food trucks used to sell you 3 amazing tacos for like $5 cash only. then people with master’s degrees discovered them and now it’s $18.50 for 3 mid tacos plus a screen asking for a 20% tip

Your Claude memory file is probably making it dumber. Anthropic just published how Claude's memory actually works, and they tested it on Pokémon Red: - Sonnet 3.7 saved everything: 413 files in 225 folders. It earned 1 badge - Fable 5 saved only what it couldn't see on screen: 9 files plus one global.md. It earned 4 badges - Opus 5.5 kept a few short notes and beat the game What they found: - Tell Claude what memory is for, not strict rules. Forcing "only record failures" wiped out much of the gain - Claude Code only loads the first 200 lines or 25 KB of MEMORY.md. Anything below that never makes it into the session - Longer instruction files make Claude follow them less - "Dreaming": letting Claude reread its old sessions to fix wrong notes. On a 350,000-file company archive, accuracy went from 13% to 48% The fix takes 2 minutes: open your CLAUDE.md or MEMORY.md, cut it under 200 lines, and delete anything Claude can already read from your code.

[#IDOLSTABLE#] 𝙋𝙞𝙘𝙠 𝙔𝙤𝙪𝙧 𝘿𝙚𝙨𝙩𝙞𝙣𝙮 𝙁𝙤𝙤𝙙 𝙈𝙖𝙩𝙚✨#MnetPlus_Original# Tap the screen to find your destined crew👀 Share with a friend for double the fun!🔥 Hotspot where Korean food unites the world beyond borders🍽️ Global Food Talk Show where your bias shares their fave K-FOOD 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 Every Tuesday 8PM (KST) 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 Release 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 Every Wednesday 8PM (KST) 𝗠𝗻𝗲𝘁 On Air == [IDOL'S TABLE] 𝙋𝙞𝙘𝙠 𝙔𝙤𝙪𝙧 𝘿𝙚𝙨𝙩𝙞𝙣𝙮 𝙁𝙤𝙤𝙙 𝙈𝙖𝙩𝙚✨ 화면을 터치해 나와 운명의 식구를 찾아보세요👀 친구에게 공유하면 재미가 2배!🔥 국경을 넘어 한식으로 하나 되는 핫플레이스🍽️ 최애의 K-FOOD 취향이 펼쳐지는 글로벌 푸드 토크쇼 〈IDOL'S TABLE〉 on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 👉 📍 매주 화요일 저녁 8시 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 공개 📍 Watch on 𝗠𝗻𝗲𝘁 𝗣𝗹𝘂𝘀 📺 매주 수요일 저녁 8시 𝗠𝗻𝗲𝘁 본방송 #엠넷플러스오리지널# #MnetPlus# #엠넷플러스# #Mnet# #엠넷#

Take full control of your game's splash screen in Unity 6! 🎨 Customize your background, adjust animations, and swap in your own logos. Plus, the "Made with Unity" logo is now completely optional on all plans, including Personal. 🔗 Learn more:

ChatGPT Voice is awesome It combines voice + visual (on-screen) UI - so it doesn't need to read every word aloud, which is a HUGE upgrade Plus, it tool calls! I asked for a coffee slot tomorrow - it checked my cal, found spots nearby, and sent out an invite 👇

Doom is coming... Get The Bundle of Doom featuring one movie ticket to experience #AvengersDoomsday# on the big screen, plus one collectible Doctor Doom Statue Bucket. Secure yours now👇

