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We just built a live bridge between Substance Painter and UEFN. 🎨→🎮 Paint in Substance → click Sync → see it in UEFN. In real time. • Auto FBX import + spawn • PBR Material with Material Instances (no recompile on sync) • Smart sync only changed textures get... show more

Surprise KiKoZl

1,195 subscribers

13,478 次观看 • 6 个月前 •via X (Twitter)

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MiaoYan is a lightweight, native macOS Markdown editor for writing and notes — one of my open-source macOS projects. It just shipped its biggest update to date, introducing Split View for side-by-side Markdown editing and live preview, with smooth bidirectional scroll sync. This release also brings a full visual refinement, layout cycling between sidebar, list, and focus modes, faster startup with native window animations, and broad performance improvements across editing, preview, and export. Built entirely in Swift, not Electron. MiaoYan is local-first, requires no account, collects no telemetry, and avoids AI features by design. I built it for clean Markdown, performance, and a calm writing environment.

MiaoYan is a lightweight, native macOS Markdown editor for writing and notes — one of my open-source macOS projects. It just shipped its biggest update to date, introducing Split View for side-by-side Markdown editing and live preview, with smooth bidirectional scroll sync. This release also brings a full visual refinement, layout cycling between sidebar, list, and focus modes, faster startup with native window animations, and broad performance improvements across editing, preview, and export. Built entirely in Swift, not Electron. MiaoYan is local-first, requires no account, collects no telemetry, and avoids AI features by design. I built it for clean Markdown, performance, and a calm writing environment.

Tw93

34,665 次观看 • 8 个月前

Real time transactions are coming to Abstract. In this demo, we built a simple cookie clicker where every click is an onchain transaction. You can see each transaction happen immediately with almost no delay. A web2 UX secured by a blockchain under the hood. This is how every app on Abstract will be built in the near future. This particular demo leverages AGW and session keys to remove the need for wallet popups. It uses a special RPC endpoint (which will be live on our mainnet soon) to fetch transaction statuses ahead of time.

Real time transactions are coming to Abstract. In this demo, we built a simple cookie clicker where every click is an onchain transaction. You can see each transaction happen immediately with almost no delay. A web2 UX secured by a blockchain under the hood. This is how every app on Abstract will be built in the near future. This particular demo leverages AGW and session keys to remove the need for wallet popups. It uses a special RPC endpoint (which will be live on our mainnet soon) to fetch transaction statuses ahead of time.

cygaar

56,166 次观看 • 1 年前

Building RAG is easy. Parsing real, unstructured data is the hard part. Most tools fail when documents get complicated. RAGFlow by InfiniFlow makes the entire process visual and flawless 🔥 It is an (open-source!) engine built specifically to find the exact needle in a data haystack, even across literally unlimited tokens. The platform comes packed with: → "Quality in, quality out" parsing for highly complex formats → Multiple recall paired with fused re-ranking → A built-in Python and JavaScript code executor for agents → An orchestrable ingestion pipeline Here's why it stands out: 1️⃣ Structural Understanding Instead of just scraping text, it handles tables across pages, scanned copies, slides, and Excel sheets natively using deep document understanding. 2️⃣ Grounded Citations Every answer is verifiable. The UI highlights the exact chunks used, allowing you to trace any response directly back to the source material. 3️⃣ Enterprise Synchronization Keep your context constantly updated with native data sync from Google Drive, Notion, Discord, and Confluence. Stop letting bad document parsing ruin your RAG systems. Best part? It's 100% Free and open-source. Link to the repo in 🧵↓

Building RAG is easy. Parsing real, unstructured data is the hard part. Most tools fail when documents get complicated. RAGFlow by InfiniFlow makes the entire process visual and flawless 🔥 It is an (open-source!) engine built specifically to find the exact needle in a data haystack, even across literally unlimited tokens. The platform comes packed with: → "Quality in, quality out" parsing for highly complex formats → Multiple recall paired with fused re-ranking → A built-in Python and JavaScript code executor for agents → An orchestrable ingestion pipeline Here's why it stands out: 1️⃣ Structural Understanding Instead of just scraping text, it handles tables across pages, scanned copies, slides, and Excel sheets natively using deep document understanding. 2️⃣ Grounded Citations Every answer is verifiable. The UI highlights the exact chunks used, allowing you to trace any response directly back to the source material. 3️⃣ Enterprise Synchronization Keep your context constantly updated with native data sync from Google Drive, Notion, Discord, and Confluence. Stop letting bad document parsing ruin your RAG systems. Best part? It's 100% Free and open-source. Link to the repo in 🧵↓

