与「Booking」相关的搜索结果

This March, we introduced Ask Maps, the biggest @googlemaps update in a decade. Now, we’re making it even more helpful and bringing it to more people. 🌏 Expanded availability: Rolling out in Australia, Brazil, Canada, Indonesia, Japan and Mexico, along with over 150 countries and territories in English. ✨Get more done with Ask Maps: Including complex, multi-step tasks, like ordering food – along with finding the perfect hotel or discovering nearby events. ⌚Real-time transit information: Stay informed about up-to-the-minute delays and conditions for your bus, train, and more. 💬Personal intelligence and past conversations: Choose to securely connect @Gmail so Ask Maps can automatically reference booking details, like a hotel reservation or flight information. You can also pick up conversations just where you left them. 🗣️An easier way to help your community: Share tips and suggest edits to a place conversationally, like changing a store’s hours, right in Ask Maps and the Contribute tab.

Gemini Spark can now tap into @GoogleChrome’s auto browse feature to take care of complex errands for you online 🔎 With your permission, Gemini Spark can use your logged-in accounts to take care of tasks like scheduling viewings for apartments you've saved or researching flight options and starting the booking process.

“The only job left is to understand what you don't like, put it into words, and tell the AI.” Here’s my new episode with @jxnlco (DevEx at OpenAI) where he showed me how he uses Codex throughout his workday, including how to: → Set up a chief of staff for Slack and email → Turn past sessions into new AI skills → Give long-running projects verifiable goals Some example Codex use cases from Jason: “I want you to read the past week of Slack messages I’ve written and make a skill to figure out how to talk like me.” “Turn this thread into a heartbeat. I want you to check my emails, my Slack, my Linear, and tell me what I need to prioritize.” “Codex can find a booking ticket and check into the flight for me and text me the boarding pass to my phone.” Jason wrote the official OpenAI handbook on how to get the most out of Codex, so don’t miss this episode. 📌 Watch now: Thanks to our sponsors: @RiversidedotFM: All-in-one AI studio for podcasts and video Google AI Studio: Build apps with Nano Banana, and more

Create professional promotional videos for your hotel, vacation rental or real estate listings. Learn more: #ImmoStoryAI# #Probex# #Hotel# #Hotels# #Vastgoed# #RealEstate# #Booking# #BookingCom# #HotelMarketing# #Airbnb# #Trivago# #Zimmo# #HotelVideo#

《量化选股初探》 不写段子了，来点干货。 今天傻哥说个有用但枯燥的东西：量化选股 美股现在的信息化程度非常高。 这意味着你的交易idea线索可以通过量化条件，非常高效的筛选。 傻哥距离说明吧。 美国和加拿大有大约2.2万家公司。 人力一个个看起来， 别说普通散户不行，连几十人的专业团队都看不过来。 咋办？量化选股 傻哥要从2.2万个股票中，选出稳定的复利机器。 核心侧重历史质量 在这里质量中，侧重roic数据，即资本效率 为了确保雪够厚，还把margin调了下 考虑成长性，还在eps增长和revenue增长中画了红线 条件如下： ROIC LTM > 15% ROIC 5年平均 > 15% ROIC 10年平均 > 12% 5年平均EBIT Margin > 12% 5年平均FCF Margin > 8% 5年收入CAGR > 7% 5年EPS CAGR > 8% 未来收入、EPS仍保持温和增长 PE、EV/EBITDA、P/FCF、FCF Yield、PEG均不过分 净负债/EBITDA < 2倍 最后筛出了5家公司： Adobe Booking Netflix Paycom WMS 这些公司都蛮有看点的： 都是商业模式成熟、资金效率高、现金流稳定、利润率多年居高不下，护城河被充分验证的。 傻哥就不去一一去讲解这5家公司了。 另外，除了稳定的复利机器，傻哥还调出了成长爆发股，和低估老登股等。 这里的条件不一而足 层层筛选，从2.2万家，筛选至10家以内 慢慢把玩，颇有妙处 足可以作为选筹、基本面判断的利器。

