DC BitMax (@DCBitMax) - Twitterプロフィール

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This is the most rigorous Bitcoin paper I've read. I've been studying — and testing — it for 20 days. scientificbitcoininstitute.org/research/publi… Dr. Santostasi and Dr. Perrenod gave us the ruler — and the imagination to see the oscillator. Together: the most falsifiable framework in crypto economics. The Power Law isn't just a model — it's the most precise ruler we have for measuring where Bitcoin stands. Most models describe the past. The Power Law keeps passing tests it was never designed for. "Isn't β=5.69 just curve-fitting?" Fair question. So I ran a test the paper didn't. ━━━━━━━━━━━━━━━━━━━━━━ Materials & Methods ━━━━━━━━━━━━━━━━━━━━━━ Data: Daily closing price and non-zero balance address count (BitcoinMagazinePro, 2010-08-17 to 2026-06-04, n=5,771). Model: log₁₀P(t) = log₁₀A + β·log₁₀(t) where t = days since Genesis Block (2009-01-03). Out-of-sample design: The power law was fitted exclusively on data up to the freeze date, with zero observations from the test period used in estimation. Two freeze points were tested: ① Freeze at 2016-07-08 (2nd halving) Training: n=2,153 | Test: n=3,617 (10 years) ② Freeze at 2020-05-10 (3rd halving) Training: n=3,555 | Test: n=2,215 (6 years) Residuals computed as: ε = log₁₀(P_observed / P_predicted) normalized by in-sample σ. Mean residual and area integrals (trapezoidal rule) applied to test period only. The out-of-sample test was my idea. Computation and analysis executed with Claude Opus 4.8 (Anthropic). ━━━━━━━━━━━━━━━━━━━━━━ Froze the power law using data up to 2016 only (β=5.717). Then measured the following 10 years it had never seen. Result: mean residual −0.05σ. Effectively zero. Frozen at 2020 instead → next 6 years, −0.13σ. Same story. The line drawn in 2016 ran straight through the next decade. That's not fitting. That's forecasting. The Power Law: powerful because it can be broken — and hasn't been. Knowing where we are won't tell us when things will happen — but it tells us exactly what to do now. Buy Bitcoin Now. @Giovann35084111 @moneyordebt @ScientificBTC @saylor @natbrunell #Bitcoin #PowerLaw

Giovanni's BTC_POWER_LAW@Giovann35084111

If you didn't read it yet. 10 k downloads. zenodo.org/records/193870…

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DC BitMax@DCBitMax·6m

@gvx1q5 @tmxortkcmghemf 오르고 내리는거 아임미까 행님 한잔해

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비트맥시갤러리@gvx1q5·12h

@tmxortkcmghemf 오늘의 비트코인 네트워크와 수년전 네트워크는 전혀 변하지않았다, 가격만 변했을뿐

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스택사츠호들@tmxortkcmghemf·13h

다들 가격만 보고 약세장이라고 말하지만, 유동성은 사라진 게 아니라 다른 곳으로 이동했을 뿐이다. 비트코인의 펀더멘털은 그대로고, 채굴기는 계속 돌아가고, 블록은 계속 생성된다. 시장이 다시 현실을 깨닫는 순간, 지금 가격은 “왜 안 샀지?” 구간으로 보일 가능성이 높다. 비트코인은 할인 중이다. 세일은 영원하지 않다.

The ₿itcoin Therapist@TheBTCTherapist

Market liquidity was siphoned from Bitcoin, gold, crypto and tech and its being injected directly into SpaceX. Bitcoin is on sale and it’s not going to last.

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DC BitMax@DCBitMax·40m

What if people who don't use much AI could lend or share their unused tokens with others who need more? Like a token-sharing economy among light users — a sort of AI credit union. 😅

Marty Kausas@marty_kausas

Our Anthropic bill is about to jump from $400K → $1.4M/yr. Not because usage exploded, but because we're about to cross 150 seats. Past 150 seats you're forced into Enterprise tier. Seats stop including any usage, every token bills at standard API rates. At our current run rate that's 3.5x overnight. Unfiltered thoughts on AI spend: 1. We should spend tokens to grow as aggressively as possible. But most people (me included) aren't conscious of what they're spending. 2. Visibility comes first. People see their personal number and they're shocked. I accidentally spent $4,000 in 3 days in Claude Code. 3. For engineering the spend is clearly worth it. Pay for the best model, it saves more than it costs. 4. For a lot of other roles it's questionable. Apps nobody uses, skills someone already built. No ROI. 5. Spend limits are coming. We already require approval for more tokens on our support team. The era of token-maxxing is coming to an end.

