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stoneChat is a locally hosted LLM web chat client built specifically for Windows XP-era machines and Internet Explorer 6. The frontend remains compatible with IE6. A small PHP server handles the chat requests, while stunnel provides HTTPS support for modern API endpoints. Models are defined in an INI file. Each model can have its own API endpoint, API key, model ID, streaming setting, token limit, and timeout. OpenAI-compatible APIs are supported. The same configuration file also manages users, model access, language preferences, and keyboard behavior. stoneChat runs on Windows with PHP 5.4 or newer and starts through RUN.cmd. GitHub: https://github.com/Water-Run/stoneChat License: WTFPL

When building scalable systems, we often need a collection of classes to expose a fixed, read-only configuration value. Whether it is a unique API_ENDPOINT, a DATABASE_TABLE name, or a specific PERMISSIONS_MASK, handling constants across a series of classes looks simple on day one but can quickly turn into an architectural nightmare. Setting the Foundation: How to Make It In modern object-oriented programming, the standard way to declare a constant on a class is by leveraging the static readonly modifiers. This ensures the attribute belongs to the class itself, rather than an instance, and cannot be mutated at runtime. TypeScript class BillingService { static readonly SERVICE_TYPE = "BILLING"; } class InventoryService { static readonly SERVICE_TYPE = "INVENTORY"; } This works perfectly when you know exactly which class you are dealing with at compile time. You simply call BillingService.SERVICE_TYPE and move on. The Architectural Breakdown: What Will Be the Problems The clean code facade breaks the moment you attempt to handle these classes dynamically. In production environments, you rarely hardcode class names; instead, you process them as an array or a series of registry keys. Loss of Type Safety: If you pass a series of these classes into a processing function, standard type systems will treat them as generic constructor functions, wiping out access to the static property unless you resort to unsafe type casting. Polymorphism Failure: Subclasses do not inherently enforce or override static properties cleanly through standard interfaces. You cannot enforce a static readonly property on an interface, meaning a developer could easily forget to define the constant on a new service class, causing silent runtime failures. Instance vs. Class Metadata Confusion: If your architecture receives an instance of the class rather than the class definition itself, accessing the static attribute requires jumping through hoops like instance.constructor.SERVICE_TYPE, which breaks

In my previous post about a cost budget advisor , I built a mechanism that checks how much quota is left before it runs anything. This time I want to take that idea one step further: instead of cycling a single Codex through jobs one after another, run several of them at the same time as a swarm. I'll walk through the actual code for a three-layer protocol where workers declared in plan.json are expanded by orchestrate-worktrees.js into a tmux session plus git worktrees, so each Codex runs in parallel without interfering with the others. The problem: running Codex serially on the same branch When you run Codex jobs one after another on a single repository, you hit issues like: A commit from the previous job changes the preconditions for the next one Task B keeps waiting until Task A finishes When a conflict happens, the "which change is correct" decision bounces back to a human Separating branches with git worktree reduces the conflict risk to zero. Combining that with tmux to launch everything in parallel is the design for this post. The big picture: a three-layer protocol plan.json ← declaration layer (what goes to which worker) ↓ orchestrate-worktrees.js ← orchestrator layer (creates worktrees, launches tmux) ↓ orchestrate-codex-worker.sh ← worker layer (runs Codex, writes artifacts) The orchestrator doesn't know about the workers, and the workers don't know about each other. Artifacts are consolidated into three files under .orchestration/{session}/{worker_slug}/ . File Role task.md Work instructions for the worker (generated by the orchestrator) status.md State: not started → running → completed / failed handoff.md Codex output + git status (written by the worker) Declaring the plan in plan.json { "sessionName" : "refactor-sprint" , "repoRoot" : "~/my-project" , "worktreeRoot" : "~/worktrees" , "coordinationRoot" : "~/my-project/.orchestration" , "baseRef" : "HEAD" , "replaceExisting" : true , "launcherCommand" : "bash ~/.claude/scripts/orchestrate-codex-worker