Charly Wargnier

19,220 次观看 • 6 个月前

Two girls, arms overhead all day, plastering a ceiling in perfect sync and it makes them around $12,000 a month between them, mostly from filming it. Anyone who's done overhead work knows it's the worst position in the trade — arms up, neck back, shoulders burning inside ten minutes. Most people tap out. These two do it for hours, side by side, matching each other's pace like they share a brain. That's the thing you can't look away from: not just that it's two women on a ceiling, but that they're in rhythm doing the part everyone else dreads. Here's why the pair matters more than people think. A solo worker is a clip you watch once. Two people moving in sync — no talking, just anticipating each other — is a relationship, and relationships are what turn a viewer into a follower. You're not watching a task get done. You're watching a partnership work, and that pulls people back for the next one. The money runs three ways off one phone. Their calendar stays booked because homeowners watch the finish and hire them at full rate, zero ad spend — the video sells the work. Tool and material brands pay $3 - 5k a post to get their gear in genuinely skilled hands. And views, often 5-10 million a clip, stack payouts on a phone one of them wedges on a bucket. Neither of them edits. They film the shift, hand it to AI, it grabs the tightest synced stretch, cuts it to the beat, captions, schedules. They're onto the next room before it posts. The reframe for anyone doing hard work: the part of your job that's physically brutal — the part you assume nobody wants to see — is exactly what people respect watching. Struggle that looks effortless is magnetic. Doing it in sync with someone else doubles it. Do you work with someone you're so in sync with you barely need words? Drop it below — I'm breaking the best ones down next.

Two girls, arms overhead all day, plastering a ceiling in perfect sync and it makes them around $12,000 a month between them, mostly from filming it. Anyone who's done overhead work knows it's the worst position in the trade — arms up, neck back, shoulders burning inside ten minutes. Most people tap out. These two do it for hours, side by side, matching each other's pace like they share a brain. That's the thing you can't look away from: not just that it's two women on a ceiling, but that they're in rhythm doing the part everyone else dreads. Here's why the pair matters more than people think. A solo worker is a clip you watch once. Two people moving in sync — no talking, just anticipating each other — is a relationship, and relationships are what turn a viewer into a follower. You're not watching a task get done. You're watching a partnership work, and that pulls people back for the next one. The money runs three ways off one phone. Their calendar stays booked because homeowners watch the finish and hire them at full rate, zero ad spend — the video sells the work. Tool and material brands pay $3 - 5k a post to get their gear in genuinely skilled hands. And views, often 5-10 million a clip, stack payouts on a phone one of them wedges on a bucket. Neither of them edits. They film the shift, hand it to AI, it grabs the tightest synced stretch, cuts it to the beat, captions, schedules. They're onto the next room before it posts. The reframe for anyone doing hard work: the part of your job that's physically brutal — the part you assume nobody wants to see — is exactly what people respect watching. Struggle that looks effortless is magnetic. Doing it in sync with someone else doubles it. Do you work with someone you're so in sync with you barely need words? Drop it below — I'm breaking the best ones down next.

Rich

23,632 次观看 • 1 个月前

🚨BREAKING: Google just merged Gemini and NotebookLM into one unified workspace and it changes everything about how you use AI for deep work. It's called Notebooks in Gemini and it's the personal knowledge base that power users have been begging for. You create a notebook for a project, drop in your files, PDFs, and documents, give Gemini custom instructions, and every chat you have stays organized in one place. No more hunting through old conversations. No more re-uploading the same files every session. The wildest part is the sync. Anything you add in Gemini automatically appears in NotebookLM. Anything you add in NotebookLM automatically appears in Gemini. One source of truth. Two powerful apps. Zero friction switching between them. So you can start a research notebook in Gemini, ask it questions all week, then flip to NotebookLM to generate a Cinematic Video Overview from the same material. Next morning, open Gemini and ask it to write a full report on exactly what you just watched. That workflow used to take three apps and a lot of copy-pasting. Now it's one notebook. Rolling out this week to Google AI Ultra, Pro, and Plus subscribers on web. Mobile and free users coming soon. What do you think?

