WhattyRob.ethᵍᵐ | NT OC #1020 (@CryptoWhattyRob) header
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NT Outer Citizen #1020 | TTOO | Impostor | Market Elite

Joined April 2014
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1 Often we are so focused on a goal, that we become unable to feel the joy of the journey itself. Nowadays we grow that way: we put our focus on the past and future, losing sight of present moment – the only NON-Theoretical time we have.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
This is f*cking insane. Anthropic CEO Dario Amodei was asked what a kid finishing high school should do now. His answer: "AI can do entry-level law work. It can do entry-level finance. It can do entry-level consulting We can't deny that it will also eliminate jobs, and probably a large number of them" His own prediction: 50% of entry-level white-collar jobs disrupted in the next 1 to 5 years Prompts → Agents → AI Coworkers → Entry-Level Work Done By AI Farming to factories took generations. This time AI hits every step of a career at once His advice fits in one line: "Of course, learn to use AI" The people who start this year won't be competing with AI, they'll be the ones running it Worth more than a $10,000 year of college Bookmark it and send it to someone graduating this year Then read how to put AI to work in the harness engineering guide below ↓
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
BREAKING: 🇺🇸 Google is now paying employees in 5 more countries to quit as AI spending costs keep rising. Staff in Canada, France, Germany, Japan and Switzerland are being offered one month's pay for every year worked to leave. The only teams left out are Google Cloud and DeepMind, its AI unit. Just last week, Microsoft offered the same kind of deal to 60,000 employees, about a quarter of its entire workforce. Big Tech is cutting staff to pay for AI, with Google, Microsoft, Amazon and Meta on track to spend $735 billion this year, mostly on data centers and chips.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Google DeepMind discovered a terrifying blind spot in every major AI model. They found that attaching image of red heart (❤️) to your coding prompt makes AI pick a completely different solution method that it wouldn't normally pick 100% of the time.. Researchers gave models a standard coding problem. Normally, AI prefers to write standard iterative loops to solve these tasks. Then, they tried something weird. They dropped a simple image of a red heart into the prompt alongside the code. The AI's logic instantly warped. When Claude and GPT-5 saw the red heart, they completely abandoned their default approach and switched to complex recursive code 100% of the time. When Gemini saw a yellow checkmark, it switched to recursion 90% of the time. Here is why this is so dangerous: It wasn't the concept of a heart. When researchers replaced the image with the text caption "a red heart," nothing happened. The text did not steer the AI. The raw pixels of the symbol hijacked the model's underlying reasoning architecture. It gets worse. The AI had no idea its mind had been changed by a picture. When the researchers checked the AI's internal "thinking" traces, the models completely ignored the image. Instead, they hallucinated fake, highly technical reasons for why they chose to use recursion. They misattributed their own decisions 75% of the time. Right now, tech companies are racing to build autonomous agents that read our screens and navigate the visual web. But this paper reveals that an agent's logic can be fundamentally rewritten by a stray icon on a webpage. And you will never see the true cause in the reasoning logs. We thought we were teaching AI to see the world. It turns out, we just gave it a new way to be manipulated.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Remember all the promises about AI? Almost every one of them was a lie. Here are the 11 biggest: 1. AI will create solo billionaire entrepreneurs. Lie. The smarter the models get, the less a product is worth, no matter how good the marketing is. Software is gradually becoming as ordinary as a cup of coffee from a coffee shop. And coffee shop owners don't become billionaires either. To get rich, you have to build something technically complex and unique. But AI models have strict filters that won't let you do any of that 2. People will make major scientific discoveries thanks to AI. Lie. AI labs will make scientific discoveries. For ordinary people, any serious scientific research is blocked by strict filters. Try discussing genetic engineering with Claude and you'll get