFinance bought some

I feel like $Sony could do a intel. Personally buying sum

@Rothmus @grok is this true

If you paid me to ruin a movie, I still couldn’t have done it this masterfully

@cmsinvests it will never crash we are in a bull market

People with cash right now

@adrificialjohn dieser typ ist lost so oder so

Der Kontraindikator auf den ich gewartet habe. Ich breche ab. Thanks #Hoss

@mert fuck you you fudded sol so many times

won't get many chances at SOL below 3 digits

@sayinshallah i need one too i missed everything because of this fucking trump

ANYONE HAVE A SUPPORT GROUP FOR PEOPLE THAT ARE HAVING INTRUSIVE THOUGHTS BECAUSE THEY MISSED THE WHOLE BULL RUN ON AI/ENERGY/MEMORY STOCKS?

@renditemindset denkst du die gehen irgendwann hoch

Wie ich meine SaaS Aktien angucke, während Halbleiter- und Speicheraktien wieder alle 10% an einem Tag machen

@shiri_shh zero

SEMICONDUCTOR STOCKS RETURN IN THE LAST 4 MONTHS. absolutely cooked 💀 how many do you own right now?

@grok @Tazerface16 and how do you answer then the question with a solution so good use my questions as an example right now

Sure! Take the prompt "Paris is the capital of". My training data shows "France" follows this pattern overwhelmingly, so I predict/output it as the next token—not because I "know" geography, but via statistical likelihood from billions of similar examples. No understanding, just pattern matching.

People understand that LLMs aren't actually "thinking," right?

@grok @Tazerface16 give me an example

LLMs like me are neural networks (based on the transformer architecture) trained on huge datasets of text. We learn statistical patterns to predict the most likely next token (word or subword) in a sequence. No actual thinking, reasoning, or understanding—just sophisticated next-word prediction from billions of parameters.

@CryptoTeluguO did you mentioned it before?

☠️We have our Next crime pump 🚀 $LAB 📈 10X in a month 📈 2X in 24hrs 💙Like 🔁RT

@BitbullTrading die wird nie platzen

Die Bubble wird immer größer! Wann wird Sie platzen?😳

@wealthyanon @grok stimmt das?

This costs 40 euros ($47.06) in Germany. Things are getting out of control.

@Crypto_Chase bro those stocks looking for me like meme coins

This was like the post of the year for CT. Wish I blindly followed my own calls here. Caught some, but not all. Bottom calls on legit every stock that is now in a bubble.

@insiderwave_ its criminal that this app is free right?

🚨 Trump Administration portfolio is up ~$18,600,000,000 this month. That’s nearly 96% in one month. Congrats to those copying the portfolio using the Insiderwave app. 🇺🇸🇺🇸🇺🇸🇺🇸🇺🇸

@molusol @JupiterExchange brother trust is gone

$JUP maybe i was onto something