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Marty Kausas@marty_kausas·1d

Our Anthropic bill is about to jump from $400K → $1.4M/yr. Not because usage exploded, but because we're about to cross 150 seats. Past 150 seats you're forced into Enterprise tier. Seats stop including any usage, every token bills at standard API rates. At our current run rate that's 3.5x overnight. Unfiltered thoughts on AI spend: 1. We should spend tokens to grow as aggressively as possible. But most people (me included) aren't conscious of what they're spending. 2. Visibility comes first. People see their personal number and they're shocked. I accidentally spent $4,000 in 3 days in Claude Code. 3. For engineering the spend is clearly worth it. Pay for the best model, it saves more than it costs. 4. For a lot of other roles it's questionable. Apps nobody uses, skills someone already built. No ROI. 5. Spend limits are coming. We already require approval for more tokens on our support team. The era of token-maxxing is coming to an end.

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meltedblocks@meltedblocks·22h

Anthropic is pushing me to be Robin Hood. Break the rules and bypass their terms for good cause. I help secure a crypto protocol with $120M+ in TVL. We are not large enough to be on every AI security whitelist, but we are definitely large enough to care if models like Mythos make vulnerability discovery faster and cheaper. And this is where it gets strange. The strongest cyber capabilities are gated, filtered, or partially routed away. I understand why. Nobody wants to hand attackers better exploit tooling. But attackers will obviously try to bypass those limits. So what should defenders do? Follow the rules and accept weaker tooling? Or test the real limits of the system, because that is exactly what attackers will do anyway? Or do you believe in their moral compass? That feels backwards. Defenders should not have to fight the attacker, the model restrictions, and the ToS at the same time. And there is another problem: cost. For an attacker, one good run can be enough. One bug. One exploit path. One protocol with money sitting in contracts. For a protocol, defense is not one run. It is every release, every dependency update, every new integration, every small change touching user funds. So if the best AI security tooling becomes gated or extremely expensive, the economics get very weird. Attackers only need to be right once. Defenders need to be right every day. In normal software, that asymmetry is already uncomfortable. In crypto, it is brutal. Because here, a bug is not just a bug. It is live money and instant loss.

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Mo Shaikh 🇺🇸@Moshaikh·1d

Citadel, is one of the most significant hedge funds, and they just dropped tokenomics … And it’s not what you would have expected

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VraserX e/acc@VraserX·9h

I’m honestly angry watching Anthropic try to position itself as the gatekeeper of our future. The playbook is obvious: • push AI rules only giant labs can survive • call open access irresponsible • lock the strongest models behind “trusted access” • sell the real power to enterprise and government • make society dependent on their approved AI layer If AI becomes the operating system for business, science, law, logistics and government, then Anthropic would gain insane leverage over what people can build, research and automate. I don’t want humanity’s future filtered through one company’s permission slip. Anthropic as gatekeepers of our future is a nightmare scenario.

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Norveçli@norveclifinance·7h

The AI bubble has burst. Now OpenAI and Anthropic are preparing for a user war and price war. Chinese AI models are dramatically cheaper, forcing U.S. AI companies to cut prices and sacrifice margins to stay competitive. The higher the competition gets, the harder it becomes to justify hundreds of billions in AI spending and the valuations built on those expectations. Everyone talked about growth at the top. Now they’re talking about price cuts. $MSFT $GOOGL $AMZN $META $NVDA $AMD $MU $TSM $ASML $ARM $AVGO #AI #ArtificialIntelligence #TechStocks #StockMarket #Investing

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Perry E. Metzger@perrymetzger·18h

I have seen some people claim, completely incorrectly, that Anthropic’s new “silent sabotage” policy is just trying to stop distillation attacks that steal weights from their models. This paragraph makes it extremely clear that that is not the case. Anthropic is generally blocking attempts to advance the state of the art in AI research, even for techniques they themselves make no use of. For example, Anthropic is targeting research on distributed training, which is to say, training runs done on large pools of computers loosely attached over the Internet, but it does not do any distributed training, as it has no need for it. Distributed training is, however, a technique that open source AI researchers without billions of dollars at their disposal have been leaning on to allow them to leverage large amounts of crowdsourced computation. Why would Anthropic do this? Likely because they fear that their model might help people write code to build open source AI systems trained without expensive hardware, and because to the EA cult, distributed open source AI training systems are the worst possible thing someone could build. It is perfectly within Anthropic’s right as a company to do stuff like this, but it is also within our right, as users of AI systems, to stop giving them money. It is perfectly within Anthropic right to lobby to try to gain a government monopoly on AI research and development, as they have for years now. It is perfectly within our rights, as citizens, to oppose repugnant attempts to grab power with all our strength.