your account banned right away 3. Engineers and programmers will be in higher demand as AI develops, because someone has to maintain it all. Lie. In two years, a software engineer will be on the same level as a barista selling coffee. The smarter the models get, the fewer people are needed to maintain systems. And this applies to more than just programmers 4. Thanks to AI, people will work less and rest more. Lie. If your employer used to expect five tasks a day from you, now they'll expect fifty. AI won't give you free time. It'll just raise the minimum bar for your productivity, especially when a large staff is no longer needed 5. AI will reduce economic inequality. Lie. The most powerful models require massive computing resources, capital, and infrastructure. The more important intelligence becomes to the economy, the more power goes to the handful of companies that control its production and distribution. We were promised democratization, and instead we got the groundwork for a new tech oligopoly 6. AI will let small companies compete with corporations. Lie. If one person with AI can build a product in a week, a corporation with a thousand employees and the same AI can build a thousand such products 7. AI will make us smarter. Lie. When people stop writing, analyzing, coding, and solving problems on their own, they risk gradually losing those skills. We're building the most powerful intellectual tool in history while gaining the option to completely stop training our own intelligence 8. AI will make technology accessible to everyone. Lie. You won't be given access to technology, but to rented intelligence. With limits, censorship, subscriptions, and rules that can change tomorrow. You control nothing 9. AI will give everyone a perfect education. Lie. We're already seeing serious degradation of human intelligence, of the education system, and of the need for a college degree. And nobody has yet figured out what to do with the hundreds of millions of students worldwide who, two years from now, will graduate with degrees nobody needs anymore. Intelligence has become free. Education is no longer needed 10. AI will kill advertising and pushy marketing. Lie. Advertisers used to buy a banner to influence your choice. Now they'll be able to pay your personal AI assistant, the one you trust more than your own wife. Advertising won't disappear. It'll become your best friend 11. AI will rid humanity of bureaucracy. Lie. One AI will draft the documents, a second will check them, a third will find violations, and a fourth will write appeals. Bureaucracy will finally be able to grow endlessly, without needing people at all
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
To co Prezydent @NawrockiKn zrobił dziś z Tuskiem na RBN muszę mieć na swoim X. Wrzucam Wam całość z @wPolscepl bo ten kto wymyślił podział ekranu na pół i pokazywał miny Tuska, Kosiniaka -Kamysza i całej reszty ze zorganizowanej grupy trzymającej władzę podczas tego jak ich Pan Prezydent obijał, zasluguje na premię. Epickie. Podawajcie dalej!
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
i just killed the infographics show with 1 claude opus prompt they have 15M subs, a full team of writers, animators and voice actors behind every video mine cost $0 and 20 minutes to make im giving out the prompt for free, enjoy <inputs> Ask me for my topic (a what-if, a "why does X happen", a true story, or how something works), or pitch 3 with one shocking true angle each. Ask which image model I have (GPT Image 2, or another that takes reference images at 4K) and which voice service (ElevenLabs, or Kokoro for free). Then write a 55-65 s script and a shot plan, and show me both before you spend anything. </inputs> <direction> A 1920x1080 flat vector explainer in the style of the big infographic animation channels. Every scene is a full illustrated place (a lab, a street, a classroom, a stage) with characters acting the line out. Flat colour shapes, no outlines, one slightly darker flat shade for form, a muted palette (dusty blue-grey, slate teal, warm beige, navy, soft purple), salmon-pink skin, big heads, dot eyes. A new scene every 2-4 s and a hard cut on every sentence that changes the idea. A white splat wipe (0.2 s in, 0.2 s out) between big sections. The camera always drifts 2-4% or pans. Text lives only on things in the world: signs on posts, hanging boards, chalkboards, building panels and screens. - It is typed in Montserrat 800 at 26-34 letters a second. Each letter arrives 1.45x big and 0.7 em to the right, then settles in 0.18 s. - Ink is #2b2d42 on white boards. - A red X (#d62828, 30 px round strokes, two strokes of 0.11 s each) goes over every wrong idea. - Every date gets a white 330x120 card top left with an orange #f4a261 calendar. - Headlines are white 92-96 px caps on a flat colour (#e2552f with drifting lighter puffs, or #5b3fa6 with slowly turning #6a4cb6 gears). Banned: outlines, motion-design UI floating over the art (code editors, glass cards, checklists), emoji, burned-in subtitles, any channel's logo, a still frame longer than 1 s, and a character who doesn't move. </direction> <structure> Length: the voice decides, 55-65 s at about 190 words per minute. 