与「arb」相关的搜索结果

加密货币害惨了我———— 因为之前 Arbitrum 搞的那次“奥德赛”空投活动，太过于坑。 导致你现在跟我讲《奥德赛》，我完全没法联想到： 诸如“人该如何回家”、“如何穿越低谷”，这种哲学史诗命题 我只能先入为主地回忆起： “黑奴”，“反撸”...😅

1994年朱镕基主导的分税制改革，被称为之后30年发展的地基。 话说回来，当前eth最需要这样的分税制改革，L2、L3们上缴的税太少了。以robinhood为例子，上线以来赚了450为美金，arb赚了45万美金，而eth得到的安全税收4.5万美金。

One BNB Chain metric that barely gets talked about: BNB Chain has the highest stablecoin market cap bridged into the chain ~$11.1B, according to DefiLlama. For comparison: Polygon: ~$2.37B Arbitrum: ~$1.06B Solana: ~$724M Capital goes where it can actually be used. BNB Chain is quietly becoming one of crypto’s biggest liquidity hubs.

A 19-year-old Japanese student built a trading bot with Claude Code in 2 days. Used his iPad as a second monitor. First night: $6,732 profit. Starting capital: $68. Total profit so far: $750,000. Here's how it works: The bot scans over 50 markets simultaneously. Syncs live BTC data from Binance every second. Spots price errors before humans even notice. The edge is pure speed + pattern recognition. While traders stare at charts trying to predict the next move, his bot is already executing on mispricing across dozens of markets. No guessing. No emotions. No hesitation. Just Claude Code logic finding gaps that close in seconds. He built the entire system in 48 hours: → Claude Code handles the trading logic → Binance API feeds real-time BTC data → iPad displays multi-market monitoring → Executes trades when arbitrage windows open The system runs 24/7. Every price dislocation = profit opportunity. Most people are still trading manually, refreshing charts, second-guessing entries. Meanwhile this 19-year-old engineering student turned $68 into $750K by letting Claude Code do what humans can't: process 50 markets instantly and execute without fear. Why are people still trading manually? 💡 I'm giving away the exact Claude Code setup for free. 24 hours only. To get it:- 1️⃣ Comment "Fable" 2️⃣ Like and Repost 3️⃣ Follow @sumitdoriya21 I'll DM you the complete setup.

A 19-year-old Japanese student built a trading bot with Claude Code in 2 days. Used his iPad as a second monitor. First night: $6,732 profit. Starting capital: $68. Total profit so far: $750,000. Here's how it works: The bot scans over 50 markets simultaneously. Syncs live BTC data from Binance every second. Spots price errors before humans even notice. The edge is pure speed + pattern recognition. While traders stare at charts trying to predict the next move, his bot is already executing on mispricing across dozens of markets. No guessing. No emotions. No hesitation. Just Claude Code logic finding gaps that close in seconds. He built the entire system in 48 hours: → Claude Code handles the trading logic → Binance API feeds real-time BTC data → iPad displays multi-market monitoring → Executes trades when arbitrage windows open The system runs 24/7. Every price dislocation = profit opportunity. Most people are still trading manually, refreshing charts, second-guessing entries. Meanwhile this 19-year-old engineering student turned $68 into $750K by letting Claude Code do what humans can't: process 50 markets instantly and execute without fear. Why are people still trading manually? 💡 I'm giving away the exact Claude Code setup for free. 24 hours only. To get it:- 1️⃣ Comment "Fable" 2️⃣ Like and Repost 3️⃣ Follow @sumitdoriya21 I'll DM you the complete setup.

A 19-year-old Japanese student built a trading bot with Claude Code in 2 days. Used his iPad as a second monitor. First night: $6,732 profit. Starting capital: $68. Total profit so far: $750,000. Here's how it works: The bot scans over 50 markets simultaneously. Syncs live BTC data from Binance every second. Spots price errors before humans even notice. The edge is pure speed + pattern recognition. While traders stare at charts trying to predict the next move, his bot is already executing on mispricing across dozens of markets. No guessing. No emotions. No hesitation. Just Claude Code logic finding gaps that close in seconds. He built the entire system in 48 hours: → Claude Code handles the trading logic → Binance API feeds real-time BTC data → iPad displays multi-market monitoring → Executes trades when arbitrage windows open The system runs 24/7. Every price dislocation = profit opportunity. Most people are still trading manually, refreshing charts, second-guessing entries. Meanwhile this 19-year-old engineering student turned $68 into $750K by letting Claude Code do what humans can't: process 50 markets instantly and execute without fear. Why are people still trading manually? 💡 I'm giving away the exact Claude Code setup for free. 24 hours only. To get it: 1️⃣ Comment "Fable" 2️⃣ Like and Repost 3️⃣ Follow @sumitdoriya21 I'll DM you the complete setup.