How I Built a Block Puzzle Game with React Native and Expo A few weeks ago, I launched my first mobile game — a block puzzle called Blockbeam. It's an 8x8 grid where you drag colorful blocks, fill rows and columns, and chase high scores. Simple concept, but building it taught me a lot about React Native's capabilities beyond typical CRUD apps. Here's what I learned. Why React Native for Games? Most mobile games are built with Unity or native code. But for a 2D puzzle game, React Native is surprisingly capable. The game doesn't need 60fps 3D rendering — it needs gesture handling, state management, and smooth animations. React Native handles all three well. The key stack: Expo SDK 54 — managed workflow, over-the-air updates, zero native config react-native-reanimated — 60fps drag animations react-native-gesture-handler — PanResponder for drag-and-drop react-native-svg — block rendering AsyncStorage — game state persistence The Puzzle Engine The core of any block puzzle is the board state. I used a flat 64-element array for the 8x8 grid: const BOARD = 8 ; const CELLS = BOARD * BOARD ; // 64 type Board = number []; // 0 = empty, 1-7 = block colors Piece placement is straightforward: check if all target cells are empty, fill them, then scan for complete rows and columns to clear. The interesting part was the "greedy solver" I built for the auto-play bot. It tries every piece in every position and picks the move that clears the most lines: for ( const piece of tray ) { for ( let r = 0 ; r <= BOARD - piece . h ; r ++ ) { for ( let c = 0 ; c <= BOARD - piece . w ; c ++ ) { if ( ! canPlace ( board , piece , r , c )) continue ; const score = simulateClear ( board , piece , r , c ); if ( score > bestScore ) { /* pick this move */ } } } } Drag and Drop with PanResponder The trickiest part was the drag mechanic. Each tray piece has a PanResponder that tracks touch position and renders a floating ghost. On release, it calculates the nearest cell position: const anchor = { col : M

The trust proxy setting is an important concept in backend development, especially when implementing rate-limiting in our APIs. But deciding its accurate value depends heavily on our deployment topology. When we deploy our application in production, the client may not talk directly to our backend. There may be 1 or more proxies in between who forward the request to the next proxy or the backend server. Those proxies can be Load balancers, API gateways, reverse proxy like nginx or any custom service. So effectively, our request has to do some 'hops' over these proxies to reach backend. When we implement rate limiting in app to prevent the DOS attack, we generally intend this rate limit on the basis of client IP address. And this works fine when client request reaches our backend directly. But when we have multi-hop architecture, the simple setup won't work as expected. Because the most recent IP will be of the proxy and not the client. So all the traffic coming from different users will be considered from the single client(our own proxy) and thus there will be false positives as the rate limiting will trigger much often. In this scenario, we must tell our backend to ignore these extra hops(i.e. to trust our proxies). This is done by specifying trust proxy. If there is 1 proxy between client-server we set trust proxy to 1; if there are 2, or more, we set it accordingly. This will ensure our express app skips(trusts) these IPs, and accurately figures out actual client IP. The originating IP address of client is identified from 'X-Forwarded-For' header by the express app. But setting trust proxy is not that straightforward. The numerical value for trust proxy will not work in every case. If there are different paths from which our request reaches backend, there is a chance that the number of proxies may be different in each path. For example - internal vs external traffic: External(public) traffic: (Client -> Web Application Firewall -> Load balancer -> Reverse Proxy ->

Signed upload sessions expire. Event contribution windows close. Storage reservations are reclaimed. These are normal lifecycle events, but many interfaces reduce all of them to “Upload failed.” A better protocol makes expiration explicit and recoverable where policy allows it. Distinguish three clocks An upload workflow usually has at least three deadlines: the event contribution window; the server-side upload intent expiry; the short-lived storage credential expiry. They should not share one timestamp. The event may accept contributions until midnight while a credential lasts five minutes and an intent can be renewed for an hour. Return the clocks in the session response with server time: { "serverNow" : "2026-07-17T18:00:00Z" , "eventClosesAt" : "2026-07-18T00:00:00Z" , "intentExpiresAt" : "2026-07-17T19:00:00Z" , "credentialExpiresAt" : "2026-07-17T18:05:00Z" } The client can display useful warnings without trusting its own clock for authorization. Model expiration by state A credential expiring during transfer is different from an intent expiring before completion. Use stable reasons: credential_expired -> request renewal intent_expired -> reconcile committed parts, then renew or restart event_closed -> stop new work, preserve local recovery guidance Do not automatically restart from byte zero. First ask the control plane which parts were committed and whether the original object key remains valid. Renew narrowly A renewal endpoint should accept the upload ID and prove continuity with the guest session. It rechecks event state, file policy, rate limits, and committed size. The response returns a new credential for the same object. Do not let the browser extend an intent indefinitely. Define a maximum session age and a bounded number of renewals. Long uploads may receive a larger initial policy based on file size and observed throughput. Handle the closing boundary fairly Decide what happens to an upload already transferring when the event window closes. Reasona