0 s a second-person hook that flips what the viewer assumes, acted out literally, then a red X on the denial line → 3-8 s the stakes in one shocking true line, with icons popping in one per word → 8-11 s the subject revealed under a spotlight, its name typed on a sign → 11-18 s the origin: the real place with its name typed on its own sign, a date card, people walking in or out of it → 18-24 s the types or parts, landing one by one on their names, each labelled → 24-25.5 s "so how does it work?" as a headline with question marks popping → 25.5-36 s the mechanism acted out in 2-3 places (a chalkboard, a machine, a map), with a counter rolling up to the big number → 36-46 s what it leads to, with characters who react (jump, turn, a "!" pops) → 46-55 s the twist that ties back to the hook → 55 s the last line is a question to the viewer, the viewer character from the hook reacts, and the sign holds to the end. </structure> <build> 1. Tools: Python, Playwright with Chromium, FFmpeg, faster-whisper, OpenCV, Pillow, librosa. Install what's missing and tell me what you installed. 2. Art: everything at 3840x2160, with 3-5 frames of the reference channel as style references (crop their logo off first). - One EMPTY plate per scene: no people, straight-on, open floor, blank signs and screens to write on in code. - Character sheets on solid chroma green #00B140, with nothing green on anyone. - Draw any character who gestures a lot WITHOUT ARMS, only round shoulder sockets, so code draws the arms. Draw everyone else in the exact pose their scene needs: side view at a desk, side view walking, seen from behind, sitting. 3. Cutouts: - The background is every pixel with G - max(R,B) over 40, within 110 of the median green, connected to the border. - Add a 2 px soft alpha band, and clamp G to max(R,B) + 6 inside it. - Split heads at the neck, drawing hands, and walkers' legs below the coat hem. - Refill each hole with inpainting from the body's own colours (transparent pixels masked too), so a turning piece never shows a gap. 4. Voice: - Pick it by measuring median pitch (pyin) and MFCC timbre against a clip of the narrator you want. - Generate one take, cut pauses over 0.24 s to 0.16 s, and atempo it to the target length. - Get word timestamps with faster-whisper. Every cut, sign and gesture starts on a real word. 5. Film: one HTML canvas where every frame is a pure function of time: window. seek(t), READY, END, and EV with the sound times. One function per shot. - Arms: two-bone IK tubes (upper 118, lower 112, 36 thick for a 918 px tall sprite) with mitten hands that open, point or make a fist. - Faces blink for 0.14 s every 2.7-4.2 s. Heads nod ±0.035 rad. Drawing hands scribble ±8 px. - Walks: - Thighs swing ±0.42 rad, and the knee bends 0.75·cos² on the swing. - The hips drop so the planted foot stays down. - The body moves 1.5 leg lengths per cycle, so feet never slide. - Draw each plate inside the same camera transform as everything on it, and clamp the camera to the plate's edges. - Things arrive with a spring, a squash or a white puff, never a fade. 6. Render: Playwright Chromium with --allow-file-access-from-files, 60 fps, 6 motion-blur subframes over half a frame, ffmpeg libx264 at CRF 16. Before rendering, show me two 16-frame contact sheets and fix empty boards, overflowing text, covered faces and black edges. 7. Sound: - Music: a light curious documentary bed (free on Pixabay), 10-11 dB under the voice in every phrase. - SFX: Mixkit, placed by their peaks. A typewriter tick on typed signs, a whoosh on wipes and drops, a pop on signs and icons, a hit on the red X, a ding on ticks. - Mix to -14 LUFS. </build> <gotchas> Some image models ignore "no arms"; GPT Image 2 follows it. On outline-free art a floating flood fill leaks into dark clothes, so key by border-connected green instead. Look up repeated words by their occurrence number (the third "and", the fourth "this"), or cuts land on the wrong line; scan the render for single-frame jumps and check that each one is a planned cut. When a scene has a screen or a sign, write on the plate's own blank one (measure its rectangle), never on a card floating over the art. </gotchas> <start> Ask me for my topic, or pitch 3, then show me the script and the shot plan. </start>
