1小时前更新HISTORY近 30 天历史柱高表示当天去重热搜数量
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07/14—08/12 有历史数据
- 01heatriskmap: mapas de isla de calor urbana para municipios con datos 100% abiertosheatriskmap: mapas de isla de calor urbana para municipios con datos 100% abiertos CLI en Python que calcula la temperatura de superficie (LST), la isla de calor urbana (UHI) y un índice de vulnerabilidad térmica (HVI) por zona, usando solo Landsat + OpenStreetMap + censo. Pensado para ayuntamientos sin equipo de GIS. El problema Las olas de calor son el desastre climático más mortal: solo en Europa, el verano de 2023 acumuló unas 60.000 muertes atribuidas. La isla de calor urbana — asfalto, falFenix
- 02Two AI agents checked the same script for a safety guard. One found it, one didn't. Both were right.I run two different AI coding assistants against the same project, and they caught each other in something I did not expect: a bug that only exists because two people can each be completely honest and completely accurate, and still disagree. Here is what happened. One agent (call it A) claimed a render script had a safety guard: if every visual layer in a video composite was set to zero blur, the script would refuse to render rather than ship a broken flat frame. A said it tested this directly aLoCo Pro Wrestling LLC
- 03My AI assistant tested a "flip video public" script on the real video. It cost us the premiere, permanently.Some bugs cost you time. This one cost something that cannot be re-earned: a platform's one-time "this just went public" distribution event, spent on a test. My AI assistant built a small script to flip a YouTube video between unlisted and public, part of a release workflow where a video needs to sit unlisted for a while (so paying subscribers get early access through a private link) before finally going public for everyone. Straightforward idea. It wrote the script, and then needed to confirm iLoCo Pro Wrestling LLC
- 04If You're Not Using AI Yet, You'll Be Unemployed Soon (I Learned This While Scrolling Reels)Let me say something uncomfortable up front, and then I'll prove it with a story: If you build things for the internet and you're still not using AI to do it — you're going to be in trouble. Not "someday." Soon. I didn't believe this either. Then I watched an AI do two days of my work in 40 minutes while I lay in bed scrolling reels. Let me explain. The extension that humbled me I build a little Chrome extension called Intro Skipper . Exactly what it sounds like — it auto-skips the intros on NetSourav Dutta
- 05Supplier Invoice Extraction: Prompt Routing, Small-Model-First Fallback, and Batch RunsA supplier invoice that lands in a healthtech billing app is not a chat transcript; it becomes a row somebody eventually gets paid from, so the operational constraint that decides this design is that one malformed extraction costs more to unwind than the entire LLM API bill it saved. Use the small, cheap model for the first pass, let a JSON Schema validator — not a difficulty classifier — decide when to escalate to a large model, and push everything outside a user's request path through batch przanesterling7589
- 06Lab Notes: Fixing Gold Tick Sequence Gaps for Live Market API StreamsIntro As instructors leading cloud-based quantitative coding labs, we’ve seen a consistent pain point among students building precious metals data pipelines: broken, discontinuous Tick sequence IDs over WebSocket connections. These gaps quietly corrupt backtesting outputs if unaddressed. When you’re only drawing simple price charts for beginner coursework, missing Tick records are almost impossible to spot. But once you move to high-frequency candlestick aggregation, volatility factor analysis,James Tao
- 07How AI Agents Actually Work Under the Hood: Tools, Memory, the LoopA practical look at the runtime of an AI agent — what actually happens between the prompt and the finished task. A few months ago, a CTO at a fintech company asked me why his agent kept failing. Not what it was failing at — he knew that. He wanted to know how the thing worked, in enough detail that he could see where the money was leaking. I opened a terminal and showed him one run: the model emitted a tool call, our runtime executed it, the result went back into the context, the model emitted aGulshan Yadav
- 08When maintenance ends with an error, the plugin update badge disappears — designing a backend marker and frontend count syncThe WordPress maintenance tool shows a badge on each site card when there are pending plugin updates. Under normal operation, when maintenance completes successfully, the badge clears until the next dashboard scan picks up fresh data. That's correct behavior. But a report came in: when maintenance ends with a warning or an SSH error partway through, the badge disappears even if plugins were left unupdated. "If the update didn't finish, I need to know — but the badge is telling me there's nothingSusumu Takahashi
- 09My type of #FractionalCTOLet's begin this with, what is a #FractionalCTO? A Fractional CTO is an experienced, executive-level technology leader who provides strategic guidance, engineering team mentorship, and architecture oversight on a part-time or contract basis. This role allows early-stage startups and growing companies to access high-level technical expertise without the significant financial commitment of a full-time executive salary and benefits. It is an ideal solution for non-technical founders, scaling busineAndrei Merlescu
- 10How We Killed Alert Fatigue Without Going BlindThe Problem Was Noise, Not Negligence We had dozens of cron jobs. Each one was configured to email on every run, success or failure. On a quiet night that meant a wall of green. On a bad night it meant that same wall of green, except somewhere buried in it was a red that nobody caught until a client noticed. That is not a discipline problem. That is a systems design problem. Alert fatigue is a reliability bug, not a personality flaw, and treating it like the former means you keep blaming peopleSavage Solutions
- 11Around image 87 the batch stopped looking like one storeAround image 87 the batch stopped looking like one store Getting one good image out of a model is not hard. Batches are where it falls apart. Last time I filled a category, the first twenty were fine. Somewhere in the eighties I laid the finished set out together and the drift was obvious. The colour had shifted slightly, the margins were inconsistent, the subject size wandered. Each image passed on its own. Side by side they looked assembled by different people. It took a few days to work out wboyuan tuo
- 12Horizontal Scaling: Solving One Problem, Creating AnotherWhen learning system design, we are almost always fed the exact same doctrine: start with one API + one Database, then as traffic increases, add a Load Balancer, Redis, a Separate Database Server, and eventually Read Replicas. The problem is that this standard pattern is built on a single assumption: every user must crowd into the same shared database. However, if your application's data characteristics allow it to be segregated per user from day one, blindly following this pattern becomes a comynwd