2026-03-17 00:00:00:03014558210http://paper.people.com.cn/rmrb/pc/content/202603/17/content_30145582.htmlhttp://paper.people.com.cn/rmrb/pad/content/202603/17/content_30145582.html11921 彭清华会见加拿大议会加中议会协会代表团
据伊朗方面3月16日消息，伊朗新任最高领袖穆杰塔巴·哈梅内伊已下令，要求由已故最高领袖阿里·哈梅内伊任命的机构负责人和官员继续履行职务。，这一点在在電腦瀏覽器中掃碼登入 WhatsApp，免安裝即可收發訊息中也有详细论述
Hi HN, I’m Alberto. I co-founded Didit (https://didit.me) with my identical twin brother Alejandro. We are building a unified identity layer—a single integration that handles KYC, AML, biometrics, authentication, and fraud prevention globally. Here’s a demo: https://www.youtube.com/watch?v=eTdcg7JCc4M&t=7s.Being identical twins, we’ve spent our whole lives dealing with identity confusion, so it is a bit of irony that we ended up building a company to solve it for the internet.Growing up in Barcelona, we spent years working on products where identity issues were a massive pain. We eventually realized that for most engineering teams, "global identity" is a fiction—in reality it is a fragmented mess. You end up stitching together one provider for US driver's licenses, another for NFC chip extraction in Europe, a third for AML screening, a fourth for government database validation in Brazil, a fifth for liveness detection on low-end Android devices, and yet another for biometric authentication and age estimation. Orchestrating these into a cohesive flow while adapting to localized regulations like GDPR or CCPA is a nightmare that makes no sense for most teams to be working on.When we looked at the existing "enterprise" solutions, we were baffled. Most require a three-week sales cycle just to see a single page of documentation. Pricing is hidden behind "Contact Us" buttons, and the products themselves are often bloated legacy systems with high latency and abysmal accuracy.We also noticed a recurring pattern: these tools are frequently optimized only for the latest iOS hardware, performing poorly on the mid-range or older Android devices that make up a huge percentage of the market. This results in a "leaky" funnel where legitimate users drop off due to technical friction and fraud goes undetected because data points are spread across disparate systems. Also, these systems are expensive, often requiring massive annual commits that price out early-stage startups.We wanted to build a system that is accessible to everyone—a tool that works like Stripe for identity, where you can get a sandbox key in thirty seconds and start running real verifications with world-class UX and transparent pricing.To solve this, we took the "delusional" path of full vertical integration. Rather than just wrapping existing APIs, we built our own ID verification and biometric AI models—from classification and fraud detection to OCR models for almost every language. This vertical integration is fundamental to how we handle user data. Because we own the entire stack, we control the flow of sensitive information from end-to-end. Your users' data doesn't get bounced around through a chain of third-party black boxes or regional middle-men. This allows us to provide a level of security and privacy that is impossible when you are just an orchestration layer for other people's APIs.We believe that identity verification is one of the most critical problems on the internet, and must be solved correctly and ethically. Many people are rightfully skeptical, especially given recent news about projects that have turned identity into a tool for mass data collection or surveillance. We don’t do anything of the sort, but we also don’t want to be coerced in the future, so we facilitate data minimization on the customer side. Instead of a business asking for a full ID scan, we allow them to simply verify a specific attribute—like "is this person over 18?"—without ever seeing the document itself. Our goal is to move the industry away from data hoarding and toward zero knowledge, or at least minimal knowledge, verification.The result of our all-in-one approach is a platform that increases onboarding rates while lowering identity costs. We’ve focused on building a high-confidence automated loop that reduces the need for manual review by up to 90%, catching sophisticated deepfakes and spoofing attempts that standard vision models miss. Our SDK is optimized for low bandwidth connections, ensuring it works on spotty 3G networks where legacy providers usually fail.We are fully live, and you can jump into the dashboard at。谷歌是该领域的重要参考
The mypy project itself -- ~100k+ lines of Python -- achieved a 4x end-to-end speedup by compiling with mypyc. The official docs say "1.5x to 5x" for existing annotated code, "5x to 10x" for code tuned for compilation. The spectral-norm result (14x) lands above that range because the inner loop is pure arithmetic that mypyc compiles directly to C. On our dict-heavy JSON pipeline, mypyc hit 2.3x on pre-parsed dicts -- closer to the expected floor.