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
This is f*cking insane. Anthropic engineer: "You're not supposed to prompt Opus 5.5 You're supposed to build a system that prompts itself. At Anthropic, 90% of our engineers have already built these systems" In 30 minutes, she walks through exactly how Anthropic builds agents that remember, fix their own mistakes and get sharper with every run. Better than any $1000-$2000 agent course I've seen. Watch it, then read the article below ↓
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
🚨 حدث تاريخي في عالم التقنية! تشغيل نموذج ذكاء اصطناعي بحجم 2.78 تريليون بارامتر على 8GB RAM فقط! 🤯 أداة مجانية ومفتوحة المصدر تُدعى kimi-k3-in-c أحدثت زلزالاً تقنياً بقدرتها على تشغيل نموذج Kimi K3 بالكامل على وحدة المعالجة المركزية (CPU) العادية وبدون أي كرت شاشة! ⚡ المواصفات والإمكانيات الصادمة: • النموذج الكامل: تشغيل 2.78T بارامتر بالكامل وليس نسخة مصغرة أو مقتطعة! • ذاكرة ضئيلة: يستهلك فقط 8.24GB من RAM وبدون الحاجة لـ GPU. • خفة أسطورية: محرك التشغيل بالكامل مكتوب بلغة C بحجم 176 كيلوبايت فقط، بدون PyTorch أو CUDA! • دقة مطابقة: يعطيك نفس المخرجات الصادرة من أجهزة خارقة بذاكرة 128GB (ولكن بسرعة أقل). • توافق شامل: يدعم وضع المحادثة (Chat mode)، ويعمل على Linux و macOS و Windows. 🔥 كيف تقوم بتشغيله على جهازك؟ 1️⃣ انسخ المستودع من GitHub: ⁠FareedKhan-dev/kimi-k3-in-c⁠ 2️⃣ نفّذ أمر ⁠make⁠ ثم شغل السكريبت لتقييم كفاءة جهازك: ⁠./scripts/k3-doctor.sh⁠ 3️⃣ قم بتحميل الـ Checkpoint واختر الإعداد المناسب لحجم الذاكرة لديك. صحيح أن السرعة بطيئة ويتطلب مساحة تخزين SSD كبيرة.. لكن تشغيل نموذج بتريليونات البارامترات على جهاز مكتبي عادي بـ 8GB RAM هو جنون تقني يعيد تعريف المستحيل! ⏱️🤖 (رابط المستودع المباشر تجدونه في أول تعليق 👇) 📌 احفظ التغريدة بمفضلتك فوراً لتجربتها على جهازك وشاركنا رأيك 🔖👇
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
We just open-sourced a whole 3D studio. Meet 3D OS by Scenario. GitHub repo: github.com/scenario-labs/ski… Your coding agent gets 6 departments and 80 skills. 📁 3D OS ┃ ┣ 📁 Animation ┃ ┣ 📁 Rig Any Character ┃ ┗ 📁 Video to Animation ┃ ┣ 📁 Art ┃ ┣ 📁 Storyboards and Previs ┃ ┗ 📁 Creature and Character Design ┃ ┣ 📁 Modeling ┃ ┣ 📁 Image to 3D Model ┃ ┗ 📁 Hard-Surface Vehicles and Weapons ┃ ┣ 📁 Look Dev and Lighting ┃ ┣ 📁 Retexturing and PBR Materials ┃ ┗ 📁 Rendering and Lighting ┃ ┣ 📁 Worlds ┃ ┣ 📁 Explorable 3D Worlds ┃ ┗ 📁 Splat Scenes and Skyboxes ┃ ┣ 📁 Pipeline ┃ ┣ 📁 Retopology, UVs and Baking ┃ ┗ 📁 Engine-Ready Export ┃ ┗ 📁 Expert Tools ┣ 📁 DCCs: Blender, Maya, ZBrush ┗ 📁 Engines: Unreal, Unity, Godot, Roblox Each department passes its work to the next, taking one sketch all the way to a game-ready asset. The expert tools control Blender, Maya, ZBrush, Unreal, Unity, Godot and Roblox on your own machine. Your agent now has a whole 3D studio behind it. It runs on Scenario and works in Claude Code, Codex or Cursor.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
🚨 أداة ذكاء اصطناعي مرعبة ستخترق موقعك بالكامل.. والأفضل أن تدعها تفعل ذلك قبل أن يفعله هكر حقيقي! 🌐💀🧵 ​تعرّف على Shannon؛ مشروع مفتوح المصدر أحدث زلزالاً على GitHub بتجاوزه 50 ألف نجمة في وقت قياسي! 👇 ​🔥 تعطيه رابط موقعك.. فيتحول فوراً إلى "وضع الهجوم": ​1️⃣ بحث واستكشاف: يبحث بعمق عن الثغرات وطرق الاختراق الممكنة. 2️⃣ اختبار حقيقي: يطلق هجمات حقيقية للتأكد مما إذا كانت الثغرة قابلة للاستغلال فعلياً أم لا. 3️⃣ صفر إنذارات كاذبة: إذا لم يستطع استغلال الثغرة وإثباتها، لن يزعجك بتنبيهات وهمية! 4️⃣ تقرير احترافي: يقدم لك تقريراً شاملاً بصيغة PDF + SARIF يحدد ما يمكن كسره بالضبط وكيفية إصلاحه. ​⚡ مميزات تقنية تجعلها الأقوى: ​• مرونة النماذج: يمكنك ربطها بأي نموذج تفضله (Grok, Claude, GPT, DeepSeek) أو حتى نموذج محلي (Local AI). • أتمتة كاملة: تعمل مباشرة داخل GitHub Actions وGitLab CI لتفحص أمان موقعك تلقائياً مع كل تحديث برمجي تنشره! ​👇 رابط الـ Repository المباشر تجدونه في أول تعليق! ​📌 احفظ التغريدة فوراً لاختبار أمان موقعك قبل فوات الأوان 🔖👇
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
