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🙌🏼Unreal Engine 5.8 just leveled up #Character #Animation! #ControlRig #Dynamics brings fast, intuitive physics directly into your rigs! NO heavy setup, NO complexity. You can now: Spawn dynamic solvers in sec, build & control chains! Enjoy! 🤩

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Stéphane Biava

1,282 subscribers

58,429 Aufrufe • vor 3 Monaten •via X (Twitter)

Kunst#Character#Animation#ControlRig#Dynamics
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You don't understand... Higgsfield MCP + Claude just automated AI film making. Every single step you used to grind through to make an AI movie, you can now do 10x faster. Drop the script into Claude Opus 4.8 and say: "Here's my script. Break it into a full shotlist. Shot number, scene, shot type, camera move and the action in each frame." Now the whole film is mapped, shot by shot. - Pull your assets. Ask Claude: "From this shotlist, list every character, every location and every prop across the whole film." That's your build list. The stuff you would need to generate and give as references in next steps. - Build the character sheets. Higgsfield MCP is connected, so Claude has hands now to do stuff directly. It generates the images itself. Have the full body, back view and close up in the character sheet. One per character. Each sheet becomes the locked reference for that face. Same move for locations, generate the empty plate for each one before anyone steps into it. - Generate the frames. Feed Claude the references plus the shot and have it write and fire the Seedance 2.0 prompt. "Using the lead's character sheet and the alley plate, generate shot 4 in Seedance 2.0. Low angle, slow push-in, rain." Claude builds the prompt, calls Seedance 2.0 and the frame lands back in chat. Use a Seedance 2.0 skill to teach Claude how to prompt it properly. Now, there are 3 ways to make the shots. Pick one per scene. - Pure prompting. Fastest one. You describe the action in words and let Seedance interpret it. For consistency across a sequence, feed it a frame from the previous shot so the look carries. - Storyboarding. You hand it a panel and it matches that composition exactly. Way more control over how the shot is framed. The tradeoff is that it can introduce more cuts than you actually want. - Path Control System This is the latest technique Seedance 2.0 technique. Generate a still base plate of the scene. Draw a red line across it to mark the exact path of the movement, then describe what's happening. Seedance follows that line for the action. Also ask Claude to remove the red line when animating. This is the one for anything where motion has to land precisely. The output reads like real live action. - Lastly, generate every clip you need, then cut them together. Get it to Capcut for editing and audio design. And that's it. The pipeline that used to need a full crew and a studio can now run from one Claude chat. 2026 is gonna be wild
0:14

You don't understand... Higgsfield MCP + Claude just automated AI film making. Every single step you used to grind through to make an AI movie, you can now do 10x faster. Drop the script into Claude Opus 4.8 and say: "Here's my script. Break it into a full shotlist. Shot number, scene, shot type, camera move and the action in each frame." Now the whole film is mapped, shot by shot. - Pull your assets. Ask Claude: "From this shotlist, list every character, every location and every prop across the whole film." That's your build list. The stuff you would need to generate and give as references in next steps. - Build the character sheets. Higgsfield MCP is connected, so Claude has hands now to do stuff directly. It generates the images itself. Have the full body, back view and close up in the character sheet. One per character. Each sheet becomes the locked reference for that face. Same move for locations, generate the empty plate for each one before anyone steps into it. - Generate the frames. Feed Claude the references plus the shot and have it write and fire the Seedance 2.0 prompt. "Using the lead's character sheet and the alley plate, generate shot 4 in Seedance 2.0. Low angle, slow push-in, rain." Claude builds the prompt, calls Seedance 2.0 and the frame lands back in chat. Use a Seedance 2.0 skill to teach Claude how to prompt it properly. Now, there are 3 ways to make the shots. Pick one per scene. - Pure prompting. Fastest one. You describe the action in words and let Seedance interpret it. For consistency across a sequence, feed it a frame from the previous shot so the look carries. - Storyboarding. You hand it a panel and it matches that composition exactly. Way more control over how the shot is framed. The tradeoff is that it can introduce more cuts than you actually want. - Path Control System This is the latest technique Seedance 2.0 technique. Generate a still base plate of the scene. Draw a red line across it to mark the exact path of the movement, then describe what's happening. Seedance follows that line for the action. Also ask Claude to remove the red line when animating. This is the one for anything where motion has to land precisely. The output reads like real live action. - Lastly, generate every clip you need, then cut them together. Get it to Capcut for editing and audio design. And that's it. The pipeline that used to need a full crew and a studio can now run from one Claude chat. 2026 is gonna be wild

