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AI 资讯

The Google / Xreal Aura XR glasses are now available to preorder

The Project Aura glasses collaboration between Xreal and Google is now one step closer to being something you can buy. Reservations for the second Android XR device, now dubbed the Xreal Aura, are available for $99 starting today, with a full launch in the US, UK, Japan, Canada, and South Korea expected sometime this Fall. […]

2026-06-17 原文 →
科技前沿

The Future of Home

How we live now is defined by unprecedented forces. In this special issue, WIRED and Architectural Digest help you understand what home will look like tomorrow—and beyond.

2026-06-17 原文 →
开发者

How we became the first Indian hosting company to deploy Cloudflare Magic Transit

I run a hosting company. I'm also a BCA student. These two things coexist somehow. GigaNodes started in 2022 as a game server hosting brand — Minecraft, FiveM, ARK, the usual. Over time it grew into a proper VPS and dedicated server operation under GigaNode Technologies Private Limited, with AMD EPYC 7C13 hardware co-located at Yotta DC Noida. Earlier this year we did something I haven't seen any other Indian hosting provider do: we deployed Cloudflare Magic Transit across our entire network. What that actually means Magic Transit is not Cloudflare CDN. It is not a proxy. It is Cloudflare's enterprise network product where your IP prefixes get announced via BGP into Cloudflare's global backbone. All traffic destined for your servers enters Cloudflare's network first, gets scrubbed for attack traffic, and clean packets get forwarded to your data center via GRE tunnel. To deploy it, your infrastructure partner needs to have BGP-level integration with Cloudflare. Individual companies can't just sign up for it. We made it work through our partnership with Advika Datacenters Private Limited (AS135682) at Yotta DC Noida. The result: DDoS traffic never reaches our hardware. Our servers don't see the attack at all. Why no other Indian provider had done this Most Indian hosting providers use blackholing. When an attack comes in, they null-route your IP. Server goes offline. Attack stops eventually. Server comes back. That is the standard. That is what "DDoS protection included" usually means in India. The difference with Magic Transit is that legitimate traffic keeps flowing while attack traffic gets dropped. Your server stays online. Players stay connected. Trades don't get interrupted. We found out pretty quickly this actually works. We took a 1.7 Tbps attack after deployment. The servers didn't notice. A 1.7 Tbps volumetric attack hit our network in May 2026. Cloudflare absorbed it at the edge. No downtime. No support tickets from customers. We found out from the Cloudfla

2026-06-16 原文 →
AI 资讯

I Moved Everything to a $4.50 Hetzner Box. Here's What Broke and What Didn't.

Last year my side project was running on AWS. A t3.small EC2 instance, an RDS PostgreSQL db.t3.micro, an S3 bucket, and a CloudFront distribution. Total bill: $47/month for an app with 200 daily users. Then someone on Reddit told me to look at Hetzner. I now run the same stack on a single CAX21 (4 vCPU ARM, 8GB RAM, 80GB SSD) for €5.49/month. Here's exactly what happened. The Migration What I was running on AWS: Node.js API (Express) PostgreSQL database Redis for sessions Nginx reverse proxy Static files on S3 + CloudFront What I moved to Hetzner: Same Node.js API PostgreSQL installed directly on the server Redis installed directly on the server Nginx + Certbot for SSL Static files served by Nginx Total migration time: one Saturday afternoon. The hardest part was setting up automated backups (solved with a cron job + Hetzner's snapshot API). What Broke Nothing critical, but: No managed database failover. On RDS, if the database crashes, AWS restarts it automatically. On Hetzner, if PostgreSQL crashes at 3 AM, I'm the one fixing it. In 8 months, this has happened zero times. But it could. No CDN by default. My static assets now serve from a single Hetzner datacenter in Germany. For my EU-heavy userbase, this is actually faster than CloudFront. For US users, it's about 50ms slower. I added Cloudflare (free tier) in front and the problem disappeared. Deployment changed. No more eb deploy or push-to-deploy. I wrote a 12-line bash script that SSHs in, pulls from git, runs migrations, and restarts PM2. Takes 8 seconds. Honestly prefer it — I know exactly what's happening. The Cost Comparison at Every Scale This is what surprised me most. The gap isn't just at my small scale — it gets wider as you grow: SpecAWSDigitalOceanVultrHetzner2 vCPU, 4GB$30/mo$24/mo$24/mo€4.50/mo4 vCPU, 8GB$61/mo$48/mo$48/mo€8.50/mo8 vCPU, 16GB$122/mo$96/mo$96/mo€16/mo Hetzner is roughly 5-7x cheaper than AWS at every tier. DigitalOcean and Vultr sit in the middle. 👉 Calculate your exact costs When