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NIK@ns123abc·11h

🚨ANTHROPIC APOLOGIZES AFTER RESEARCHERS CALLED INVISIBLE GUARDRAILS “SECRET SABOTAGE” >claude fable 5 had INVISIBLE guardrails >secretly degrading users’ AI research >bro what >researchers found out and went nuclear >called it “secret sabotage” Anthropic: “We made the wrong tradeoff and we apologize” New policy: If Claude suspects you’re building frontier AI it will ‘alert’ the user that it’s refused the request or routed it to Opus

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DC BitMax@DCBitMax·52m

놀랍네 놀라와

NIK@ns123abc

🚨ANTHROPIC APOLOGIZES AFTER RESEARCHERS CALLED INVISIBLE GUARDRAILS “SECRET SABOTAGE” >claude fable 5 had INVISIBLE guardrails >secretly degrading users’ AI research >bro what >researchers found out and went nuclear >called it “secret sabotage” Anthropic: “We made the wrong tradeoff and we apologize” New policy: If Claude suspects you’re building frontier AI it will ‘alert’ the user that it’s refused the request or routed it to Opus

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DC BitMax@DCBitMax·55m

@gvx1q5 @Notesfor_X ㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋ

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비트맥시갤러리@gvx1q5·12h

@Notesfor_X 공부를 해서 성과를 내본적이 있나요?? 👀🤡👀🤡👀🤡👀 공부도 못하고 맨날 시험에서 떨어지는 친구가 공부해!! 책좀읽어!! 라고하면 부처도 긁힙니다 👀🤡👀🤡👀🤡👀 전인구는 말이라도 이쁘게합니다 👀🤡👀🤡👀🤡👀

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하워드🍟⚡️@Notesfor_X·16h

투자든 저축이든 재테크든 자기의 소중한 돈이 들어간건데 왜 공부를 하라고 하면 발작하는걸까요? 공부를 해본 적이 없어서....? 머리가 나빠서...?

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SemiAnalysis@SemiAnalysis_·1d

BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won't notice. We are already seeing Anthropic's latest model's moderation filters our GPU inference research and programming 😭

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IVCrushLeague@IVCrushLeague·1d

@SemiAnalysis_ Getting shadow banned by your own LLM

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Jake@JakeKAllDay·1d

@SemiAnalysis_ It won’t just not help you, it will lie and purposefully give you bad info. The “ethical AI” company with the most brazenly unethical LLM, on purpose. x.com/JakeKAllDay/st…

Jake@JakeKAllDay

I am all for safety refusals, and TOS refusals are fine, but giving intentionally wrong/bad answers on perfectly legal things that "violate our TOS" and charging people for said token/usage is pretty brazenly fraudulent.

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Prof@TheProfInvestor·16h

My First purchase of SpaceX will be in 10 months. All IPOs trade in a similar trend. Shocking stats: - Most IPOs drop 50% after going live. Look at $CAVA $RDDT $ALAB $CRWV $CART $CBRS - Some drop further to 70-80%, look at $HOOD $PLTR - And some never recover: $MBLY $CRCL $KLAR

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moneyordebt ∞/21M@moneyordebt·2h

@david_eng_mba

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DC BitMax@DCBitMax·1h

x.com/i/article/2065…

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DC BitMax@DCBitMax·1h

그런데 저기에 나온 친구들은 대한민국의 BTS 입니다 BTS from South Korea.

Amarillo@anyelamarillo

Alguien descubrió una herramienta que puede hacer esto con cualquier video de YouTube: Eliminar el audio original, transcribir el audio, traducir a más de 100 idiomas, clonar la voz del hablante original, redoblar Se ejecuta localmente. Completamente gratis. En menos de 2 minutos. La herramienta se llama Voice-Pro, búscala en GitHub Para quienes hacen videos de traducción, aprenden idiomas, o quieren doblar contenido extranjero al chino, esto es básicamente un regalo caído del cielo. ¿Qué herramienta usas ahora para procesar el doblaje de videos?

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Amarillo@anyelamarillo·1d

Alguien descubrió una herramienta que puede hacer esto con cualquier video de YouTube: Eliminar el audio original, transcribir el audio, traducir a más de 100 idiomas, clonar la voz del hablante original, redoblar Se ejecuta localmente. Completamente gratis. En menos de 2 minutos. La herramienta se llama Voice-Pro, búscala en GitHub Para quienes hacen videos de traducción, aprenden idiomas, o quieren doblar contenido extranjero al chino, esto es básicamente un regalo caído del cielo. ¿Qué herramienta usas ahora para procesar el doblaje de videos?