Rez Karim

10,951 Aufrufe • vor 3 Monaten

Tired of trading electricity in a system built for institutions — not you? Carlos Aurelio Hernández felt the same. That’s why he went on a mission — to build a platform where energy professionals could finally trade on their own terms. Now, as CEO of Watt2Trade, he’s changing the game. Here’s how... ⚡🧵 Before building Watt2Trade, Carlos became one of the most respected voices in Mexico’s energy sector — with 35+ media appearances on platforms like Forbes, El Financiero, and Grupo Fórmula. He’s been at the table for every major energy discussion in the last decade. And more importantly — he’s built... ⚙️ HHGM – powering factories, refineries, and municipalities ⚡ SUJIO – cutting energy costs by up to 30% 💼 Volta Capital – backing the next wave of energy innovation Now Carlos is leading Watt2Trade — the first decentralized exchange where you can trade electricity directly. ✅ No brokers ✅ No approvals ✅ No red tape Just your wallet, your power — and a global marketplace open 24/7. It’s built by people who understand the energy market inside and out — and are finally putting it in your hands. This is the future of energy — and you’re invited to shape it. Your kilowatt is your currency. Your Watt is your Power.
0:16

Tired of trading electricity in a system built for institutions — not you? Carlos Aurelio Hernández felt the same. That’s why he went on a mission — to build a platform where energy professionals could finally trade on their own terms. Now, as CEO of Watt2Trade, he’s changing the game. Here’s how... ⚡🧵 Before building Watt2Trade, Carlos became one of the most respected voices in Mexico’s energy sector — with 35+ media appearances on platforms like Forbes, El Financiero, and Grupo Fórmula. He’s been at the table for every major energy discussion in the last decade. And more importantly — he’s built... ⚙️ HHGM – powering factories, refineries, and municipalities ⚡ SUJIO – cutting energy costs by up to 30% 💼 Volta Capital – backing the next wave of energy innovation Now Carlos is leading Watt2Trade — the first decentralized exchange where you can trade electricity directly. ✅ No brokers ✅ No approvals ✅ No red tape Just your wallet, your power — and a global marketplace open 24/7. It’s built by people who understand the energy market inside and out — and are finally putting it in your hands. This is the future of energy — and you’re invited to shape it. Your kilowatt is your currency. Your Watt is your Power.

Watt2Trade

28,792 Aufrufe • vor 1 Jahr

Golden mornings. Fresh air. Clear mind. 🌅✨ Sometimes all it takes is a 15-minute walk to reset your entire day. Made with Seedance 2.0 on TapNow Prompt: Create a 15-second ultra-realistic, fast-paced cinematic lifestyle vlog. A beautiful 23-year-old female influencer wearing white T shirt with black short is on her morning walk in a lush green park during golden sunrise. The editing is energetic with quick 1–2 second cuts, smooth gimbal shots, dynamic transitions, speed ramps, and cinematic close-ups. The vibe is fresh, motivating, and aesthetic, similar to viral Instagram Reels and TikTok lifestyle content. Scene 1 (0–2 sec): Close-up of her tying her white sneakers, grabbing a water bottle, and opening the park gate. Dialogue: "Morning reset... let's go!" Scene 2 (2–5 sec): Selfie shot while walking confidently through the park with sunlight behind her. Dialogue: "Nothing beats fresh air at sunrise." Scene 3 (5–8 sec): Fast montage of her walking, smiling, birds flying, trees swaying, smartwatch tracking steps, and shoes hitting the path. Dialogue: "Just fifteen minutes can completely change your mood." Scene 4 (8–12 sec): Slow-motion hair flip, laughing, stretching, and enjoying the golden sunlight. Dialogue: "Move your body... clear your mind." Scene 5 (12–15 sec): She turns toward the camera with a bright smile and gives a thumbs-up while continuing her walk. Dialogue: "See you tomorrow for another morning reset!" Style: Hyper-realistic , cinematic golden-hour lighting, vibrant colors, luxury influencer aesthetic, ultra-smooth camera movement, quick jump cuts, speed ramps, natural expressions, realistic lip sync, shallow depth of field, crisp ambient nature sounds, high-energy editing, no text overlays, no logos, no watermarks.
0:15

