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AI Photo Editor No Sign Up Edit Photos Free Online Open the editor, upload a JPG, PNG, or WebP image, and describe the change you want. This free AI photo editor online needs no sign in to start: remove distractions, rebuild backgrounds, create campaign images, or enhance detail from one browser workspace. No installation and no account needed to try. Sign in only when you want daily credits and a longer cloud creation history. Generation Mode Single Edit Multi Fusion Model 🍌 Nano Banana 2 Lite Lightning-fast, low-cost 1K image generation & editing Quick Select: 🍌 Nano Banana 2 Lite Fast SeeDream 5.0 Pro HD GPT Image 2 4K Wan 2.7 Pro Pro Image Upload Upload Image ( 0/1 ) Upload Max 30 MB Supported formats: JPG, PNG, WEBP (Max 30 MB) Prompt 0 / 1000 Try these examples Replace background Change hair color Object remover Style transfer Old photo restoration Aspect Ratio Default 1:1 3:2 2:3 9:16 16:9 3:4 4:3 4:5 5:4 1:4 4:1 1:8 8:1 21:9 Image Resolution 1K Generate Images ( 2 credits) Before Remove the red suitcase and traffic cone, then rebuild the cobblestone naturally. ↓ After Remove unwanted objects 4.9/5 from 10,000+ happy creators Trusted by innovative teams at What Can an AI Photo Editor No Sign Up Tool Actually Do? These tools cover common photo-editing goals from one page. Test an AI photo editor no sign up workflow on a real image, inspect the result, and then decide whether an account is useful. Remove Objects with an AI Photo Editor No Login Workflow Identify a distra

Yet Another Markup Language Engineering Toolkit Yamlet is a minimal, single-source-of-truth spec format for spec-driven development with agents. One component per .yamlet.yaml file, one contract, a handful of requirements, and EARS acceptance criteria. Basically, minmaxing the spec game: Write down the minimum that is required, but convey the maximum meaning possible. All accompanied by a (hopefully) challenging skillset of sparring partners, that result in a quick and easily verifiable spec definition. email_service.yamlet.yaml is a complete example of one such file. There can be many, and that's the point — each a small scope, focused on the exact, minimal, must-fulfill requirements. The folder specs_example/ also contains more examples, as well as the generated test files from the acceptance criteria. Install yamlet is a single self-contained binary (no runtime needed) for macOS and Linux, on both Intel and Apple Silicon / arm64. In addition to this, it's also a plugin for claude code! brew tap RicardoMonteiroSimoes/yamlet # add the tap (one-time) brew trust --tap RicardoMonteiroSimoes/yamlet # trust it (one-time) brew install yamlet yamlet --version Homebrew 6+ gates non-official taps behind a trust step: without it, brew install prompts you to confirm the tap on first use. brew trust --tap pre-approves it so the install runs unattended (and covers future upgrades). Homebrew works on Linux too, so the same commands install it there. To upgrade later: brew upgrade yamlet .

What this is A studio for building knowledge models : a domain or a document written as layers of typed nodes joined by typed relationships, so that a check can be pointed at one claim instead of at "the document". That distinction is the whole product — it is the difference between a finding and an impression. It was built out of frustration with what happens when you ask a general model to reason about company material: it produces something fluent, confident and unverifiable, and you cannot tell which parts it read and which parts it filled in. The response here is not a better prompt. It is to make the structure explicit and checkable first, and to let the model work against that structure rather than against a pile of prose. A model in Pennant says things like: this section makes this claim; this claim creates this obligation on this owner by this date; this evidence would settle it; this rule contradicts that one. Then the analyzers run against the graph, and what comes back is specific enough to argue with. Nothing here needs a language model. Every graph, check, ordering and export is arithmetic over what you typed. AI assistance is optional, off by default, and adds suggest buttons — never silent edits. Screenshots Quick start docker compose up --build # then open http://127.0.0.1:8080 Or natively, with Go 1.21+: make up # builds and serves on 127.0.0.1:8080, data in ./data There are no Go dependencies to download, so go build works offline. It binds loopback by defa

2026/07/20 - Ryan Boyd Announcing the Data Outpost Conference Data Outpost is a new conference for data and AI builders, coming to San Francisco November 4-5, 2026. The next evolution of Small Data SF: two days of workshops, talks, and real time with the people building the data layer AI depends on.

Your AI agent's memory files are lying to it. stalebrain finds every lie, proves it with commits, and hands you the fix. Install · Demo · What it does · How it compares · Troubleshooting · License Type /stale-brain in your AI coding assistant and it audits every agent memory file in your repo (CLAUDE.md, AGENTS.md, .cursorrules, GEMINI.md, Copilot instructions, 18+ locations across 13 agents) against the code as it exists today. Claims that check out get a dated stamp. Claims that don't get a verdict, the commits that prove it, and a ready-to-apply fix. Not a linter. A trust model: after one audit, every claim in agent memory carries an age, a verification date, and cited evidence. Install Prerequisite: a repo with git history. That's it. With uv or pip (recommended, works inside Claude Code or any CLI) uv tool install stalebrain # or: pip install stalebrain / pipx install stalebrain stalebrain install # user-level: every repo, Claude Code CLI and desktop app stalebrain install --project . # or just this repo One-shot without installing anything permanent: uvx stalebrain install With git alone # project-level git clone https://github.com/stalebrainlabs/stalebrain .claude/skills/stale-brain # or user-level (available in every repo) git clone https://github.com/stalebrainlabs/stalebrain ~/.claude/skills/stale-brain Then type /stale-brain , or say "audit my agent memory". Desktop / no terminal at all stalebrain install covers the Claude Code desktop app (it reads the same user-l

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Quick answer Daily AI news for vibe coders. July 31, 2026: OpenAI cuts GPT-5.6 Luna 80%, Nscale buys Anyscale, Gemini Robotics 2, plus one build to ship today. 5 min read · Updated July 31, 2026 Welcome to the daily AI news brief for vibe coders. It is Friday, July 31, 2026, and the last 24 hours were about cost and consolidation. OpenAI slashed a frontier model’s price, an infrastructure buyer scooped up the company behind Ray, and Google pushed AI deeper into physical robots. If you ship on Shopify, Claude, GPT, Gemini, or Firebase, the pricing news alone changes the math on what you can afford to build this weekend. TL;DR OpenAI cut GPT-5.6 Luna’s price by roughly 80%, making bulk API work far cheaper. Nscale agreed to buy Anyscale for about $1.65B; Ray stays open under the PyTorch Foundation. Google DeepMind shipped Gemini Robotics 2, a three-model suite for whole-body humanoid control. The EU opened a €10B call for up to seven AI gigafactories, bids closing November 12. AWS posted $42.2B in Q2 revenue, its fastest growth in 18 quarters. Build of the day: route one bulk task to Luna and measure the new cost per run. OpenAI cuts GPT-5.6 Luna price roughly 80% [ECOSYSTEM] What shipped. OpenAI sharply cut the price of GPT-5.6 Luna, its most cost-efficient tier, with input and output dropping from about $1 and $6 to roughly $0.20 and $1.20 per million tokens. GPT-5.6 Terra, the balanced everyday model, saw a smaller cut of about 20%. The move landed roughly three weeks after