今日已更新 420 条资讯 | 累计 20392 条内容
关于我们

标签:#art

找到 1275 篇相关文章

开发者

Google’s first smart speaker in six years arrives next week

Google's first new smart speaker in six years starts shipping on June 29th, narrowly missing its promised spring launch window. Preorders for the Google Home Speaker open today, June 17th. Nothing has changed hardware-wise in the nine months since the $99 speaker was announced. It has the same slightly squished round design, with touch-capacitive buttons […]

2026-06-17 原文 →
AI 资讯

Jackery announces ‘world’s slimmest’ fridge battery

Jackery is jumping on the fridge-battery trend with what it says is the "world's slimmest." FridgeGuard also looks nice; a break from power stations that tend to look more at home at a job site than the kitchen or living room. Measuring just 2.63 inches (67mm) thick, the Jackery FridgeGuard power station is meant to […]

2026-06-17 原文 →
AI 资讯

Got Thread problems? There’s an app for that

The new Thread Networks Diagnostics Tools app from Thread Group, the standards body behind the wireless IoT protocol, officially launches in beta today. The app, which arrives on iOS and has been available on Android in alpha for a few weeks, is the first dedicated tool to provide visibility into your Thread-based smart home network. […]

2026-06-17 原文 →
开发者

Will Matter finally be able to do what it should have always done?

Matter, the smart home interoperability standard, might finally get a feature that should have been there from day one: a single shared Matter network managed by multiple ecosystems. With this feature, called Joint Fabric, smart devices added to the network will be controllable by any authorized platform - Apple Home, Google Home, Amazon Alexa, and […]

2026-06-17 原文 →
AI 资讯

My backyard made me a color-changing smart lighting convert

I'll admit it. I was wrong. Wildly colorful lighting is delightful for your smart home - well, outdoors, at least. Smart lighting is one of my favorite features of the smart home - it combines convenience with ambiance, letting you change the entire look of your room with just a press of a button. But, […]

2026-06-17 原文 →
AI 资讯

I've Been Trying to Build Something Online Since 2020. Still Not There. Looking for Advice.

In 2020, I discovered the idea that people could make money online by building things. Since then, I've tried almost everything. I started websites. I learned design. I learned marketing. I built digital products. I launched projects that nobody used. I launched projects that got almost no traffic. Every year I thought: "Maybe this is the year it finally works." But somehow I always ended up back at zero. The frustrating part is that I didn't quit. For 5 years I've been consistently learning new skills: Graphic design Website building Digital products Content marketing SEO Social media Yet I still haven't reached the point where I can say: "Yes, this business is working." Recently I spent weeks building a library of 500+ Notion templates. I launched it. The result? Almost nothing. No viral launch. No overnight success. Just another reminder that building is easier than distribution. That's the lesson that keeps hitting me: Building isn't my problem anymore. Getting attention is. I can create products. I can design landing pages. I can write content. But distribution still feels like a puzzle I'm trying to solve. So I'm asking developers, founders, and creators who are further ahead: If you were starting again today with no audience and no reputation, what would you focus on? Would you: Double down on content? Build more products? Focus entirely on one distribution channel? Spend more time networking? I'm genuinely curious because after 5 years of trying different things, I'm convinced the answer isn't "work harder." It's probably "work differently." I'd love to hear your advice.

2026-06-17 原文 →
AI 资讯

The $0 Bug That Cost Us $1,800 in API Calls

Last quarter our OpenAI bill went from $620 to $2,480 in 23 days. No new features shipped. No traffic spike. Zero error alerts. Deployment logs were clean. Just a number climbing in silence while five engineers stared at dashboards that gave us totals and nothing else. This is what we found. And why "cost monitoring" is completely the wrong mental model. The dashboard that answers the wrong question First thing I did was open the OpenAI usage dashboard. It showed me a total. A graph going up. A model breakdown. I knew we spent $2,480. I still had no idea which feature spent it, which service triggered it, or which user was responsible. The dashboard was answering "how much" while we were desperately asking "what caused it." Those are completely different questions. Almost every cost tool on the market only answers the first one. That distinction matters more than most engineering teams realise until they are staring at a bill like ours. Three features, zero visibility We had three features hitting GPT-4o: A document summariser, triggered manually by users An inline suggestion engine, triggered on keystrokes A batch report generator, triggered on export Any one of them could be the problem. Or all three. Or one specific tenant hammering one endpoint in a loop nobody noticed. Without attribution at the feature, service, and user level, we were just guessing. So I did what most engineers do: optimised the feature that felt most expensive. Added caching to the one that ran most often. Two weeks later the bill was still climbing. Guessing at cost problems without attribution data is exactly like debugging a performance issue without a profiler. You move things around and hope. 48 hours of real data A teammate dropped CostReveal in our Slack. I set it up that evening. The Node.js SDK wraps your existing provider calls. You instrument each one with a feature name, service context, and user or tenant ID. That is the entire integration for the base case: import { CostReveal

2026-06-17 原文 →