Golden mornings. Fresh air. Clear mind. 🌅✨ Sometimes all it takes is a 15-minute walk to reset your entire day. Made with Seedance 2.0 on TapNow Prompt: Create a 15-second ultra-realistic, fast-paced cinematic lifestyle vlog. A beautiful 23-year-old female influencer wearing white T shirt with black short is on her morning walk in a lush green park during golden sunrise. The editing is energetic with quick 1–2 second cuts, smooth gimbal shots, dynamic transitions, speed ramps, and cinematic close-ups. The vibe is fresh, motivating, and aesthetic, similar to viral Instagram Reels and TikTok lifestyle content. Scene 1 (0–2 sec): Close-up of her tying her white sneakers, grabbing a water bottle, and opening the park gate. Dialogue: "Morning reset... let's go!" Scene 2 (2–5 sec): Selfie shot while walking confidently through the park with sunlight behind her. Dialogue: "Nothing beats fresh air at sunrise." Scene 3 (5–8 sec): Fast montage of her walking, smiling, birds flying, trees swaying, smartwatch tracking steps, and shoes hitting the path. Dialogue: "Just fifteen minutes can completely change your mood." Scene 4 (8–12 sec): Slow-motion hair flip, laughing, stretching, and enjoying the golden sunlight. Dialogue: "Move your body... clear your mind." Scene 5 (12–15 sec): She turns toward the camera with a bright smile and gives a thumbs-up while continuing her walk. Dialogue: "See you tomorrow for another morning reset!" Style: Hyper-realistic , cinematic golden-hour lighting, vibrant colors, luxury influencer aesthetic, ultra-smooth camera movement, quick jump cuts, speed ramps, natural expressions, realistic lip sync, shallow depth of field, crisp ambient nature sounds, high-energy editing, no text overlays, no logos, no watermarks.

Maria

17,855 Aufrufe • vor 2 Monaten

🟥 𝗣𝗼𝗰𝗸𝗲𝘁𝗙𝗶 𝟮.𝟬 𝗶𝘀 𝗛𝗘𝗥𝗘 — 𝘁𝗿𝗮𝗱𝗲 𝗦𝗼𝗹𝗮𝗻𝗮 𝘁𝗼𝗸𝗲𝗻𝘀 𝘃𝗶𝗮 𝗧𝗢𝗡 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 With PocketFi 2.0, we’ve unlocked the 𝗳𝘂𝗹𝗹 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 Solana for the TON community, transforming your everyday crypto experience into digital art. Start your Solana journey with PocketFi 2.0 💰 𝗧𝗢𝗡 ↔ 𝗦𝗼𝗹𝗮𝗻𝗮 💰 Swap tokens, explore top protocols, and top up Solana directly from your TON wallet. 💎 𝗚𝗮𝘀𝗹𝗲𝘀𝘀 𝘀𝘄𝗮𝗽𝘀 & 𝗯𝗲𝘀𝘁-𝗽𝗿𝗶𝗰𝗲 𝗿𝗼𝘂𝘁𝗶𝗻𝗴 We cover all fees, manage rent, and route your trade for the best deal — all in USDC, no SOL required. 🌍 𝗔𝘂𝘁𝗼𝗽𝗶𝗹𝗼𝘁: 𝗯𝘂𝘆 𝘀𝗺𝗮𝗿𝘁, 𝗰𝗵𝗶𝗹𝗹 𝗵𝗮𝗿𝗱 Set up auto-buys for any Solana asset and average your entry price with gradual, low-risk stacking. 📁 𝗘𝘅𝗽𝗼𝗿𝘁 𝗦𝗼𝗹𝗮𝗻𝗮 𝘄𝗮𝗹𝗹𝗲𝘁 You can export Solana seed phrase anytime in settings — full control, whenever you need it. 🤩 …and of course new ref rewards. Invite your friends and get lifetime rewards — 𝘂𝗽 𝘁𝗼 𝟯𝟬% of their trading fees go to you. 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗠𝗼𝗿𝗲: ▫️ Instantly switch between TON and Solana right from the home screen. ▫️ Track everything in the History tab — from deposits to Autopilot setups. ▫️ Flex your PnL with the community using the Share button in the Holdings tab. ▫️ View token data, favorite assets, and share them — all in one place on the token screen. ▫️ Always get the best price — smart routing finds top Solana DEX offers for you. ▫️ No guessing slippage — we auto-adjust it based on market conditions. ▫️ No stuck tokens — we handle rent and clean up unused accounts for you. 🟥 𝗧𝗵𝗲 𝗻𝗲𝘄 𝗧𝗢𝗡 𝗲𝗿𝗮 𝗶𝘀 𝗹𝗶𝘃𝗲 — 𝘁𝗿𝘆 𝗣𝗼𝗰𝗸𝗲𝘁𝗙𝗶 𝟮.𝟬 𝘁𝗼𝗱𝗮𝘆.
0:14