# Cursor Features and Practical Usage 🌐 "Just look at the screen and fix it" is now something the AI agent can literally do. Cursor's Browser tool hands the agent control of a browser, covering everything from E2E testing to design-to-code in one loop. 🏷️ Title: Browser Tool 🔗 URL: 📘 Overview The Browser tool lets Cursor's agent directly drive a browser inside the IDE. It can navigate to URLs, click, fill forms, capture screenshots, and inspect console logs and network traffic on its own. The key benefit is closing the loop between visual verification and code changes within a single agent run. ⚙️ How It Works The browser runs as a secure web view controlled via an MCP server extension, and the agent can: ・Navigate: visit URLs, follow links, move through history, reload pages ・Interact: click, double-click, right-click, hover, fill and submit forms ・Inspect visually: capture screenshots as images to verify layout and UI ・Debug: read JavaScript console logs and errors, plus network traffic Logs are written to files and the agent selectively reads only the relevant lines, so it handles huge outputs efficiently. Automatic dev-server detection prevents starting duplicate servers. Authentication cookies, localStorage, sessionStorage, and IndexedDB persist across sessions in the same workspace, so login state survives between verification runs. 🛠️ Practical Usage The design sidebar lets you design and code at the same time. You can visually adjust element positioning, flex direction, alignment, grid layouts, width/height/padding/margin, colors, gradients, shadows, opacity, and border radius with sliders. When the look matches your vision, click `Apply` and an agent translates the visual changes into appropriate code. You can also select multiple elements and apply changes together via hot-reload. Execution safety is governed by approval modes: `Manual approval` (recommended), `Allow-listed actions`, and `Auto-run`. 💡 Use Cases ・E2E testing: fill forms with test data, validate error messages, capture screenshots for visual regression ・Design-to-code: import Figma mockups and convert to pixel-perfect HTML/CSS ・Accessibility audits: check contrast ratios, semantic HTML, ARIA labels, and keyboard navigation against WCAG ⚠️ Caveats The origin allowlist provides best-effort protection only. Link navigation and client-side redirects from allowed domains may still reach non-allowed origins, and manual user navigation bypasses the allowlist entirely. Avoid `Auto-run` with untrusted code, and review allowlist configurations regularly. #Cursor# #AICoding#

According to the official FAQ, Halo: Campaign Evolved on PS5 will require both players in split-screen co-op to have their own PlayStation Network accounts, active PlayStation Plus subscriptions, and linked Microsoft accounts. Normally local split-screen games normally don’t require PlayStation Plus. The FAQ also states that Xbox players only need separate Microsoft accounts for split-screen. If these requirements are accurate, PS5 players will need two PlayStation Plus subscriptions just to play couch co-op, in addition to two Microsoft accounts.

🧠 Can your model act on information that's no longer on screen? Even frontier multimodal LLMs fall apart at a memory card game and a 3D maze. 📰 Title: Beyond the Current Observation: Evaluating Multimodal Large Language Models in Controllable Non-Markov Games 🔗 URL: 💡 Overview This paper introduces RNG-Bench, a benchmark that measures whether MLLMs can hold past, no-longer-visible observations in mind and act on them. It isolates in-context belief-state tracking through two games: Matching Pairs (memory cards) and a first-person 3D Maze. 🔍 Challenges Solved Existing benchmarks expose full state or only test "remember-to-answer" after an episode ends. This work moves into closed-loop "remember-to-act" settings, where a recall error reshapes the observations that follow, capturing the real difficulty agents face. 🛠 Methodology & Proposed Approach ・Games framed as POMDPs, requiring belief states maintained from interaction history ・Difficulty controlled by grid size, visual pattern, and text vs image modality ・A Duel protocol pits two models on the same board, plus an Oracle that injects true hidden state ・A Memory Gap metric compares normal vs Oracle play to separate forgetting from poor decisions 📊 Use Cases / Results On 10×10 Matching Pairs, GPT-5.4 hit 62.3%, Gemini-3.1-Pro 50.0%, Qwen3.5-397B 25.3%. On a 13×13 maze, Gemini-3.1-Pro led with 50% success. Qwen3.5-397B collapsed from 90.6% (4×4) to 0.7% (12×12). Removing action-text traces dropped GPT-5.4 by ~75%, showing visual recognition, not history length, is the real bottleneck. #MultimodalLLM# #AIAgents#