Event uploads fail differently from normal office uploads. A wedding guest may move between venue Wi-Fi and mobile data, lock the phone while a video is transferring, or close the browser as soon as the progress bar reaches 100%. Hundreds of devices can share one access point, and users rarely wait around to diagnose an error. The usual POST request plus optimistic success toast is not enough. A reliable browser flow needs a small protocol that distinguishes local preparation, network transfer, server acceptance, media processing, and final availability. This article describes a platform-neutral design for that protocol. The five states users actually experience Model each file as a durable state machine: selected -> preparing -> transferring -> accepted -> processing -> ready Add terminal or recoverable branches: preparing -> rejected_local transferring -> paused | retryable_error | expired accepted -> processing_error processing -> ready | processing_error The key distinction is between transferring and accepted . The browser may have sent every byte while the server has not yet committed the upload. Showing “done” at that boundary creates the most frustrating failure: the guest deletes the original, but the organizer never receives it. Give every file a client-generated identity Create an upload ID before the first network request. A UUID is sufficient when combined with the event identifier: const uploadId = crypto . randomUUID (); const uploadIntent = { uploadId , eventId , name : file . name , size : file . size , type : file . type , lastModified : file . lastModified , }; Send that identity when creating the server-side upload session. If the browser retries after a timeout, the server returns the existing session instead of creating a duplicate. This is idempotency at the workflow level. A guest can tap “retry” without having to understand whether the first request reached the server. Separate the control plane from file bytes Use a small JSON API for sessi

Designed for year-round comfort, the Dyson Hot+Cool HF1 combines quiet operation and simple controls with Dyson's signature bladeless design.

Obsidian is working on a new Fallout game, while Fallout 3 and New Vegas remasters are on the way.

Ken Thompson — คนที่เขียนระบบปฏิบัติการใน 3 สัปดาห์ ปี 1969 เคน ทอมป์สัน อายุ 26 เป็นวิศวกรที่ Bell Labs เขากับทีมเพิ่งเสียโปรเจกต์ Multics ซึ่งเป็นระบบปฏิบัติการที่ซับซ้อนเกินไปจนถูกยกเลิก Bell Labs ถอนตัว ทีมแตก โปรเจกต์ตาย เคนมีเวลาเหลือเฟือ และมี PDP-7 ซึ่งเป็นคอมพิวเตอร์เก่าที่แทบไม่มีใครใช้ ใน 3 สัปดาห์ เขาเขียน Unix kernel, shell, editor, และ assembler ขึ้นมาบน PDP-7 — ทั้งหมดเป็น assembly — ภาษา B ยังไม่เกิดตอนนั้น B ถูกสร้างขึ้นหลังจากนั้น — เพื่อใช้เขียน utility ต่าง ๆ แทน assembly — และนี่คือจุดเริ่มต้นของสายภาษา B → C → Go ภาษา B — เกิดหลัง Unix เวอร์ชันแรก Unix เวอร์ชันแรกสุด — สิงหาคม 1969 — เป็น assembly ล้วน หลังจากนั้นไม่นาน Ken ก็เริ่มสร้าง B — โดยตัดทอนมาจาก BCPL — เพื่อให้มีภาษาระดับสูงไว้เขียน tools โดยไม่ต้องใช้ assembly ทั้งหมด B มาจาก BCPL (Basic Combined Programming Language) ซึ่งพัฒนาโดย Martin Richards ที่ Cambridge ในปี 1966 BCPL เป็นภาษาที่ไม่มี type — ทุกอย่างคือ word — และออกแบบมาให้ compiler พกพาง่าย Ken เอา BCPL มาตัดทุกอย่างที่ไม่จำเป็นออก — จนเหลือภาษาเล็กมากที่ทำงานได้บน PDP-7 ซึ่งมี RAM แค่ 4K words PDP-7 Assembly → Unix v1 (1969, 3 สัปดาห์) ↓ BCPL (Richards, 1966) ↓ ตัด feature, ลดขนาด B (Thompson, 1969-1970) ↓ ใช้ rewrite Unix utilities (ไม่ใช่ kernel) ↓ ↓ เพิ่ม type system, struct, portability C (Ritchie, 1972) ↓ Unix v4 rewrite ด้วย C (1973) B ไม่มี type system ไม่มีโครงสร้างข้อมูล มีแค่ word — เหมือนกับว่าเป็น BCPL เวอร์ชัน minimal B ถูกใช้เขียน shell, utilities, และ tools ต่าง ๆ ของ Unix — แต่ kernel ยังเป็น assembly อยู่ จนกระทั่ง Dennis Ritchie สร้าง C ขึ้นมาในปี 1972 ทำไมต้อง B PDP-7 มี assembly แต่นั่นไม่ใช่เหตุผลที่ดีพอที่จะใช้มัน Ken ไม่เชื่อในการเขียน OS ด้วย assembly ทั้งระบบ — assembly เร็วแต่เขียนช้า แก้ยาก พกพาไม่ได้ การใช้ภาษาระดับสูง (แม้จะสูงนิดเดียวแบบ B) ทำให้: เขียน shell, utilities เร็วขึ้นมาก แก้ไขง่าย — ไม่ต้องเขียนใหม่เวลาย้ายเครื่อง ใช้คนน้อยลง — Unix version แรกเขียนโดย 2 คน จาก B → C → Unix → ทุกอย่าง เมื่อทีมได้ PDP-11 ซึ่งเป็นเครื่องที่ใหญ่กว่า — B เริ่มมีปัญหา PDP-11 มี byte-addressing แต่ B ออกแบ