🟥 𝗣𝗼𝗰𝗸𝗲𝘁𝗙𝗶 𝟮.𝟬 𝗶𝘀 𝗛𝗘𝗥𝗘 — 𝘁𝗿𝗮𝗱𝗲 𝗦𝗼𝗹𝗮𝗻𝗮 𝘁𝗼𝗸𝗲𝗻𝘀 𝘃𝗶𝗮 𝗧𝗢𝗡 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 With PocketFi 2.0, we’ve unlocked the 𝗳𝘂𝗹𝗹 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 Solana for the TON community, transforming your everyday crypto experience into digital art. Start your Solana journey with PocketFi 2.0 💰 𝗧𝗢𝗡 ↔ 𝗦𝗼𝗹𝗮𝗻𝗮 💰 Swap tokens, explore top protocols, and top up Solana directly from your TON wallet. 💎 𝗚𝗮𝘀𝗹𝗲𝘀𝘀 𝘀𝘄𝗮𝗽𝘀 & 𝗯𝗲𝘀𝘁-𝗽𝗿𝗶𝗰𝗲 𝗿𝗼𝘂𝘁𝗶𝗻𝗴 We cover all fees, manage rent, and route your trade for the best deal — all in USDC, no SOL required. 🌍 𝗔𝘂𝘁𝗼𝗽𝗶𝗹𝗼𝘁: 𝗯𝘂𝘆 𝘀𝗺𝗮𝗿𝘁, 𝗰𝗵𝗶𝗹𝗹 𝗵𝗮𝗿𝗱 Set up auto-buys for any Solana asset and average your entry price with gradual, low-risk stacking. 📁 𝗘𝘅𝗽𝗼𝗿𝘁 𝗦𝗼𝗹𝗮𝗻𝗮 𝘄𝗮𝗹𝗹𝗲𝘁 You can export Solana seed phrase anytime in settings — full control, whenever you need it. 🤩 …and of course new ref rewards. Invite your friends and get lifetime rewards — 𝘂𝗽 𝘁𝗼 𝟯𝟬% of their trading fees go to you. 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗠𝗼𝗿𝗲: ▫️ Instantly switch between TON and Solana right from the home screen. ▫️ Track everything in the History tab — from deposits to Autopilot setups. ▫️ Flex your PnL with the community using the Share button in the Holdings tab. ▫️ View token data, favorite assets, and share them — all in one place on the token screen. ▫️ Always get the best price — smart routing finds top Solana DEX offers for you. ▫️ No guessing slippage — we auto-adjust it based on market conditions. ▫️ No stuck tokens — we handle rent and clean up unused accounts for you. 🟥 𝗧𝗵𝗲 𝗻𝗲𝘄 𝗧𝗢𝗡 𝗲𝗿𝗮 𝗶𝘀 𝗹𝗶𝘃𝗲 — 𝘁𝗿𝘆 𝗣𝗼𝗰𝗸𝗲𝘁𝗙𝗶 𝟮.𝟬 𝘁𝗼𝗱𝗮𝘆.

XPocket

232,529 Aufrufe • vor 1 Jahr

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.
0:13

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.

