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This is a submission for Weekend Challenge: Passion Edition What I Built The theme was passion, and mine has always been the sky and everything beyond it. Day or night, there's a specific kind of awe in remembering that the sky isn't a backdrop. It's real, it's happening right now, and every point of light is an actual place. Night is simply when you can see the most of it. I wanted to put that feeling into a browser tab. Zenith takes your location, cinematically lowers you from orbit down onto your exact spot on Earth, and becomes a first-person view of your real sky, one you can drag to look around. Every star is where it actually is. The Sun, the Moon, and the visible planets are computed for your latitude, longitude, and this exact minute, and placed where they truly are. It isn't a fixed picture either: the whole sky rotates slowly in real time, so stars rise and set while you watch. Tap any object and you travel to it. The camera flies out through the real starfield, the object grows from a point into a detailed close-up, and a short, grounded briefing appears telling you what you're actually looking at, from where you're standing, right now. A warm voice reads it to you. Stay a while and Zenith reminds you that there are people over your head: it shows how many humans are in space this moment, by name, and draws the real International Space Station crossing your sky whenever it's above your horizon. Not information about space. The quiet, enormous wonder of looking up and knowing, for a moment, exactly what you're looking at. Demo Live: https://zenith-rgerjeki.vercel.app A short walkthrough: the descent to your location, dragging the real sky, and flying to a planet for an AI briefing read aloud in a warm voice. Code rgerjeki / Zenith Zenith The sky above you, right now. I've always been drawn to the sky, and everything beyond it. Zenith is a first-person view of yours : it takes your location, lowers you onto your exact spot on Earth, and gives you the real

Building an explainable AI platform that helps district administrators allocate resources and farmers make better crop decisions using Gemini, Vertex AI, BigQuery, and Google Cloud. Climate disasters are not just weather events. They are decision problems. When forecasts predict a strong El Niño, governments do not simply need more data. They need answers to questions like: Which districts will be affected first? Where should limited water resources be sent? Which crops are likely to fail? What should farmers sow instead? Why is the AI recommending this action? Existing dashboards provide plenty of charts. Very few provide decisions. That became the motivation behind El Niño 2026 Decision Copilot , an AI-powered decision intelligence platform built during the Google Cloud Gen AI Academy APAC Hackathon . The Problem India depends heavily on the monsoon. A severe El Niño can lead to: Rainfall deficits Reservoir depletion Groundwater stress Crop failures Rising food prices Rural employment challenges The information already exists across dozens of government portals, weather services, satellite datasets, and agricultural reports. The challenge is that it is scattered. District collectors do not have time to manually combine: Weather forecasts NDVI satellite imagery Reservoir levels Mandi prices Contingency plans Drought indicators Farmers face an even bigger challenge. Most need a simple answer: Given my district, should I plant the usual crop this season? The Goal Instead of building another dashboard, I wanted to build an AI system that reasons over multiple data sources and produces explainable recommendations. The platform serves two audiences through the same intelligence engine. District Administrators They receive: District risk scores Interactive risk maps Reservoir outlook Crop stress indicators Resource allocation recommendations AI-generated explanations Instead of simply showing that a district has high risk, the system explains why . Farmers Farmers intera

What nobody tells you about exporting your multi-agent prototype to a local workspace. Every architect who's prototyped a multi-agent app in Google AI Studio eventually hits the same wall: the prototype works, but it lives in a browser tab. At I/O 2026, Google shipped a fix — Export to Antigravity, a one-click handoff to a local production workspace, carrying "all the context" with it. I ran a real two-agent prototype through it. Here's exactly what survived the trip, what didn't, and what I had to fix by hand — including a bug that had nothing to do with the export itself. 1. The Pilot Project + The Click The project: Research Digest — a sequential two-agent app. Agent 1 (Researcher) takes a topic, uses grounded web search to gather sources. Agent 2 (Editor) synthesizes those findings into a polished digest. Persistence via Firestore, with a history archive of past digests. Built entirely from a single prompt in AI Studio's Build mode . Along the way, provisioning Firestore surfaced my first real gotcha before I even got to the export step — more on that below. Triggering the export: Code tab → Export → Export to Antigravity. The dialog is genuinely informative — it tells you upfront what's coming: all project files, conversation history, and explicitly "1 secret will be included." 2. What Actually Survives the Trip The export dialog's claims, checked one by one: Claimed to transfer What I found All project files ✅ Confirmed — full structure landed intact: .agents, .antigravity, src, config files, README.md with setup instructions Secrets (1 secret) ✅ Confirmed — GEMINI_API_KEY arrived populated in .env, worked immediately, no manual re-entry Conversation history history❌ Did not transfer. The imported "Research Digest" project showed "No conversations yet" in Antigravity's Agent Manager, despite the dialog's explicit promise. Checked twice, on two separate screens — consistent result. 3. The Gotchas Gotcha 1 — "Conversation history will carry over" is currently no

You can see if ads on Google Search, Google Discover, and YouTube were made or edited using AI from a new section in Google's "My Ad Center," as reported earlier by TechCrunch. The update, announced on Thursday, adds a "created or edited with AI" label under the "how this ad was made" tab. Users can […]

If Google's AI tools are used, it will automatically be noted in My Ad Center.

