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Pada series sebelumnya, kita sudah melakukan instalasi nix di VirtualBox dan setup SSH agar dapat diakses diluar VirtualBox. Sebelum kita lanjut untuk melakukan konfigurasi system lagi, kita butuh mengetahui bagaimana syntax dalam menulis program Nix dan di artikel ini kita akan mempelajari dasar syntax-nya. Nix Language Nix adalah purely functional language yang lazy-evaluated , digunakan untuk mengkonfigurasi Nix package manager dan NixOS. Karakteristik utama: Purely functional : sebuah function hanya bisa mengembalikan nilai berdasarkan inputnya, tidak bisa mengubah variabel di luar scope-nya (no side effects), dan tidak ada variabel yang bisa diubah setelah didefinisikan (no mutation). Kalau kamu familiar dengan const di beberapa bahasa pemrograman, semua variabel di Nix berperilaku seperti itu. Lazy evaluation : Nix tidak menghitung nilai suatu ekspresi sampai nilai itu benar-benar dibutuhkan. Ini artinya kamu bisa mendefinisikan ribuan package di nixpkgs tanpa semuanya dievaluasi sekaligus. Hanya yang kamu gunakan saja yang akan diproses. Semua adalah expression : tidak ada statement di Nix, setiap baris kode selalu menghasilkan sebuah nilai. if/else bukan statement seperti di bahasa pemrograman pada umumnya, melainkan expression yang harus mengembalikan nilai dari kedua cabangnya. Tidak ada loops : karena variabel tidak bisa diubah, loop seperti for atau while tidak ada artinya di Nix. Sebagai gantinya, kamu menggunakan fungsi seperti map dan filter , atau rekursi untuk mengolah kumpulan data. 1. Basic Data Type Konsep JavaScript Nix String "hello" "hello" Number 42 , 3.14 42 , 3.14 Boolean true , false true , false Null null null List [1, 2, 3] [ 1 2 3 ] Object { a: 1 } { a = 1; } ⚠️ Perbedaan Penting List di Nix menggunakan spasi sebagai pemisah, bukan koma Attribute set menggunakan = bukan : , dan setiap entry diakhiri dengan ; Nix let name = "Alice" ; age = 30 ; scores = [ 10 20 30 ]; person = { name = "Bob" ; age = 25 ; }; in person Javascript const name

The company has set aside an unusually high number of shares for retail investors. Still, experts say, you’re just getting the crumbs.

The rocket maker debuts on Nasdaq today under a wave of criticism about Musk’s near-absolute control. It’s how the company has worked from the start.

In this podcast, Shane Hastie, Lead Editor for Culture & Methods spoke to Craig McLuckie, co-creator of Kubernetes and CEO of Stacklok, about the impact of AI coding tools on open source communities and engineering teams, designing deliberate organisational culture, and navigating evolving career paths for engineers in the age of AI. By Craig McLuckie

MIT Technology Review Explains: Let our writers untangle the complex, messy world of science and technology to help you understand what’s coming next. You can read more from the series here. Your brain lives in the dark space of your skull. Yet it knows when the wind lifts the hairs on your skin, when your heart is…

I run a content site, do-and-coffee.com . Like everyone else, it gets scraped by AI crawlers. Instead of blocking them, I did something else: I put a paywall in front of the site that returns HTTP 402 Payment Required to bots, with machine-readable payment instructions. If a crawler pays a cent in USDC, it gets the article. If it doesn't, it gets the 402 and nothing else. Then I let it run for 30 days and watched. Here's what actually happened — and it's not the number you'd put on a pitch deck. TL;DR A Cloudflare Worker sits in front of the site. AI crawlers get 402 + x402 payment requirements ; humans and search bots pass through free. Payment is USDC on Base , $0.01 per article, verified and settled through Coinbase's CDP facilitator. 30-day result: 5,811 crawler requests, 5 paid, 5,806 served a 402. Revenue at $0.01/article ≈ $0.05 . The interesting part isn't the revenue. It's who paid: GPTBot paid 4 times out of 48 requests; ClaudeBot paid once out of 651. Architecture do-and-coffee.com/blog/article/* ─▶ x402 Worker (Cloudflare) │ has X-PAYMENT-RESPONSE? ───────────┤─▶ yes ─▶ proxy origin (200) KV cache hit (payer:url)? ─────────┤─▶ yes ─▶ proxy origin (200) no X-PAYMENT? ─────────────────────┤─▶ 402 + payment requirements has X-PAYMENT? ────────────────────┘ │ ├─▶ CDP /verify (is the signed payment valid?) ├─▶ CDP /settle (waitUntil: confirmed — on-chain) └─▶ on success: KV.put(payer:url, receipt, ttl 24h) ─▶ proxy origin The worker speaks the x402 protocol: a 402 response carries an accepts array describing exactly how to pay (scheme exact , network base , asset USDC, amount, payTo wallet). A compliant agent reads that, signs a USDC payment, and retries with an X-PAYMENT header. The worker verifies and settles it through Coinbase's facilitator, then proxies the real article. How it works The 402 response When there's no payment, the worker builds the requirements and returns 402: function buildPaymentRequirements ( resourceUrl : string , env : Env ): Payment