West Lord

592,877 Aufrufe • vor 2 Monaten

🎉 Over 100,000 Users & OptimAI Lite Node v1.1 Released—Edge Node Coming Soon! Get OptimAI Lite Node v1.1 now: 🌐Chrome Extension: 📱Telegram Mini-app: In just 10 days since launching the OptimAI Lite Node on Chrome Extension and Telegram Mini-app, we’ve surpassed 100,000 active node participants—an incredible milestone thanks to your amazing support! ✨ OptimAI Lite Node v1.1 is now LIVE with significant upgrades: + Enhanced network stability for handling massive concurrent connections. + Improved UI for a smoother, more intuitive user experience. + Making your node experience smoother, more stable, and just plain better. + Automatic updates on Chrome and Telegram—no manual action required. 💡Our Chrome Extension has successfully passed rigorous testing by the Chrome Web Store, demonstrating industry-leading security and transparency. You're always in control, always secure! 🌟Up Next: OptimAI Edge Node for Mobile! We’re working diligently to launch the Edge Node—bringing decentralized AI computing directly to your mobile device. Exciting updates coming soon, so stay tuned! OptimAI Network: #L2 #DePIN Reinforcement Data Network for #Agentic #AI. ⭐ Mine Data. Fuel AI. Earn Rewards. ⭐ Turn Your Data into Tomorrow’s AI #Agent. Learn more at our website:
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🎉 Over 100,000 Users & OptimAI Lite Node v1.1 Released—Edge Node Coming Soon! Get OptimAI Lite Node v1.1 now: 🌐Chrome Extension: 📱Telegram Mini-app: In just 10 days since launching the OptimAI Lite Node on Chrome Extension and Telegram Mini-app, we’ve surpassed 100,000 active node participants—an incredible milestone thanks to your amazing support! ✨ OptimAI Lite Node v1.1 is now LIVE with significant upgrades: + Enhanced network stability for handling massive concurrent connections. + Improved UI for a smoother, more intuitive user experience. + Making your node experience smoother, more stable, and just plain better. + Automatic updates on Chrome and Telegram—no manual action required. 💡Our Chrome Extension has successfully passed rigorous testing by the Chrome Web Store, demonstrating industry-leading security and transparency. You're always in control, always secure! 🌟Up Next: OptimAI Edge Node for Mobile! We’re working diligently to launch the Edge Node—bringing decentralized AI computing directly to your mobile device. Exciting updates coming soon, so stay tuned! OptimAI Network: #L2 #DePIN Reinforcement Data Network for #Agentic #AI. ⭐ Mine Data. Fuel AI. Earn Rewards. ⭐ Turn Your Data into Tomorrow’s AI #Agent. Learn more at our website:

OptimAI Network

224,886 Aufrufe • vor 1 Jahr

BREAKING: LLMs just learned to COMPUTE for real, it's mean NO MORE GUESSING math. Chinese college kid Guo Hanjiang vibe-coded MiroFish in 10 days (23k+ GitHub stars, $4.1M from Shanda in 24h) - the AI swarm simulator that’s already printing. ByteDance (VolcEngine) dropped the nuclear upgrade: OpenViking - structured viking:// filesystem memory (L0 ultra-summary -> L2 full details) - agents now run 100+ steps with zero amnesia or hallucinations, 11.6k stars and climbing. Now this just dropped and the entire AI timeline is shaking. Startup Percepta embedded a full WASM virtual machine directly into Transformer weights. No more external Python sandboxes. No more hallucinations in exact tasks. The model streams raw machine code at 30,000+ tokens/sec on CPU, executes millions of steps, and solves the world’s hardest Sudoku via real backtracking + constraint propagation - 100% accurate, zero bullshit. They killed the Attention Bottleneck with Exponentially Fast Attention (HullKVCache + 2D heads + convex hull queries in log time). What used to die at 1k steps now flies. This is the bridge: System 1 intuition (normal LLMs) + System 2 deterministic logic (native code execution) in ONE brain. Agents won’t need tools anymore. Heavy simulations will run inside the weights. Check out: Now put it all together: MiroFish swarms + OpenViking infinite memory + Percepta native flawless compute = agents that can hardcore simulate millions of future scenarios, run perfect logic loops for days, and predict events/markets/reality with god-tier accuracy. No drift. No bullshit. Just pure foresight. This combo will change everything, imo. The era of predictive super-agents that actually print the future is here. We’re watching this one closely. Save this combo.
0:14

BREAKING: LLMs just learned to COMPUTE for real, it's mean NO MORE GUESSING math. Chinese college kid Guo Hanjiang vibe-coded MiroFish in 10 days (23k+ GitHub stars, $4.1M from Shanda in 24h) - the AI swarm simulator that’s already printing. ByteDance (VolcEngine) dropped the nuclear upgrade: OpenViking - structured viking:// filesystem memory (L0 ultra-summary -> L2 full details) - agents now run 100+ steps with zero amnesia or hallucinations, 11.6k stars and climbing. Now this just dropped and the entire AI timeline is shaking. Startup Percepta embedded a full WASM virtual machine directly into Transformer weights. No more external Python sandboxes. No more hallucinations in exact tasks. The model streams raw machine code at 30,000+ tokens/sec on CPU, executes millions of steps, and solves the world’s hardest Sudoku via real backtracking + constraint propagation - 100% accurate, zero bullshit. They killed the Attention Bottleneck with Exponentially Fast Attention (HullKVCache + 2D heads + convex hull queries in log time). What used to die at 1k steps now flies. This is the bridge: System 1 intuition (normal LLMs) + System 2 deterministic logic (native code execution) in ONE brain. Agents won’t need tools anymore. Heavy simulations will run inside the weights. Check out: Now put it all together: MiroFish swarms + OpenViking infinite memory + Percepta native flawless compute = agents that can hardcore simulate millions of future scenarios, run perfect logic loops for days, and predict events/markets/reality with god-tier accuracy. No drift. No bullshit. Just pure foresight. This combo will change everything, imo. The era of predictive super-agents that actually print the future is here. We’re watching this one closely. Save this combo.