Google AI recently became the official AI Model and Platform Partner of DEV Community. As someone building an AI routing platform, I paid attention. Google's Gemini Enterprise Agent Platform (formerly Vertex AI) promises enterprise-grade AI agent orchestration — and with the DEV partnership, there's never been a better time to explore it. In this article, I'll share how I integrated Google Cloud's Agent Platform with my existing AI router (built on Neon PostgreSQL), what I learned about Gemini's enterprise capabilities, and why the Google AI + Neon + Algolia trifecta is the ideal stack for AI-first applications in 2026. Why Google Cloud's Agent Platform? The Gemini Enterprise Agent Platform is Google's answer to the question: "How do I orchestrate multiple AI agents in production?" It provides: Pre-built agent templates for common workflows (customer support, code review, data analysis) Grounding with Google Search — your agents can cite real, current sources Context caching — reduce costs by reusing conversation context across turns Multimodal understanding — Gemini processes text, images, audio, and video in one call Enterprise security — VPC controls, data residency, IAM integration For QuantumFlow AI (my AI routing platform), the Agent Platform solved a critical problem: how to orchestrate 26 different AI models without building a custom orchestration layer from scratch. The Architecture: Google Cloud + Neon + Next.js Here's the stack I built: User Request → Google Cloud Agent Platform (Gemini orchestration) → QuantumFlow Router (selects optimal model) → Local models (Ollama — free, sovereign) → Cloud models (GPT-4o, Claude, DeepSeek, Gemini) → Neon PostgreSQL (logs, analytics, cost tracking) → Algolia (search across all AI responses) Why Neon (DEV's Database Partner)? Neon is dev.to's official database partner, and for good reason. It's serverless PostgreSQL with: Database branching — create a full database copy in seconds (like git for data) Bottomless storage

If you’re looking for a relatively affordable way to cut down on cooling costs, Google’s Nest Thermostat can help. It’s packed with smart controls and energy-saving features, and right now it’s on sale in white for $79 ($50 off), which is its best price of the year, at Amazon. The smart thermostat is quick to […]

State agency's delay could mean free robotaxi rides in company’s new Ojai vehicle for a few months.

Google shipped AlloyDB AI functions GA with a proxy model architecture that trains a lightweight local model from LLM outputs, then runs queries at database speed without external calls. Smart batching delivers 2,400x throughput improvement. The proxy model reaches 100,000 rows per second in preview, but benchmark numbers apply only to ai.if in internal testing. By Steef-Jan Wiggers

The feature can do things like apply cinematic relighting to brighten up a dark clip, swap out a plain background for something fun, or add artistic styles to videos.

The company's streaming devices aren't quite keeping up with competitors in several important categories.

It allows you to reimagine videos stored in Google Photos using Gemini Omni.

Android Bench is evolving, and developers can help guide that process.

Google's upcoming Pixel lineup might cost more than last year's. A report from Dealabs spotted by 9to5Google suggests that Google could raise the starting price of its 41mm Pixel Watch 5 to $399, while adding LTE could bump the price to $499. That's a $50 jump from the base Pixel Watch 4, which starts at […]

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Nine months ago I wrote a post on here claiming my ENS identity architecture had reached "85% Knowledge Panel trigger probability." Two things happened since. Google's Knowledge Graph actually minted an entity node for me. And I learned that the 85% number was fiction — mine. This is the honest retrospective. The timeline, with receipts Date What happened Aug 2025 ookyet.com first indexed Oct 2025 Entity markup shipped: Person @graph , Dentity verification, ENS identifiers. The "85%" post Jun 2026 Search Console turned red: Q&A errors, Profile page: Invalid object type . Cleanup Jun 28, 2026 Fixed markup deployed. Then: hands off Jul 2, 2026 Knowledge Graph Search API returns a machine-minted Person node for ookyet Jul 7, 2026 Search Console fully green: ProfilePage valid, indexed pages up, zero 404s Still no Knowledge Panel. Keep reading — that part matters. What Google actually built You can reproduce this: curl "https://kgsearch.googleapis.com/v1/entities:search?query=ookyet&limit=10&key=YOUR_API_KEY" { "result" : { "@id" : "kg:/g/11z806my44" , "name" : "Qifeng Huang" , "@type" : [ "Person" ] } } Three details in that tiny response taught me more than anything I shipped in 2025. The /g/ MID is machine-minted. You can't register one, buy one, or submit one. Google's entity reconciliation creates it when enough independent sources agree that a person exists. This is the mechanical prerequisite for a Knowledge Panel — the entity has to exist in the graph before anything can be displayed about it. The node's name is my real name, not my handle. My site declares name: "ookyet" . The node says "Qifeng Huang" — pulled from the high-authority anchors (LinkedIn, ORCID), not from my self-declaration. Third-party corroboration outweighs anything you say about yourself. Expected, and honestly a relief: the graph is working as designed. The Knowledge Graph holds 8 distinct people named Qifeng Huang. Query any of them by real name and you get a crowded namespace. Query ookyet

Google's new phones could feature glowing LEDs and higher price tags.

Google's upcoming event in August will introduce new Pixel devices.

Google's next Pixel event will be August 12 at 6pm ET.

Google is hosting its next Made by Google launch event for Pixel hardware on August 12th in New York City, according to an invitation sent by Google to The Verge. Unusually, the event is taking place in the evening: It'll kick off at 6PM ET that day. The email also includes a brief animation teasing […]