标签：#RAM

submitted by /u/namanyayg [link] [留言]

submitted by /u/the_redwood_wanderer [link] [留言]

submitted by /u/BigAd4703 [link] [留言]

submitted by /u/RelevantEmergency707 [link] [留言]

submitted by /u/badcryptobitch [link] [留言]

📓 Stop Memorizing English — I Built an AI App That Actually Works ⚡ The Hook You try to learn English. You memorize words. And then… you forget them. 🧠 The Real Problem Most people learn English the wrong way: memorizing random word lists switching between apps and dictionaries learning without context That’s why nothing sticks. 🚀 The Idea What if learning English felt like this: 👉 You read something interesting 👉 You click a word you don’t know 👉 You instantly understand it No interruptions. No friction. ✨ Introducing: English Notebook A modern AI-powered app where you learn English by interacting with real content . generate stories click unknown words build vocabulary automatically 🤖 Generate Stories Based on Your Level This is one of the most powerful features. You choose your level: A1 → Beginner A2 B1 B2 C1 C2 → Advanced And the app generates a custom story just for you . 🖼️ Story Generator 📖 Learn by Clicking Words No more: copy-pasting opening dictionary tabs losing focus Just click any word: definition translation (your language 🌍) example sentences 🖼️ Word Interaction 📚 Smart Vocabulary Notebook Every word you click: 👉 automatically saved 👉 turned into a flashcard You can: review anytime mark as mastered ✅ 🖼️ Vocabulary Notebook 📊 Track Your Progress (Game Changer) This is where things get serious. You don’t just learn — you measure your growth . Dashboard shows: total words learned active vs mastered words daily streak 14-day activity trend 🖼️ Dashboard What gets measured gets improved. 🕘 Nothing Gets Lost (History System) Every story you generate is saved. You can: revisit old stories continue reading anytime track your learning journey 🖼️ History 🔊 Learn with Audio listen to stories follow highlighted words improve pronunciation naturally 🌍 Multi-Language Support You can choose your translation language: Persian 🇮🇷 Arabic Spanish Hindi and more 🎯 Why This App Is Different Most apps: ❌ force memorization ❌ feel like school ❌ break your focus English Note

A follow-up to Part 1: the self-recall thesis — the series runs through Part 6 . Code: RE-call — everything below is measured and reproducible ( make eval ), full study in docs/ENTAILMENT_SUPERSESSION_STUDY.md . I published a thesis post about agent memory and got five comments that were better than the post. Two of them didn't just critique the design — they described, precisely, why it would fail and what would fix it. So I did the only reasonable thing: I turned both into experiments, ran them on the same eval harness the series is built on, and shipped what survived. That's RE-call v0.3 , and this post is the receipt. I want to be explicit about why I'm writing it this way. The point of publishing this series was never broadcast — it was error-correction . A design you keep in a drawer accumulates conviction; a design you publish accumulates objections , and objections are the cheapest high-quality signal you will ever get. The comment section of Part 1 did more for this codebase than any week of solo iteration. This post exists to pay that back with the thing commenters almost never receive: evidence that someone listened, measured, and changed the code. Comment 1: "A similarity score is not a confidence score" Vinicius Pereira put it in one line I've been quoting since: Proximity is a candidate; entailment is the evidence. His argument: the near-misses that hurt most are high-similarity and wrong — memos semantically adjacent to the query that don't answer it. A threshold-based gap_warning (Part 3, Part 5) waves them straight through by construction , because their similarity clears any threshold you could calibrate. The abstention signal cannot be the retriever's own score. You need a separate check that the retrieved memo actually entails an answer. He was right, and measurably so. I built a held-out challenge set of 10 near-miss queries — each names a strongly on-topic memo that does not contain the asked-for fact ("how much did the cache reduce memory usag

Hot take 👀 The hardest part of React isn't hooks. It's knowing how to structure an app so it stays maintainable as it grows. Clean architecture beats clever code every time. What's been the biggest challenge in your React projects?

submitted by /u/davidalayachew [link] [留言]