slash1s

156,699 Aufrufe • vor 5 Monaten

A cinematic AI-powered visual experience showcasing how imagination can be transformed into stunning digital worlds From futuristic environments and creative fashion visuals to seamless character transformations every scene blends technology creativity, and storytelling into one immersive piece. Made with MiniMaxH3 on WeryAI Wery Prompt: A stylish young South Asian woman with long dark hair, natural glamorous makeup and an elegant modern outfit. Keep her face, hairstyle, outfit and appearance consistent throughout the entire video. Scene 1 — 0–4s: She sits at a sleek modern workstation in a futuristic studio. She looks directly into the camera and says naturally: “What if you could turn your ideas into reality in just a few clicks?” Natural facial expressions and hand gestures. Slow cinematic camera push-in. Perfect lip-sync. Scene 2 — 4–7s: She turns to her computer and opens WeryAI. She types a creative idea and says: “That’s exactly what I love about WeryAI.” The interface responds with elegant AI processing animations and glowing digital effects. Scene 3 — 7–11s: Her simple idea transforms into stunning AI-generated visuals: a fashion scene, futuristic city, cinematic character, premium product advertisement and social-media video. She looks impressed and says: “Give it an idea, and watch it come to life.” Use smooth cinematic transitions and dynamic camera movement. Scene 4 — 11–15s: She turns back toward the camera with a confident smile and says: “WeryAI. Your imagination, powered by AI.” The camera slowly pulls back as the WeryAI brand reveal appears with a clean futuristic glow. Audio: Natural confident female voice, warm energetic delivery, subtle futuristic background music and soft cinematic sound effects. Keep dialogue clear and prominent. Lip-sync: The woman must visibly speak every line with accurate lip synchronization, natural mouth movement, blinking and facial expressions. Visual quality: Photorealistic, cinematic 4K, realistic skin, smooth camera movement, premium lighting, shallow depth of field, consistent character. No subtitles, no distorted face, no warped hands, no extra fingers, no flickering, no random text, no watermark.
0:15

A cinematic AI-powered visual experience showcasing how imagination can be transformed into stunning digital worlds From futuristic environments and creative fashion visuals to seamless character transformations every scene blends technology creativity, and storytelling into one immersive piece. Made with MiniMaxH3 on WeryAI Wery Prompt: A stylish young South Asian woman with long dark hair, natural glamorous makeup and an elegant modern outfit. Keep her face, hairstyle, outfit and appearance consistent throughout the entire video. Scene 1 — 0–4s: She sits at a sleek modern workstation in a futuristic studio. She looks directly into the camera and says naturally: “What if you could turn your ideas into reality in just a few clicks?” Natural facial expressions and hand gestures. Slow cinematic camera push-in. Perfect lip-sync. Scene 2 — 4–7s: She turns to her computer and opens WeryAI. She types a creative idea and says: “That’s exactly what I love about WeryAI.” The interface responds with elegant AI processing animations and glowing digital effects. Scene 3 — 7–11s: Her simple idea transforms into stunning AI-generated visuals: a fashion scene, futuristic city, cinematic character, premium product advertisement and social-media video. She looks impressed and says: “Give it an idea, and watch it come to life.” Use smooth cinematic transitions and dynamic camera movement. Scene 4 — 11–15s: She turns back toward the camera with a confident smile and says: “WeryAI. Your imagination, powered by AI.” The camera slowly pulls back as the WeryAI brand reveal appears with a clean futuristic glow. Audio: Natural confident female voice, warm energetic delivery, subtle futuristic background music and soft cinematic sound effects. Keep dialogue clear and prominent. Lip-sync: The woman must visibly speak every line with accurate lip synchronization, natural mouth movement, blinking and facial expressions. Visual quality: Photorealistic, cinematic 4K, realistic skin, smooth camera movement, premium lighting, shallow depth of field, consistent character. No subtitles, no distorted face, no warped hands, no extra fingers, no flickering, no random text, no watermark.