2026-06-16 原文 →
AI 资讯

The Reference Check Questions Nobody Asks AI Vendors

I have done this process wrong more times than I would like to admit. You call the references the vendor sends you. Three customers, all happy, all articulate, all saying roughly the same things. You hang up feeling good. You sign. Six months later you are dealing with a support team that responds every 72 hours and a renewal quote that is 40% higher than year one. The reference check told you nothing useful. Not because the customers lied. Because you asked the wrong questions. Here is what I ask now. "How many people at the vendor have you spoken to in the last six months?" One contact who handles everything and is sometimes slow — that tells you something. A team of people across sales, technical support, and leadership — that tells you something different. Enterprise AI vendors with thin account teams show their limitations at exactly the moment you need them most: when something breaks at the worst possible time. "Tell me about the last time something broke in production." Not IF something broke. Something always breaks. I want to know what happened next. Did the vendor show up? Did they communicate clearly while the issue was live? Did they follow up after closing the ticket, or did they close it and disappear? The answer to this question tells me more about a vendor than any product demo. "What do you know now that you wish you had known before signing?" This question works because it is framed as advice, not criticism. Reference customers who would never say "this product has problems" will happily answer this one honestly. Listen for anything about pricing surprises, scope limitations that only appeared after deployment, or feature gaps the sales team glossed over. "When you renewed, did you evaluate alternatives?" Renewal is the honest signal. A customer who renewed without looking elsewhere is genuinely satisfied. A customer who looked at three other options and came back is someone who chose this vendor over real competition. A customer who is approachin

2026-06-16 原文 →
AI 资讯

Mid-Conversation System Prompts: Steering an Agent Without Breaking the Cache

Here is a problem I hit building a long-running agent: I needed to inject a new instruction partway through a session ("the project is Go, write Go") but editing the top-level system prompt to add it invalidated my entire prompt cache. Every cached turn got reprocessed at full price. The fix is a feature that landed in the current Claude models: mid-conversation system messages. Here is what it is and when to use it. The setup that breaks A long agent session has a large, stable system prompt and a growing message history, and you cache the prefix so each turn reuses the prior work cheaply. That works until you learn something mid-session that the agent needs to know: a mode toggled, the user delivered async context, files changed on disk, the token budget dropped. The naive move is to edit the system prompt to include the new fact. But the system prompt sits at the front of the cached prefix. Change one byte there and you invalidate everything after it. Your whole conversation history reprocesses at full input price on the next request. For a long session, that is expensive and slow. The fix: a system message in the messages array The current models let you put a system -role message directly in the messages array, after the history, instead of editing the top-level system : const response = await client . messages . create ( { model : " claude-opus-4-8 " , max_tokens : 16000 , system : [ { type : " text " , text : STABLE_SYSTEM , cache_control : { type : " ephemeral " } }, ], messages : [ ... history , // cached prefix, untouched { role : " user " , content : latestUserMessage }, // @ts-expect-error: role:"system" SDK types may still be landing { role : " system " , content : " This project is Go. Write all code in Go. " }, ], }, { headers : { " anthropic-beta " : " mid-conversation-system-2026-04-07 " } }, ); Because the new instruction sits after the cached history, it invalidates nothing before it. The cached prefix stays intact, you pay full price only for the

2026-06-16 原文 →