Top ⁠computer ⁠chip equipment ⁠maker ASML said its capacity expansion ​plans in 2027 and 2028 unveiled ‌today take into ⁠account ⁠demand for its tools from Elon Musk's planned ​Terafab chip production facility in Texas. "We're in dialogue with all our customers and ​we know ... what their building plans are," ⁠CFO Roger ⁠Dassen ​said on a call. "Terafab is also part of ​those plans." Dassen also said ASML was close to fully booking its 2027 EUV capacity and ⁠had already secured a substantial number of 2028 extreme ultraviolet lithography (EUV) orders.

Super excited to be the very first rider in our Robotaxi internal trial. Ordered it right outside our office building — hailed, got in, sat down, and off we went. This marks the first time we've fully connected the online booking and offline riding experience. Sitting in that car, I couldn't help but feel a bit emotional. We announced the Robotaxi plan last November, kicked off public-road testing this January, rolled out production vehicles in May, and now, just eight months later, we've run the whole loop and started internal trials. That's faster than we ever expected. Huge thanks to everyone on the Robotaxi team who made this happen. True large-scale deployment of Robotaxis is a long journey. Next, we'll keep doubling down on safety, fine-tune the experience, and improve generalization, steady steps all the way. I'm really looking forward to the day when our internal users, locals in Guangzhou, and travelers visiting the city can all pull out their phones, hail a XPENG Robotaxi, and hop in for a ride. And for this first taste of Robotaxi? I give it a solid 10/10!

claude fable 5 can scrape thousands of sold homes and finds the patios with zero shade in 100°+ heat. then it mails the owner a postcard with the fix rendered into their own backyard here's the system you can sell to contractors: - scrapes every home sold in the metro in the last 12 months (recent buyers spend the most) - vision-reads the listing photos, skips the 64% with cover already - measures the sun on each patio, hour by hour, off google's satellite data - renders a louvered pergola into the owner's actual backyard photo - prints the diagnosis on the postcard: "your patio takes 11 hours of direct sun a day. saturday it hits 97°." - QR opens a heat report for their exact address with a booking link every install is $6.5k to $18k, one close covers months of retainers and homes sell every single day. reply "SYSTEM" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

Say you run a salon. You tell Dina your hours and details, and publish it as a service. Customer tells Dina "book me a slot at 5". Customer's Dina finds your Dina, it gets approval from you, and booking is done. Your knowledge becomes a service. Your Dina becomes the API.

2027 年記憶體供需缺口將持續擴大，這才是 Apple 遊說白宮「避免長鑫存儲未來被列入實體清單」的真相 ▌先講我最新的產業調查：Apple 面對的壓力，已從記憶體成本大增，升級到供需缺口持續擴大。 1. 2026 年用於消費電子的記憶體產能中，預計 15–20% 將於 2027 年轉供資料中心，且後續不排除繼續擴大。 2. 受記憶體（LPDDR）供應緊張影響，Apple 在 2H26–1Q27 對 A20 處理器的實際拉貨量，可能比原目標少 10–20%（不過，這也可能部分是 Apple over-booking 的結果）。 ▌長鑫在招股書中提到，該公司的產能遠低於國內需求；加上全球記憶體供需持續失衡，因此即便 Apple 遊說成功並向長鑫採購 DRAM，也不會顯著降低成本與改善供需缺口。但在供需失衡持續擴大下，Apple 仍有必要爭取新的供應來源。 ▌這也解釋為何 Apple 這次會比 2022 年評估長江存儲更積極。當年的長江，是提供改善 NAND 成本的選項；而這次的長鑫，則是管理 DRAM 供需失衡風險的選項。 ▌Tim Cook 是少數能同時與美中政府維持良好關係的科技領袖，故此事最好趕在他卸任 CEO 前完成。即便最終未果，透過媒體披露後，也能讓市場留下「Apple 已盡力、無奈仍受限於美方政策」的印象，或能緩和市場對漲價與交期拉長的不滿。