与「Inon」相关的搜索结果

Thank you all for your patient waiting! The rewards for this month are finally ready! 感謝大家的耐心等待！ 這個月的獎勵終於準備好了！ #Pokémon# #Inon# #ナンジャモ#

xAI just released Grok Build CLI and it’s a game changer for developers Grok Build is a powerful AI coding agent and CLI built for professional software engineering and complex coding workflows running directly in your terminal With Grok Build CLI, you can: - Plan and review tasks before execution with clean diffs - Run multiple sub-agents in parallel for large projects - Use headless mode for automation and scripting - Seamlessly work with your existing tools and setups This is xAI going all-in on giving power users real engineering tools Currently in early beta and exclusively available for SuperGrok Heavy subscribers If you’re on SuperGrok Heavy, you can start using it right now Check it out here:

the level of narcissism and main character syndrome with these ai basketball game edits is killing me. yes you’re very pretty but you weren’t at a basketball game and no one was zooming in on you. how is this not embarrassing 😭

I've recently got in on the act of getting AI to solve open problems in mathematics. More precisely, I gave some questions asked by Melvyn Nathanson to ChatGPT 5.5 Pro, to which I have been given access, and it answered them. 🧵

Haven’t been to a crypto event this engaging in a long time - everyone’s going all-in on the competition 😄 Welcome to Korea! 🇰🇷 @Euphoria_fi @megaeth @bread_ @hotpot_dao

**Summary: Discussion between Jeff Liang and Quant Alex Wu on Optimizing Option Order Execution and Slippage Capture** The core topic of their conversation is: **The current option limit order execution is poor (high slippage, low fill rate), essentially due to the lack of professional high-frequency / algorithmic market-making capabilities. They need to upgrade from “cutting meat with a blunt knife” to a sophisticated Delta-hedging + options market-making system.** ### 1. Problem Diagnosis - Current order placement feels like **“cutting meat with a blunt knife”** — poor queue position, low fill probability, and severe slippage. - Jeff provided concrete data: **Average loss of approximately $5.2 per executed option contract** (slightly less than 1 bp), including fees and rebates — still unacceptable. - Even with perpetual futures maker fee rebates helping a bit, the situation “cannot be ignored.” - **Price checking and adjustment frequency is NOT the root cause.** The real drivers are **fill probability** and **queue position**. ### 2. Fundamental Solution Direction (Alex’s View) - A robust **Delta-hedging system** shares significant technical overlap with high-frequency market-making systems for spot, futures, and perpetual contracts. Without this foundation, one is essentially powerless against adverse selection. - Using **maker orders for Delta hedging** is conceptually the same as **Delta-1 market making for inventory risk management** — the analogy made everything “suddenly clear.” - Options market making and Delta-1 market making are **tightly coupled**: - The Delta-1 system handles the Delta exposure of options. - Options themselves can provide protection for Delta-1 positions. ### 3. Technical Difficulty and Implementation Path - This requires entering the realm of **algo trading / HFT**, involving substantial research and engineering resources. - **Language requirement**: Python is **not sufficient**. Must use **C++ and Rust**. - **Target clients**: Institutional clients and high-net-worth individuals engaging in on-exchange block trading. - **Detailed step-by-step roadmap from scratch (Alex’s plan)**: 1. Collect large volumes of **order book data** (snapshots, incremental updates, tick-by-tick trades) for perpetuals + futures + options. 2. Build **fill probability models + queue models**, including: - Limit order arrival intensity - Fill probability - Queue position - Latency modeling 3. First implement and validate on **Delta-1 products**, then extend the backtesting system to support these HFT primitives. 4. Expand from Delta-1 / single option contracts to **all option contracts** (requires major redesign and validation due to performance demands). 5. Develop specialized algorithms for **limit order posting + aggressive crossing** to reduce overall slippage. 6. Finally, conduct small-capital live trading validation. Alex repeatedly emphasized: **“This project is genuine heavy industry.”** ### 4. Consensus - Delta-One research is the foundation for studying option fill probabilities. - Options market making must be deeply integrated with the Delta-hedging system — they cannot be treated separately. - The current phase is **infrastructure building**, requiring patient and significant investment. **Overall Assessment**: Alex provided a highly professional and systematic optimization roadmap, covering data infrastructure, modeling, and execution layers. Jeff focused on the business pain point (real slippage costs). Both fully agree that a fundamental rebuild of the underlying high-frequency system is necessary. This is a classic **quantitative execution optimization** discussion — starting from a clear business problem and pointing directly toward building institutional-grade HFT-level capabilities.

しばらく姿を消していました🥺
この間も気にかけてくれて本当にありがとう💗 今はだいぶ元気になりました！
5月から少しずつ更新を再開します✨ これからも一緒に過ごせたら嬉しいです🥰 - I kinda disappeared for a while 🥺 Thank you so much for checking in on me, I’m feeling much better now!
Updates will slowly start again from May ✨ Missed you guys 🥰

Greater Precision and Control ChatGPT Images 2.0 can conceptualize more sophisticated images, and then actually bring that vision to life effectively. It’s able to follow instructions, preserve requested details, and render the fine-grained elements that often break image models: small text, iconography, UI elements, dense compositions, and subtle stylistic constraints, all at up to 2K resolution. Zoom in on the rice…

Human orgs are not legible, the CEO can’t see/feel/zoom in on any activity in their company, with real time stats etc. I have no doubt that it will be possible to control orgs on mobile, with voice etc., but with this level of legibility will that be optimal? Not in principle and asymptotically but in practice and for at least the next round of play.