PyTrees look deceptively simple. You flatten a nested Python object into leaves, keep a structure descriptor, and later rebuild or map over the same shape. That abstraction is powerful enough to carry optimizer states, model parameters, batched inputs, gradients, and sharding annotations. It is also just ambiguous enough that three major frameworks implement three subtly different languages under the same idea. This note compares JAX jax.tree_util , PyTorch torch.utils._pytree , and TensorFlow tf.nest . I tested the behavior in two environments: an older stack with JAX 0.4.35, PyTorch 2.2.2, TensorFlow 2.20.0, and a newer stack with JAX 0.10.0, PyTorch 2.12.0, TensorFlow 2.21.0. Most flatten/unflatten semantics were stable across these versions. The main version-sensitive result is PyTorch: _pytree.tree_map in 2.2.2 accepts only one pytree, while 2.12.0 supports multiple pytrees and behaves much closer to JAX prefix-style mapping. The short version: JAX treats pytrees as a transformation language, PyTorch is converging toward that model in torch.func , and TensorFlow exposes a broader nested-structure utility through tf.nest . Those differences show up exactly where backend-agnostic libraries usually hurt: None , dictionary order, custom containers, tree_map , autodiff, and vectorization. The Shape Of The APIs The three APIs have the same surface story but not the same contract. from jax import tree_util as jtu from torch.utils import _pytree as tpu import tensorflow as tf leaves , treedef = jtu . tree_flatten ( tree ) tree = jtu . tree_unflatten ( treedef , leaves ) tree = jtu . tree_map ( f , * trees ) leaves , spec = tpu . tree_flatten ( tree ) tree = tpu . tree_unflatten ( leaves , spec ) tree = tpu . tree_map ( f , tree ) # PyTorch 2.2.2 tree = tpu . tree_map ( f , * trees ) # PyTorch 2.12.0 leaves = tf . nest . flatten ( tree ) tree = tf . nest . pack_sequence_as ( structure , leaves ) tree = tf . nest . map_structure ( f , * structures ) Flattening means "whi

I Built a Git Sync Tool for My Obsidian Vault You write notes, you save them, you forget to push to GitHub. Then your laptop dies, and your notes are gone. I built a single Bash script that automates the entire sync workflow, and it works with any Git repo. If you use Obsidian (or any plain-text note-taking system) and sync via Git, you know the drill: write notes, stage changes, commit, fetch, check status, pull, push. Every time. It's 6 repetitive commands that you will inevitably skip until disaster strikes. I got tired of this and built git-sync , a single Bash script that does everything in one go. What It Does git-sync is a terminal-based Git sync tool that: Auto-commits all changes with a timestamp Fetches remote state Detects divergence (ahead/behind) Shows you only the relevant sync options Executes your choice with safety guard rails How It Works Run it from inside any Git repo: ./git-sync Phase 1 - Auto-commit: Staged or unstaged changes are committed automatically with a message like "Last Sync: Jun-12 (Arch)" . The device name is configurable. Phase 2 - Fetch & Detect: It fetches from remote, counts how many commits ahead and behind you are, and categorises the state: ahead, behind, diverged, or in-sync. Phase 3 - Smart Menu: Only relevant options are shown: State Options Ahead only Upload, Sync, Force push, Cancel Behind only Download, Sync, Hard reset, Cancel Diverged All six options Phase 4 - Execute: The chosen action runs with a spinner and status messages. Destructive operations (force push, hard reset) require explicit confirmation. Why It's Useful for Notes Syncing Obsidian + Git is a powerful combo. Your notes are plain markdown, version-controlled, accessible from any device. The friction is the sync ritual. git-sync removes it. Multi-device workflows: I run this on my Arch desktop (DEVICE_NAME="Arch") and my work laptop (DEVICE_NAME="Laptop"). The auto-commit message tells me exactly which machine made each sync, so I can trace conflicts back

Avataar AI's distilled video model is priced at $0.005 for every second of generation

Today on Uncanny Valley, we take an early look at the SpaceX IPO and why you might find yourself among the investors without even realizing it.

Amazon's rolling out a free software update for Echo Hub devices that gives the home screen a much-needed update to the interface it launched with in 2024. It had already added Alex Plus AI support, but the new interface has a cleaner, fully customizable layout that fits more smart home info and controls on the […]

Activists raised a 40-foot-tall inflatable Elon Musk in Manhattan to draw attention to the risk he allegedly poses to investors.

Wits its official share pricing announcement, SpaceX's IPO has begun.

After SpaceX makes its public debut, lower-tier SPV investors face hidden fees, lengthy payout delays, and the risk of outright fraud.