Calira

12,635 Aufrufe • vor 16 Tagen

🚨This is insane… this guy built a clawdbot that flipped $69 into $1M+ on POLYMARKET Sounds insane? 100%. Fake? Not even remotely. If you trade on Polymarket, this should have YOUR focus. A fresh wallet just surfaced with 22,173 resolved predictions and $1,013,168 in PNL It trades strictly in NEW 5-minute & 15-minute crypto markets Profile → COPYTRADE → Weekly profit is sitting around ~$100,000 And what powers it is almost offensively simple I reviewed the entire setup No sophisticated ML stacks No institutional-grade systems No complex data pipelines Just automated execution paired with statistical edge His COMPLETE playbook: 1. Ultra-short timeframes Only 5-min Up/Down contracts. Locked into 5 & 15m markets exclusively. Clawdbot-style execution framework. Pure intraday momentum extraction. No swing positions. No storytelling. Just speed and repetition 2. Order splitting + micro sizing Every position is broken into multiple small entries. Fixed predefined size per fill. Size scales only when conviction increases. This limits drawdowns and smooths the equity curve 3. Probability farming The model doesn’t hunt for moonshots. It stacks small mathematical edges. Over thousands of trades = that compounds into six figures monthly Largest trade so far: “Bitcoin Up or Down - January 19, 5-6AM ET” $13,320 → $36,887 (+176%) Now the important part: This can be replicated cursor + py-clob-client + python install the SDK generate Polymarket API keys define the Clawdbot strategy prompt AI builds the Clawdbot execution logic paper test with $1 You don’t need elite discretionary skill Bottom line Why are you still trading manually while automated systems run 24/7?
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🚨This is insane… this guy built a clawdbot that flipped $69 into $1M+ on POLYMARKET Sounds insane? 100%. Fake? Not even remotely. If you trade on Polymarket, this should have YOUR focus. A fresh wallet just surfaced with 22,173 resolved predictions and $1,013,168 in PNL It trades strictly in NEW 5-minute & 15-minute crypto markets Profile → COPYTRADE → Weekly profit is sitting around ~$100,000 And what powers it is almost offensively simple I reviewed the entire setup No sophisticated ML stacks No institutional-grade systems No complex data pipelines Just automated execution paired with statistical edge His COMPLETE playbook: 1. Ultra-short timeframes Only 5-min Up/Down contracts. Locked into 5 & 15m markets exclusively. Clawdbot-style execution framework. Pure intraday momentum extraction. No swing positions. No storytelling. Just speed and repetition 2. Order splitting + micro sizing Every position is broken into multiple small entries. Fixed predefined size per fill. Size scales only when conviction increases. This limits drawdowns and smooths the equity curve 3. Probability farming The model doesn’t hunt for moonshots. It stacks small mathematical edges. Over thousands of trades = that compounds into six figures monthly Largest trade so far: “Bitcoin Up or Down - January 19, 5-6AM ET” $13,320 → $36,887 (+176%) Now the important part: This can be replicated cursor + py-clob-client + python install the SDK generate Polymarket API keys define the Clawdbot strategy prompt AI builds the Clawdbot execution logic paper test with $1 You don’t need elite discretionary skill Bottom line Why are you still trading manually while automated systems run 24/7?

Shelpid.WI3M

10,521 Aufrufe • vor 6 Monaten

90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.
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90% of "AI developers" just download pre packaged GGUF files from Hugging Face, hit run, and call it a day. The top 10% know how to pull the raw safetensors, run the math, and quantize massive models into Q4_K_M themselves. If you think llama.cpp can only execute models, you’re missing the best part of the open source ecosystem. It’s a high performance optimization suite. Manually stripping 69% of the VRAM footprint off a brand new model architecture is where real infrastructure value is made. If you want to actually master local inference and deploy models like Google’s massive Gemma 4 12B it on consumer NVIDIA hardware using llama.cpp, you need to learn this pipeline. Let's build it. I just took the raw 22.7 GB Gemma 4 baseline and manually compressed it down to a 7.02 GB Q4_K_M GGUF artifact using llama.cpp. That is a 69% reduction in footprint. No quality loss. No VRAM bottlenecks. Just native, hardware accelerated C++ inference running a full 2,50,000 token context window on a dual NVIDIA Tesla T4 setup. Stop melting your VRAM on unoptimized weights and stop relying on other people's pipelines. Own your stack. I mapped this entire architecture from dynamic binary fetching to raw quantization and real time GPU streaming into a single, bulletproof notebook. Notebook link is in the comments below. Bookmark this blueprint for your next deployment and tell me which quantization works best for your workflow and model.