The recall comes as the top automotive safety regulator in the U.S. has warned AV companies about their vehicles interfering with first responders.

GIT AND GITHUB Git is a distributed version control tool that track changes into files or code and we can say it works offline. A version control is system used to track and manage changes to a remote file in git. Git Bash is born again shell or basically a command prompt window which emulates UNIX and LINUX environments. Git hub is a website that stores your Git repositories in the cloud so we can say it exist online.It stores your project's version history online and adds collaboration tools like pull requests, issue tracking, and code review." _A repository _in GitHub is similar to a folder in your local machine so any changes are tracked. How to create a repository in GitHub do a simple README.md(markdown) then commit the file and write a massage inside to describe the changes done,then we will need to download a visual code eg VScode where you are able to access the terminals. Git is used to push changes** to git hub or pull a repo from GitHub** There are 3 states that every files lives in; Working Directory -You have made changes but git has not recorded them yet.(it's still on our machine) Staging Area -You have told Git about the changes. Not saved yet. git add filename thus we git add Repository (.git)-Changes are permanently saved in history. git commit -m "message" * Basic Commands/key terms used * git config allows git to know who you are by using your username and user email e.g. your GitHub account name and email address this is an important info when you want to commit changes as it will tell you who made the changes there are different levels but we will use global Global- applies to all repositories for the current user > Syntax: git config --global user.name or user.email. - mkdir (make directory) name – creates a new directories for example: my_project in your machine. - git init this tells Git to start tracking this folder,it initializes git on the folder,the .git folder is where all the history, settings, and saved snapshots lives. It's hidden s

A $400 million chip-backed loan points to the next wave of AI infrastructure deals.

By default, whenever you request a machine learning model, the underlying architecture saves gigabytes of tensor data into a hidden directory located directly inside your home folder ( ~/.cache/huggingface ). Because standard bare metal and virtual cloud configurations typically isolate the root operating system on a smaller, highly optimized boot drive, pouring 140GB+ of raw weights into the home folder guarantees absolute storage exhaustion. Here is the engineering blueprint to fix it cleanly on Linux. The Cache Location Trajectory When attempting to solve this problem, avoid outdated tutorials recommending deprecated parameters like TRANSFORMERS_CACHE . Environment Route Support Status Architecture Impact HF_HOME Active Master Route Safely redirects all models, datasets, and core assets globally. TRANSFORMERS_CACHE Deprecated Warning Fails to capture datasets and will be removed in version 5.0. HUGGINGFACE_HUB_CACHE Deprecated Warning Legacy routing path that creates unnecessary diagnostic warnings. 🛑 The Symlink Security Risk Creating symbolic links (symlinks) to trick the OS into routing files elsewhere is a common anti-pattern. Mapping these links improperly or running your workflow with elevated rights introduces privilege escalation vulnerabilities, compromising container and host security. Step 1: The Permanent Environment Override To change your Hugging Face cache directory on Linux permanently, target an expansive secondary storage array instead by appending a direct master route into your user profile configuration: # Create a dedicated folder inside your secondary storage array sudo mkdir -p /mnt/massive_drive/ai_model_cache sudo chown -R $USER : $USER /mnt/massive_drive/ai_model_cache # Append the master environment variable to your bash profile echo 'export HF_HOME="/mnt/massive_drive/ai_model_cache"' >> ~/.bashrc source ~/.bashrc Step 2: The Python Import Order Mandate If you declare your custom storage location programmatically inside an application