Claude's watermark probably doesn't work how you think. As the CTO of GPTZero, I'll explain how Anthropic, Google and OpenAI are building text watermarking in this brief explainer and whether it can be defeated. Almost all forms of watermarking that are fast and cheap enough for a frontier lab have the same formula, following the KGW method: In generation: 1. Let's say you've generated n tokens so far. Take those n tokens + a secret key to generate a random hash 2. Use that hash to randomly reweight the probabilities for the n+1 token, and then sample from that new distribution. In the simple case, you could split 50% of all English words into a green or red set based on your hash, and boost the probability of words in the green set. For watermark detection: 1. For each token, see if it was in the green or red set. 2. To do this, recreate the hash based on the secret key and the text preceding the current token. Then, recreate the green and red set of words. 3. Once you've checked all the words in the text, if the next token is selected disproportionally from the green set more than 50% of the time, you claim the text has the watermark. I can tell you want to ask the following: 1) Isn't it easy to mess up the hash if you paraphrase the text? The answer is mostly yes, however, you can use a statistical model to get your hash instead of a deterministic function (SIR, Adaptive Watermark). Since the entire watermark is probabilistic, this is fine. 2) Doesn't this make the text much worse? The answer is yes, it does - Yes, it does – but for most people, it's imperceptible (Google claims in human feedback study with 20,000 texts), since there are exponentially many ways to write the same paragraph. DiPmark does something more sophisticated to avoid shifting the text distribution on average. Of course, watermarks fail on short text or highly predictable texts like "2+2=4". 3) Shouldn't it be easy to figure out the green and red sets? The answer is no. You would need an exponentially large number of samples from the watermarker to reconstruct those sets exactly, but it's a risk if the detector is open to the wild (Watermark Stealing) Still, there are couple challenges that a frontier lab needs to overcome: 1. Their watermark needs to work token-by-token because they are streaming their text to users. Many watermark methods plan sentences or paragraphs at a time, or change the text after its entirely written, in order to make their watermark robust to paraphrasers, and a frontier lab cannot afford to do this yet (SemStamp, PostMark) 2. If the secret key leaks, the watermark is busted. To avoid a large blast damage from this, you need to have a couple secret keys in rotation. 3. There are some texts, like code, that cannot be arbitrarily changed, otherwise the code will break. In those cases, the watermark needs to selectively change words in parts of the text that can tolerate synonyms (i.e. like variable naming) - see SWEET, EWD, Invisible Entropy. 4. They will need to educate their users on how to deal with false positives and false negatives of a detector, which is a big challenge (one we put a lot of effort into) So, how do I see this playing out in the next 6 months? 1. If Anthropic releases the watermark detector publically, I think they defeat their own watermark. People find reliable watermark removal strategies by testing against Anthropic (AI detectors like GPTZero have an advantage here because they can train against these adversaries once they become popular). 2. If they keep the detector private to the government, like Google has done, it's "safer". However, there are some papers showing trained approaches that work robustly to zero-shot break watermarks without any data, simply because they try to write the text just like a human (Zhang et al. 2024, Watermarks in the Sand). Also, making your detector makes it battle-tested and stronger long-term (my experience). 3. In my testing, the watermarks don't survive intense paraphrasing (especially if you combine word choice and syntax attacks), or human text substitution (rewrite your AI text by plagiarizing human authors). The free paraphrasers I've tried have quickly bypassed Google Deepmind's SynthId for what it's worth. 4. All-in-all, frontier labs are likely okay with this because they expect most users to not attack the watermark, and also because they + European regulators likely don't care past a certain point - its good enough. 5. Overall, I think users of frontier LLMs will not really care about this, because 1) they don't realize watermarks are there, 2) EU will force everyone to conform, 3) this seems more like regulatory hoop-jumping than an earnest effort from frontier labs to expose LLM use Lastly, people's first concern shouldn't be watermarking, it should be AI detectors! If you're posting, "its not X, its Y!!", I don't think the watermark is going to make a difference :)

🔓 Top Token Unlocks This Week (Aug 10 - Aug 16) 1️⃣ Rain (RAIN) - $506.9M; 5.64% circ supply 2️⃣ Pump​.​fun (PUMP) - $20.0M; 1.80% circ supply 3️⃣ Pieverse (PIEVERSE) - $15.4M; 7.30% circ supply 4️⃣ Avalanche (AVAX) - $10.9M; 0.39% circ supply 5️⃣ Arbitrum (ARB) - $7.4M; 1.40% circ supply 6️⃣ Aptos (APT) - $6.9M; 1.37% circ supply 7️⃣ Sei (SEI) - $5.1M; 1.65% circ supply 8️⃣ Starknet (STRK) - $4.0M; 2.39% circ supply 9️⃣ Official Trump (TRUMP) - $1.4M; 0.36% circ supply 🔟 Worldcoin (WLD) - $1.1M; 0.09% circ supply

Un estudiante japonés de 19 años creó un bot de trading con Claude Code en solo 2 días. Usó su iPad como segunda pantalla. La primera noche ganó 6.732 dólares. Capital inicial: 68 dólares. Beneficio total hasta ahora: 750.000 dólares. Así es como funciona: El bot analiza más de 50 mercados al mismo tiempo. Sincroniza datos de BTC en tiempo real desde Binance cada segundo. Detecta errores de precio antes de que los humanos siquiera los noten. Su ventaja es simple: velocidad + reconocimiento de patrones. Mientras la mayoría de los traders observan gráficos intentando predecir el siguiente movimiento, su bot ya está aprovechando diferencias de precio en decenas de mercados. Sin adivinar. Sin emociones. Sin dudar. Solo la lógica de Claude Code encontrando oportunidades que desaparecen en cuestión de segundos. Construyó todo el sistema en apenas 48 horas: → Claude Code se encarga de la lógica de trading → La API de Binance proporciona datos de BTC en tiempo real → El iPad muestra el monitoreo de múltiples mercados → Ejecuta operaciones cuando aparecen oportunidades de arbitraje El sistema funciona 24/7. Cada desajuste de precio = una oportunidad de beneficio. La mayoría de la gente sigue operando manualmente, actualizando gráficos y dudando de cada entrada. Mientras tanto, este estudiante de ingeniería de 19 años convirtió 68 dólares en 750.000 dólares dejando que Claude Code hiciera lo que los humanos no pueden: Procesar 50 mercados al instante y ejecutar operaciones sin miedo. ¿Por qué la gente sigue haciendo trading manualmente?