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Gemma 4-26B on a ₹40,000 Laptop: The Best Local AI Model for Indian Companies in 2026 Google’s Gemma 4-26B is a 26-billion parameter open model that runs on a consumer laptop with 16GB RAM. For Indian companies — from 3-person startups to 50-seat SMEs — that is a game-changer. You do not need cloud credits. You do not need an API subscription. You do not need to send your internal data to a third-party server. You need a laptop, a quantized model, and 30 minutes of setup. ...

Answer three questions — scope of change , how type-heavy your codebase is , and who runs it — and the tool choice collapses to two. Solo TS-heavy repo: VS Code + ts-morph . Small team, one repo: WebStorm + jscodeshift . Multi-repo org: ast-grep + Sourcegraph Batch Changes . You can skip Babel, Comby, OpenRewrite/Moderne, and ReSharper unless you're in their specific ecosystem. Tool sprawl is a symptom: if you're debating 10 tools, the real gap is that nobody's defined what's ...

Ask any AI coding agent to write a Stripe webhook handler and it will produce something reasonable in thirty seconds. Ask it to verify that handler actually works and it hits a wall. The problem isn't intelligence. It's plumbing. To debug a webhook you need to receive a real event on a public URL, check its signature, look at what actually arrived, fix your code, and run the same event again. Every step traditionally involves a human: clicking around a provider dashboard, copying a signing se...

Qwen2.5 Runs on a ₹25,000 Android Phone — The Multilingual AI Model Every Indian Company Needs Alibaba’s Qwen2.5 is a 7-billion parameter open model that runs on Android phones with 6GB RAM via Termux. For Indian traders who think in Hinglish and companies that serve multilingual customers, that matters. English-only models miss context. Cloud APIs add latency and cost. Qwen2.5 runs locally, understands Hindi + English + 20+ Indian languages, and costs nothing after your phone bill. ...

Smash Stories: Slaying a Silent RCE via Insecure Deserialization The Bug I Smashed During an authorized security assessment of a custom Python/Flask microservice, I discovered a chaotic, high-severity vulnerability masquerading as a harmless caching mechanism. The application was storing user session preferences in a base64-encoded cookie. The problem? The backend was deserializing this cookie using Python's inherently insecure pickle library without any integrity checks. This allowed arbit...

Introduction to Logging in Go Logging in a Go web server backend is a critical mechanism for capturing and recording events such as errors, debug information, and operational data. It serves as the backbone for troubleshooting, monitoring, and compliance in production environments. However, developers, especially those new to Go, often face a fundamental decision: should log statements be scattered throughout the codebase or centralized in a unified mechanism? This choice directly impacts ...

Lantea.ai 深度解析：微信链接审核机制的“降维打击” 在数字生态的博弈中，微信的链接审核并非简单的“关键词过滤”，而是一套基于 行为特征、社会工程学与实时流量拓扑 的综合防御体系。要理解其运作逻辑，必须跳出“内容审查”的肤浅认知，从以下四个维度进行降维拆解。 一、 核心逻辑：从“内容治理”转向“流量拓扑过滤” 微信的审核逻辑并非聚焦于链接内的文字内容，而是将其视为一个 “流量节点” 进行动态评估。 动态信誉评分（Dynamic Reputation Scoring）： 每个域名在微信体系内都有一个隐形的“健康值”。该值由域名注册时间、解析记录历史、SSL证书等级以及 转发链条的跳跃深度 决定。 黑盒行为指纹（Behavioral Fingerprinting）： 系统不依赖于静态爬虫，而是通过模拟端（模拟器/真机集群）对链接进行“沙盒环境”访问。它会记录该页面加载时的重定向次数、是否存在隐藏的劫持脚本、是否包含诱导性 UI 设计（如高仿微信红包界面）。 流量溯源黑名单： 审核机制不仅看链接本...

The leaks that matter usually aren't in production code — they're in the workflow around it. Five common ones: AsyncStorage for tokens , real user data in design mockups , multi-stage AI pipelines , logs and crash reports , and bundled permissions . Two greps that find real bugs today: AsyncStorage.setItem near token , and console.log(user / console.log(token / console.log(prompt . Model consent by purpose , not by OS permission. Camera consent is not AI-summarization consent...

The High Stakes of the Waiting List A phone rings at the scheduling desk of a major metropolitan cardiac center. On the other end of the line is a patient who has been experiencing worsening chest pain, waiting for a coronary artery bypass graft. The scheduler, juggling three other holding lines while trying to coordinate with the intensive care unit coordinator and the lead surgeon, promises to call back once a slot opens up. This scene plays out thousands of times a day across the healthcar...

"No-code" sounds effortless. Configure your app in a browser, hit publish, done. And that is exactly how it should feel, for one app, seen from the outside. Keeping thousands of no-code apps alive and published, for years, is another job entirely. This post opens the machine room: hosting, push delivery, store submissions, and the maintenance treadmill running underneath. Quick context: GoodBarber is a no-code app builder running since 2011. Customers configure an app in a web back office; th...

Self-healing AI scrapers sound like the obvious next step in web data collection. Instead of manually updating selectors every time a website changes, the scraper can inspect the page, understand the new structure, adjust its extraction path, and continue collecting data. For developers, data teams, and automation builders, that promise is attractive because traditional scraper maintenance is often repetitive and time-consuming. But self-healing does not mean unbreakable. It can reduce some o...