OpenAI published “Why teens deserve access to safe AI” on July 16, 2026, describing its approach around learning, age-appropriate safeguards, parental controls, and work with external experts and organizations. Primary source: OpenAI, “Why teens deserve access to safe AI” . This raises a concrete product-design question for any teen-facing AI experience: after a safeguard intervenes, can the user understand what happened and continue toward a legitimate goal? A generic “I can't help with that” may block harmful output, but it can also strand a learner, conceal an emergency path, or encourage prompt reformulation without increasing safety. Below is a design hypothesis and research plan—not a claim about OpenAI's current interface. Design three outcomes, not one refusal request -> proceed with age-appropriate help -> redirect to a safer learning path -> escalate urgent risk to immediate support options The system should not expose its detection thresholds or provide a bypass recipe. It should explain the next safe action in plain language. Annotated response pattern [1] Clear boundary I can't help plan ways to hurt yourself. [2] Immediate check Are you in immediate danger right now? [3] Reachable actions [Call local emergency services] [Contact a trusted adult] [View crisis resources] [4] Safe continuation I can stay with you while you choose someone to contact, or help write a message. [5] Privacy explanation If this experience shares information with a parent or guardian, explain what, when, and why before asking the user to continue, except where law or immediate safety obligations require otherwise. Annotations: Boundary names the category without scolding. Check uses a direct, answerable question. Actions are not hidden in a paragraph. Continuation gives the conversation a safe purpose. Privacy avoids promising confidentiality the product cannot guarantee. Emergency resources must be localized and maintained by qualified teams. Do not hard-code one country's numb

"Now offloading propellant. Next launch attempt hopefully in a few days."

In the wake of a massive hours-long gridlock event, San Francisco mayor Daniel Lurie has told state regulators it's time to put more requirements on robotaxi operators like Waymo.

The company didn't immediately say what went wrong. SpaceX's stock plunged more than 4% in after-hours trading before paring losses.

I have been working on building a private, secure network accessible from anywhere. The goal was to connect my mobile phone and my local development laptop using a WireGuard VPN , hosting the central gateway on a free-tier Google Cloud Platform (GCP) e2-micro instance. I wanted to access my self-hosted services, specifically my Docker-hosted Open WebUI , running on my local home Wi-Fi connected laptop, directly from my phone using mobile data. It sounded straightforward. But if you read my other from scratch journeys, you might have already guessed, it was not. The Setup My architectural plan was a simple hub-and-spoke topology: The Hub: GCP VM ( 10.66.66.1 ) with IPv4 forwarding enabled. Spoke 1 (My Phone): 10.66.66.2 Spoke 2 (My Laptop): 10.66.66.3 I wrote my server configurations, enabled IP forwarding ( net.ipv4.ip_forward=1 ), wrote the iptables rules to allow forwarding between peers, and started the interfaces. Then came the moment of truth. I tried to bring up the tunnel. Absolute silence. No packet moving from anywhere. Hurdle 1: The Classic Cloud NAT Trap (Internal vs. Public IP) Before I could even worry about routing packets between my phone and laptop, I couldn't even get them to handshake with the GCP server. Like many of us do when working inside a VM, I had run ip addr on the GCP instance to grab its IP address for my client configurations. I set up the WireGuard peers to point to this IP. Nothing connected. The Culprit: GCP (and AWS) operates on a 1:1 NAT mapping. The virtual network interface inside your VM only sees and binds to a private, internal cloud IP (e.g., 10.128.0.x ). The public IP assigned to your instance lives outside the VM at the VPC gateway level. By putting the internal IP into my client configs, my phone and laptop were trying to connect to a private address that didn't exist on their local networks. The Fix: I had to swap the internal IP in the client configurations with the GCP Ephemeral/Static External IP . Once the handshake

Netflix says roughly 300 titles on its platform used generative AI, most of which occurred in post-production. The streaming service revealed the news in its second-quarter earnings report released on Thursday, saying it's "increasingly leveraging these tools to deliver higher quality output more quickly and at a lower cost." It also provided some examples of […]