Working with modern APIs means living in JSON. But the moment your project touches a legacy enterprise system - a bank, a government service, or a SOAP endpoint that hasn't changed in a decade - you're suddenly dealing with XML. The challenge isn't just swapping syntax; it's understanding where the two formats are structurally incompatible, and what breaks silently when you ignore that. Why JSON and XML Don't Simply Map to Each Other JSON is compact and type-aware - it distinguishes between numbers, booleans, strings, and arrays natively. XML is verbose, treats all content as text, and has no concept of arrays. It only has repeated sibling elements. This gap is where most conversion bugs are born. A JSON array with just one item can silently become a plain object if your converter doesn't handle the edge case explicitly. The Three Biggest Conversion Pitfalls First is array ambiguity - XML has no array type, so a JSON array becomes repeated sibling elements. A single-item array is indistinguishable from a plain object unless your converter explicitly preserves the list context. Second is type erasure - XML flattens numbers, booleans, and strings into plain text, destroying the type information that many downstream systems depend on. Third is the single root element rule - JSON can have multiple top-level keys, but every valid XML document must have exactly one root element wrapping everything else. Handling Arrays the Right Way Always nest array items inside a named parent element. A JSON users array should produce a parent element containing individual child elements. This structure makes the list unambiguous to any downstream XML parser and prevents silent data loss during round-trips. Escaping Special Characters Characters that are perfectly valid inside a JSON string will break an XML parser immediately. Your conversion logic must escape these four: less-than becomes <, greater-than becomes >, ampersand becomes &, and double-quote becomes ". Skipping even one of

Firefox CLI is my new project - a CLI interface that lets your agent control your real Firefox session. It's a full equivalent of Agent Browser with the same capabilities, but for Firefox - and with a number of improvements. Why it's better First, you install the extension once and for all. The extension ships right alongside the CLI: install it, grant access, forget about it. Unlike Chrome, where you have to grant connection permissions every half hour and manage debugging sessions - here it's one button and full control. Second, your agents can now create their own separate windows and request your permission to connect on their own. In everything else, Firefox CLI mirrors Agent Browser: token-efficient operation via short IDs , running arbitrary scripts, keypresses, input emulation, form filling, and full tab and window management of your real session - where you're already logged in. Why I built it I used the Comet browser for a long time (on my promo subscription to Perplexity), but it started to let me down. More unnecessary features and ads crept in, it got slower. But the main thing - using Comet as an actual browser during development is extremely inconvenient : there's music you can't turn off, a broken onboarding that was never fixed after months of back-and-forth with support, and a poorly functioning CDP. I switched back to Firefox as my main browser, but losing the ability for agents to control my browser was a huge blow to my workflow. No automation for filling out boring freelance forms, no proper web app testing. I went looking for alternatives, but nothing like Agent Browser for Firefox simply existed. And here's the result :) Installation 1. Install the CLI: npm install -g firefox-cli 2. Install the Firefox extension: firefox-cli setup 3. Install the skill for agents: Claude Code /plugin marketplace add respawn-llc/claude-plugin-marketplace /plugin install firefox-cli@respawn-tools Codex $skill-installer install https://github.com/respawn-llc/fire

By integrating an AI assistant directly into Edits, Meta is aiming to keep creators engaged on Instagram as it continues to compete with TikTok and YouTube for creators' attention.

Alt Carbon said the agreement followed more than a year of scientific review and due diligence, with Microsoft requiring additional verification and data-sharing measures.

SpaceX alumni Andrew Redd is betting the ocean has vast amounts of untapped geothermal energy.

7 Things I Wish I Knew Before Scaling Next.js + Supabase to 100K Users Six months ago, we launched our SaaS with Next.js and Supabase. The stack was perfect for our MVP: fast development, great DX, and it just worked. Then we hit 10K users. Then 50K. Then 100K. Everything that worked beautifully at small scale started breaking. Database queries that took 50ms now took 5 seconds. Our Supabase bill went from $25/month to $800/month. Users complained about slow page loads. Here's what I wish someone had told me before we started. 1. RLS Policies Are Not Optional (Even in Development) We skipped RLS in development. "We'll add it before launch," we said. Launch day came. We enabled RLS on all tables. The app broke in 47 different places. Queries that worked suddenly returned empty arrays. Inserts failed with permission errors. We spent 12 hours fixing RLS policies while users waited. What I'd do differently: Enable RLS from day one. Write policies as you create tables: CREATE TABLE posts ( id UUID PRIMARY KEY DEFAULT uuid_generate_v4 (), title TEXT NOT NULL , user_id UUID REFERENCES auth . users ( id ) ); -- Enable RLS immediately ALTER TABLE posts ENABLE ROW LEVEL SECURITY ; -- Write policies now, not later CREATE POLICY "Users can view own posts" ON posts FOR SELECT USING ( auth . uid () = user_id ); Test with RLS enabled. If it works in development, it'll work in production. 2. Database Indexes Are Not Premature Optimization "We'll add indexes when we need them." We needed them on day 3. Our posts feed query went from 50ms to 8 seconds as we hit 10K posts. Users complained. We scrambled to add indexes during peak traffic. The query: const { data } = await supabase . from ( ' posts ' ) . select ( ' *, profiles(*) ' ) . eq ( ' published ' , true ) . order ( ' created_at ' , { ascending : false }) . limit ( 20 ) The fix: CREATE INDEX posts_published_created_at_idx ON posts ( published , created_at DESC ) WHERE published = true ; Query time dropped to 12ms. What I'd do di