You have a Java application, and now you need it to do something Java is awkward at. Maybe you want to let users script your app without recompiling it. Maybe you want to change a piece of business logic without a full redeploy. Maybe you just want to run a quick, throwaway script and not stand up a whole build. Java is a phenomenal language and runtime, but these are the edges where it starts to feel heavy. That is exactly the space Aussom is built for. I started using Java almost 20 years ago and have loved every bit of it. I'm proud of all the recent momentum in the Java space and I hope it continues. Java does so much so well. But every great tool has an edge where it stops being the right one, and reaching for another language there isn't a betrayal of Java. It's how the best ecosystems work. A useful comparison: C and Python Look at C. C is clearly important. Even after a lifetime of use it's still the foundation for new projects today, and new competitors such as Rust haven't been able to meaningfully displace it. C is fast and powerful on its own, but it isn't great for simple tasks. It's poor for throwaway code and quick scripts, it isn't very portable, and it hands you plenty of footguns. It's also a poor choice when you want to offer a scripting interface. Enter Python. Python is everywhere today because the barrier to entry is so low and it's genuinely useful. But Python leans on C. It's written in C, and much of its power comes from existing C libraries, whether they're UI frameworks, AI inference engines, or anything in between. C is efficient but poor at simple dynamic work; Python is dynamic and simple but poor at raw power and efficiency. Neither replaced the other. They endure together because they complement each other's weaknesses. That is the case I make for Aussom. Aussom is to Java as Python is to C. It doesn't compete with Java, it complements it. What makes Aussom different from other JVM languages This is where Aussom parts ways with most o

submitted by /u/we_are_mammals [link] [留言]

I remember being at an advisory board of big tech in 2023, close to the starting point of code generation with LLMs. Like everyone else, I was amazed. People were copying and pasting generated code, experimenting with prompts, and imagining a future where AI could become every developer's pair programmer. I was excited too. But I remember having a completely different question. Not: -"Will AI write code?" Instead, I kept wondering: -Why are we still writing code at all? Not because I think programming is going away. Not because programmers won't be needed.And certainly not because programming languages are somehow "wrong." It was a much simpler question. Programming languages have always existed to bridge a gap between humans and machines. Humans think in goals, ideas, and intentions. Machines execute deterministic operations. Programming languages became the interface between those two worlds. For decades, we've improved that interface. Assembly became higher level languages. Higher level languages became frameworks. Frameworks became libraries and abstractions that let us think less about implementation and more about solving problems. Then large language models arrived. Suddenly, we could describe what we wanted in plain language. But instead of questioning the interface itself, we mostly asked AI to become incredibly good at translating our intentions into programming languages. Today, our workflow looks something like this: Human intent - LLM - Programming language - Compiler / Runtime -Machine execution And every time I look at this pipeline, I find myself asking the same question I had back then. -Are we optimizing the wrong layer? Maybe the question isn't "Can AI write code?" Maybe the question is: -Do programming languages still need to be the primary interface between humans and computers? This isn't an entirely new idea.Researchers have explored concepts like Intentional Programming, where software is represented by its intent rather than by a specific pr

Okay so. We need to talk about classes. If you've been following along with this series, you're...

I host a Postgres podcast, and I recently recorded a conversation with Panos Antonopoulos, a Distinguished Engineer at Microsoft who spent 13 years working on SQL Server before moving onto Postgres and HorizonDB. Panos told me that at a high level, Postgres felt very familiar as he started to work on it, that the concepts are very similar. Transactions, storage, & more—the fundamentals transfer surprisingly well. We also covered: The cleanliness of the Postgres codebase. How LLMs are making it easier to digest years of Postgres design discussions that are publicly available on the mailing lists. Why Postgres has become the default answer for so many workloads, and why more people seem to be asking, "Why not Postgres?" Shared-storage architectures and some of the work he's doing in Azure HorizonDB. One quote that stuck with me: "That was a shocking experience for me. I could understand new areas in Postgres much faster than I could for SQL." For people who have worked across multiple database systems (Oracle, SQL Server, MySQL, Postgres, etc.), I'm curious whether you've had a similar experience—or a completely different one. Podcast/transcript here if anyone is interested: https://talkingpostgres.com/episodes/working-on-postgres-after-13-years-on-sql-server-with-panagiotis-antonopoulos submitted by /u/clairegiordano [link] [留言]

submitted by /u/andreiross [link] [留言]