Alok

62,631 Aufrufe • vor 1 Monat

Free NVIDIA GPU with 16 GB VRAM GPU for Running Local LLMs! If you want to master local LLMs but you're waiting until you can afford a $1,500 GPU, you're honestly not going to make it. The open source AI ecosystem is moving way too fast for you to wait on your budget to catch up. Especially when you can build a bleeding edge inference engine from scratch right now, completely for free. You don't need a heavy local rig to start. Google is literally letting you use an enterprise grade NVIDIA Tesla T4 GPU for $0/hour. At standard cloud computing rates (~$0.20/hr), Google Colab’s 4 hour daily free tier hands you roughly $24 worth of data center tier GPU compute every single month. And most people just waste it. Let’s talk about the hardware you get access to for free. The NVIDIA Tesla T4 is an absolute workhorse: - Architecture: NVIDIA Turing (TU104) - VRAM: 16GB GDDR6 (320 GB/s bandwidth) - Compute: 320 Tensor Cores | 2560 CUDA Cores - Performance: 130 TOPS INT8 | 8.1 TFLOPS FP32 - Power: Sipping energy at a max 70W TDP This is the exact same hardware I used to run DeepMind's Gemma 4 26B A4B QAT MoE at a 250,000 context window without a single Out Of Memory (OOM) crash. If you have a web browser and 10 minutes, you have everything you need. I’ve put together a fully documented, cell by cell Google Colab notebook that teaches you exactly how to do this. Here is what the notebook actually teaches you: - How to provision an Ubuntu Linux environment with CUDA 13.0 and verify your driver stack. - How to pull the source code and compile the latest llama.cpp C++ binaries from scratch, specifically optimizing the build for your exact GPU using the -DCMAKE_CUDA_ARCHITECTURES=native flag. - How to directly download quantized local LLMs (GGUF format) straight from HuggingFace using the CLI. - How to manage 16GB VRAM limits, offload neural network layers to the GPU, and push massive context windows. Compile raw llama.cpp, ollama run a model, or spin up the LM Studio CLI. Pick whatever stack you are comfortable with. just start building. No hardware. No credit card. No excuses. Bookmark this post right now so you don't lose the tutorial. Even if you don't have time to run it today, you are going to want this workflow in your engineering toolkit. The link to the free Colab Notebook is in the comments below. Lemme know if you need more tutorials like this.
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Free NVIDIA GPU with 16 GB VRAM GPU for Running Local LLMs! If you want to master local LLMs but you're waiting until you can afford a $1,500 GPU, you're honestly not going to make it. The open source AI ecosystem is moving way too fast for you to wait on your budget to catch up. Especially when you can build a bleeding edge inference engine from scratch right now, completely for free. You don't need a heavy local rig to start. Google is literally letting you use an enterprise grade NVIDIA Tesla T4 GPU for $0/hour. At standard cloud computing rates (~$0.20/hr), Google Colab’s 4 hour daily free tier hands you roughly $24 worth of data center tier GPU compute every single month. And most people just waste it. Let’s talk about the hardware you get access to for free. The NVIDIA Tesla T4 is an absolute workhorse: - Architecture: NVIDIA Turing (TU104) - VRAM: 16GB GDDR6 (320 GB/s bandwidth) - Compute: 320 Tensor Cores | 2560 CUDA Cores - Performance: 130 TOPS INT8 | 8.1 TFLOPS FP32 - Power: Sipping energy at a max 70W TDP This is the exact same hardware I used to run DeepMind's Gemma 4 26B A4B QAT MoE at a 250,000 context window without a single Out Of Memory (OOM) crash. If you have a web browser and 10 minutes, you have everything you need. I’ve put together a fully documented, cell by cell Google Colab notebook that teaches you exactly how to do this. Here is what the notebook actually teaches you: - How to provision an Ubuntu Linux environment with CUDA 13.0 and verify your driver stack. - How to pull the source code and compile the latest llama.cpp C++ binaries from scratch, specifically optimizing the build for your exact GPU using the -DCMAKE_CUDA_ARCHITECTURES=native flag. - How to directly download quantized local LLMs (GGUF format) straight from HuggingFace using the CLI. - How to manage 16GB VRAM limits, offload neural network layers to the GPU, and push massive context windows. Compile raw llama.cpp, ollama run a model, or spin up the LM Studio CLI. Pick whatever stack you are comfortable with. just start building. No hardware. No credit card. No excuses. Bookmark this post right now so you don't lose the tutorial. Even if you don't have time to run it today, you are going to want this workflow in your engineering toolkit. The link to the free Colab Notebook is in the comments below. Lemme know if you need more tutorials like this.

Alok

178,744 Aufrufe • vor 2 Monaten