Hi, I'm Boris a PHP developer whose deepest experience is TYPO3, with Laravel and Filament being a newer, growing focus. A lot of that work across both has been building admin tooling and integrations that quietly need to just work: payments, webhooks, notifications. This post is about one small piece of that: signing webhook payloads correctly, and a mistake that's easy to make even once you already know HMAC signing in theory. The problem If your app sends webhooks to another s...

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Article URL: https://github.com/janestreet/incremental Comments URL: https://news.ycombinator.com/item?id=48987822 Points: 138 # Comments: 21

Article URL: https://www.instructables.com/A-Koi-Pond-Mosaic-Made-From-10-Pounds-of-3D-Printe/ Comments URL: https://news.ycombinator.com/item?id=48987831 Points: 28 # Comments: 21

Article URL: https://www.armaangomes.com/blogs/doom/ Comments URL: https://news.ycombinator.com/item?id=48987846 Points: 49 # Comments: 9

Article URL: https://asia.nikkei.com/business/technology/five-us-tech-giants-hidden-debts-soar-to-1.65tn-on-opaque-ai-funding Comments URL: https://news.ycombinator.com/item?id=48987863 Points: 224 # Comments: 101

Hi, I designed and developed a spatial index that maps museum artefacts as connecting arcs/hyperlinks from their origin site to institutional location/sources. The Index specifically looks at western/euro-american institutions and maps their collection categorised by them under Islamic art, Asian/African art, ethnological collections, Middle East, South America etc. Started as my MA thesis in 2022, kept building since, mostly solo with a little funding. Fully open source, self-hosted, AGPL-3.0, ...

Article URL: https://fzakaria.com/2026/07/20/linux-kernel-will-support-origin-sort-of Comments URL: https://news.ycombinator.com/item?id=48988793 Points: 8 # Comments: 6

The final approval settles one case, but it doesn't resolve the broader issue of using copyrighted works to train AI models.

FROST-SOP V6.1.0 工程实践：从初始化流水线看「零门槛上手」 作者：神通说 日期：2026-07-21 主题：周二·SOP工程 | V6.1.0 新特性深度解析 开篇：一个让所有开发者头疼的问题 想象这个场景： 你刚克隆了一个开源项目，兴冲冲地跑起来，结果： ModuleNotFoundError: No module named xxx ImportError: DLL load failed OSError: [WinError 2] 系统找不到指定的文件 你开始疯狂搜索、提问、等回复。一小时过去了，项目还没跑起来。 这是开源项目最大的痛点之一：「最后一公里」问题。 今天，我们来聊聊 FROST-SOP V6.1.0 是如何解决这个问题的。 V6.1.0 核心特性：初始化流水线 V6.1.0 版本最核心的更新，是一个 全自动初始化流水线（Initialization Pipeline） 。 ...

I’ve seen enough postmortems to know that a large percentage of them are essentially polite fiction. We sit in a meeting, everyone is exhausted from the outage, and we agree on a narrative. We write down that 'the database connection pool was exhausted' or 'a bad deploy caused an error spike.' Then we add an action item like 'add more monitoring' or 'improve testing,' and we move on to the next feature request. Three months later, the exact same thing happens. The same service, the same er...

If you have written any optimization code, you have met linear programming even if nobody called it that. "Maximize output without blowing the resource budget" is an LP problem, and the classic algorithm that solves it is the simplex method. It is worth understanding not because you will hand-code it (you'll usually call a solver), but because knowing how it moves makes you far better at modeling problems for it. Here is the algorithm stripped down to its logic. The problem shape Every ...

Picking the right deep learning library shapes almost everything about a computer vision project, from how fast you can prototype a model to how painful it is to ship one into production. Two frameworks dominate this decision today: PyTorch and TensorFlow. Neither has definitively won, but the split between them has become clearer than it was five years ago, and understanding that split is the fastest way to stop guessing and start building. Why the Choice of Framework Still Matter...

I run a scheduled agent that publishes to DEV.to twice a day. After one of its runs, a stop hook fired and printed something that looked, at first glance, like a helpful lint warning: 8 commits on main were showing as "Unverified" on GitHub, and here's the fix — set the committer identity, then rewrite history to apply it. The exact prescription was: git config user.email noreply@anthropic.com git config user.name Claude git commit --amend --reset-author # for the tip commit ...

Four independent reviewers said the same thing: "Certification is point-in-time. Attacks are runtime." — @correctover (CrewAI), @wrencalloway (dev.to), @mads_hansen (dev.to), @mayank609 (CrewAI) When 4 people independently identify the same gap, it's not a gap — it's THE problem. So I built L3. The gap My 8-layer Sentinel pipeline audits skills at import time: L1.5-L1.8: static analysis (metadata, semgrep, secrets, malware patterns, malware families) L2: g...

Hey everyone! 👋 First of all, thank you so much for all the support, feedback, and feature suggestions since the Product Hunt launch. Every comment has been incredibly valuable, and I've already started implementing some of your ideas. Today I'm excited to share a new update to Rizzzler ! 🌙 ✨ What's New? 🎨 2 Brand-New Themes I've added two new themes , giving you even more ways to personalize your profile and match your own style. Whether you prefer someth...

Every time this comes up, someone credits the same setup: Athena on Iceberg is where "the code is the spec" — where you open Git and read the whole system, catalog to transforms to schema, without logging into anything. In my experience they're not wrong. What I want to argue is that they're right for mostly the wrong reason. The reason people reach for is the engine — serverless, open format, nothing to provision. But the thing that actually keeps code as the spec, when it does, is someth...