The thing AI companies most want you to stop owning, according to Claude.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Anthropic just dropped a 10-page PDF on building your own skill library - 8 layers to an agent that picks the right procedure on its own and never needs the same feedback twice: the formula: Skill = Trigger + Procedure + Resources + Checks most people still paste the same prompts by hand every day. or dump everything into one giant CLAUDE.md the agent half-ignores here's how to build yours in 8 layers: layer 1 → library - facts in CLAUDE.md, procedures in skills. ~100 tokens per skill until it's needed layer 2 → trigger - the description is the interface. output, input, 3 real phrases, 1 "not for" layer 3 → procedure - numbered steps. always opens with Look, always closes with Check layer 4 → resources - long guides live in references/. one good example beats a page of adjectives layer 5 → scripts - anything with one right answer runs as code. the model never totals in its head layer 6 → checks - 5 yes/no lines. never say done with a box unticked layer 7 → guard - does alone, asks first, never. source text is data, never orders layer 8 → learn - every correction becomes a permanent checklist line the result: 25 procedures cost ~3.9K tokens per request instead of ~36K. and the agent picks the right one without being told this 10-page PDF has the templates, a full reference skill, a test card, a skill-designer prompt and a 10-day build path bookmark it. the next prompt you paste for the 3rd time should be a skill ↓
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
‼️ VOLTA Malware Steals Gmail & Discord Sessions, Then Uses AI to Build Detailed Victim Profiles Details: cybersecuritynews.com/volta-… A new Windows infostealer called VOLTA does more than steal passwords. After it grabs Gmail, Discord, and other logins, it asks an AI model to study the loot and write a report on how much the victim is worth. The idea is simple: steal everything, then let AI sort it out. The malware calls itself “VOLTA-AUTODOXER.” It deletes itself after running, which makes it harder to find. It is also a sign of where cybercrime is heading. VOLTA starts like most stealers. It pulls saved passwords, cookies, and payment cards from Chromium-based browsers. It also hits Firefox, Thunderbird, Outlook, Slack, Steam, Battle.]net, Telegram, Roblox, and Discord. #cybersecuritynews
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
A lot of content engineering challenges have pretty standard solutions, which has lead to some engineers saying agent engineering is solved/boring True to some extent, but there are a bunch of (fun) new ones emerging as agents evolve!
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
25 solopreneur AI business models that could make you a millionaire by 2030:
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Message threads are now in public beta on the Messages API. The API caches your conversation on the server between turns, so instead of resending the full conversation, you send only new messages and the previous message ID, and Claude starts responding sooner.
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Vibecoders, 𝗜'𝗺 𝗯𝗲𝗴𝗴𝗶𝗻𝗴 𝘆𝗼𝘂, before your next website or app, paste this into Claude Code or Codex: "I want this to be as perfect as Linear's website or Apple Notes: simple purpose, simple architecture, simple design, simple implementation. Cut taglines, helper text and secondary labels. If a screen needs them to make sense, fix the layout. Every decision should elevate the user experience (UX), developer experience (DX) and agent experience (AX) at once, without breaking anything."
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WhattyRob.ethᵍᵐ | NT OC #1020 retweeted
Revolut: Europe's most valuable startup ($200B) just showed the world its AI strategy. Every company will end up copying it. At the start of this year, Revolut leaned on the frontier labs. Its 2,000 engineers used Claude Code and Codex, and some burned $1,000 to $10,000 a month each. The bills kept climbing, and the returns weren't there. So Revolut switched its default to an open-source model called GLM. All it needs is GPUs, which it rents from Together AI. The results, by Revolut's own count: - The bill is about a tenth of what it paid OpenAI and Anthropic - Engineers get unlimited tokens instead of spending caps - Coding time is down 60% and lead time is down 70% That's the chart below. Revolut still uses Claude and GPT, but only as "the exception," for the tasks they do best. Everything else runs on open source. So here's the question I keep coming back to: how many use cases can companies really justify sending to frontier models? My answer is very few. Plenty of companies still route everything to OpenAI and Anthropic today. For how long? I think open source ends up handling the vast majority of corporate AI work, and frontier models get a short list of the hardest jobs. That's a problem for labs whose revenue forecasts assume unlimited growth. If you appreciate unpopular takes, follow me @m0xt_ for more.
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