What a One-Line CSS Fix Taught Me About Code Review (My First Firefox Patch Feedback Loop) When I started contributing to Firefox through Outreachy, I expected the hard part to be writing code. What actually taught me the most was a two-line CSS fix that a reviewer sent back — not because it was wrong, but because it wasn't quite right yet. Here's what happened with Bug 2026574 . The Bug In Firefox's Split View about:opentabs page, long strings in the search field were overflowing outside their container instead of wrapping. Visually, it broke the layout — text just spilled past its boundary instead of staying contained. My job: make the text wrap properly, without breaking anything else on the page. My First Attempt I went into moz-card.css and targeted the heading element directly: .moz-card-heading { overflow-wrap : break-word ; min-width : 0 ; } This worked, technically. The text wrapped. Locally, it looked fixed. I submitted the patch for review, feeling fairly confident — it was a small, contained change. The Feedback My reviewer, Tim Giles, came back with a better approach. Instead of targeting the heading specifically with two properties, he suggested applying a single, more precise rule to the parent .moz-card element: .moz-card { overflow-wrap : anywhere ; } overflow-wrap: anywhere is more aggressive than break-word — it allows breaks at any point when needed to prevent overflow, not just at existing break opportunities. And by moving it to .moz-card instead of just the heading, the fix covered the component more robustly instead of patching one specific element. It was a smaller diff. It solved the actual problem instead of the symptom I'd focused on. And it followed patterns already used elsewhere in the codebase. What I Actually Learned My first instinct, seeing feedback on a patch I thought was "done," was a small jolt of did I get this wrong? But that's not what was happening. Getting feedback on a first pass isn't failure — it's the normal shape of h

Seed7 is a GPL licensed open source programming language. It is given away for free and nobody from the development team gets any money from it. submitted by /u/ThomasMertes [link] [留言]

Today I accidentally became the maintainer of software that was already almost three decades old: reviving a 1990s Java utility to keep the last PAD submitter alive in 2026. I was looking for a way to submit my AI app RiverScript to old desktop software directories and ended up digging through the long-forgotten world of PAD files. There was one problem. The only batch submission tool I could find was a Java application that first appeared in the late 1990s. The last release was in 2017. It was written by Roedy Green of Canadian Mind Products — a software developer who passed away in 2023. He spent decades writing and freely distributing Java utilities, and maintaining the widely-read Java Glossary . Roedy Green also wrote How To Write Unmaintainable Code — a famous satirical guide about writing code nobody can maintain. So, Roedy, today the code you wrote almost three decades ago was maintained. The tool still did exactly what it was supposed to do. Thank you. It just had absolutely no idea the modern web existed. It happily produced URLs like http://https://riverscript.com instead of https://riverscript.com , disabled SNI globally (which was probably a perfectly reasonable workaround at some point), and couldn't cope with the fact that almost every website now redirects HTTP to HTTPS. So I dug through the legacy Java code, fixed the compatibility issues, and got it working again. I used it to submit my app to several software directories, then published the revived version on GitHub so anyone who still needs it can use it too. Maybe nobody will ever need it again. Maybe someone will. Either way, I'm happy this old thing works again. So today, the code of the man who wrote "How To Write Unmaintainable Code" is still being maintained even after he was gone. P.S. The public repository for Mini PAD Submitter 26.3 Revived — 2026 Community Fix is available and open to everyone. submitted by /u/Odd-Flamingo-6211 [link] [留言]

submitted by /u/mttd [link] [留言]

After the browser transfers a file, the server may still scan, transcode, extract metadata, or generate previews. The interface needs status updates, but the most fashionable real-time transport is not automatically the most reliable choice for an event guest on a mobile browser. Start with the update contract Define states and transitions before choosing transport: accepted -> queued -> processing -> ready accepted -> rejected processing -> processing_error Every status response should include a monotonically increasing version or timestamp. The client can ignore events older than the state it already knows. Polling is a strong baseline HTTP polling works through proxies, resumes naturally after a page wake, and is easy to cache and rate-limit. Use adaptive intervals: one second just after acceptance, then back off to several seconds when processing takes longer. const delay = Math . min ( 8000 , 1000 * 2 ** slowChecks ); Add jitter when many guests finish at the same time. Stop when the state is terminal, the page is gone, or a server-provided retry time says to wait longer. SSE fits one-way progress Server-Sent Events are attractive when the server only pushes status. The browser reconnects with a last-event ID, and the wire format is simple. But mobile networks and some intermediaries silently kill idle connections. Send occasional heartbeats and treat reconnection as normal. The reconnect handler must fetch current state because events may have been missed beyond the server replay window. Do not keep one SSE stream per file. Subscribe by guest session or album and filter authorized upload IDs on the server. WebSockets add more responsibility WebSockets make sense when the client also sends frequent commands over the same channel or when a host moderation console needs many rapid updates. For a guest waiting on two files, they add connection authentication, heartbeat, reconnect, replay, and load-balancer complexity without much user benefit. Never rely on the so