🚨BREAKING: Google just merged Gemini and NotebookLM into one unified workspace and it changes everything about how you use AI for deep work. It's called Notebooks in Gemini and it's the personal knowledge base that power users have been begging for. You create a notebook for a project, drop in your files, PDFs, and documents, give Gemini custom instructions, and every chat you have stays organized in one place. No more hunting through old conversations. No more re-uploading the same files every session. The wildest part is the sync. Anything you add in Gemini automatically appears in NotebookLM. Anything you add in NotebookLM automatically appears in Gemini. One source of truth. Two powerful apps. Zero friction switching between them. So you can start a research notebook in Gemini, ask it questions all week, then flip to NotebookLM to generate a Cinematic Video Overview from the same material. Next morning, open Gemini and ask it to write a full report on exactly what you just watched. That workflow used to take three apps and a lot of copy-pasting. Now it's one notebook. Rolling out this week to Google AI Ultra, Pro, and Plus subscribers on web. Mobile and free users coming soon. What do you think?

Mayank Vora

136,834 次观看 • 5 个月前

Someone is vibe coding a live 3D news globe with Claude Code that pins real world events on a spinning Earth as they happen. Instead of doomscrolling a feed, you open a tab with a 3D Earth and watch the world light up in real time. Breaking news, conflicts, disasters and humanitarian alerts get pinned to the exact spot on the map, alongside live flights and upcoming rocket launches. Click any event and it pulls up a short brief with its actual sources, so you can see where it came from. People are already saying it's the only way they want to read news now, the kind of thing you keep open in a tab and just glance at all day.

Someone is vibe coding a live 3D news globe with Claude Code that pins real world events on a spinning Earth as they happen. Instead of doomscrolling a feed, you open a tab with a 3D Earth and watch the world light up in real time. Breaking news, conflicts, disasters and humanitarian alerts get pinned to the exact spot on the map, alongside live flights and upcoming rocket launches. Click any event and it pulls up a short brief with its actual sources, so you can see where it came from. People are already saying it's the only way they want to read news now, the kind of thing you keep open in a tab and just glance at all day.

0xMarioNawfal

39,104 次观看 • 3 个月前

If you think this is just another silly demo made with AI, read this post. You might change your mind, because this demo is about MATH. What you see on the screen is not a render from Blender (obviously, it’s not that good). It’s a three.js app built with Toolcraft. Available on the web and rendered in real time(link in the comments). But Blender still has a lot to do with it. Blender has Geometry Nodes - a powerful node-based system for creating and manipulating procedural geometry. In other words, it’s math. And math is a universal language. And who do you think is pretty good at math? >>> AI. Now you can download or buy Blender files from marketplaces, and when they contain Geometry Nodes for procedural animations, objects, surfaces, or effects, you can transfer that logic to the web. Make it real-time, make it interactive. Materials are a separate story, of course. They can still suck unless you use the right tricks: PBR, HDRIs, material blending, displacement, and faked surface relief. So why is Blender important here? Blender is open source, and many tools around it are open source too. An AI trained on their code. That means it can translate the math from one environment to another quite accurately. If you’ve been struggling to reproduce some idea with AI that you had in your head or seen in some references, and it has something to do with Geometry Nodes, and you can find that idea or a close one in the Blender ecosystem - it means you can transfer it to the web. Thank me later.

If you think this is just another silly demo made with AI, read this post. You might change your mind, because this demo is about MATH. What you see on the screen is not a render from Blender (obviously, it’s not that good). It’s a three.js app built with Toolcraft. Available on the web and rendered in real time(link in the comments). But Blender still has a lot to do with it. Blender has Geometry Nodes - a powerful node-based system for creating and manipulating procedural geometry. In other words, it’s math. And math is a universal language. And who do you think is pretty good at math? >>> AI. Now you can download or buy Blender files from marketplaces, and when they contain Geometry Nodes for procedural animations, objects, surfaces, or effects, you can transfer that logic to the web. Make it real-time, make it interactive. Materials are a separate story, of course. They can still suck unless you use the right tricks: PBR, HDRIs, material blending, displacement, and faked surface relief. So why is Blender important here? Blender is open source, and many tools around it are open source too. An AI trained on their code. That means it can translate the math from one environment to another quite accurately. If you’ve been struggling to reproduce some idea with AI that you had in your head or seen in some references, and it has something to do with Geometry Nodes, and you can find that idea or a close one in the Blender ecosystem - it means you can transfer it to the web. Thank me later.

Alex Barashkov

28,300 次观看 • 2 个月前

Apple spent 7 years and $3,500 per unit building Vision Pro, this guy did something better with a webcam in his bedroom. And no, this isn't a render, it's running live on his laptop right now with a webcam pointed at his hands. The webcam tracks 21 points on each of his hands in real time, every fingertip, every knuckle, every joint, mapped to a 3D skeleton at 60 frames per second. A piece of digital silk is rigged to that skeleton, so when he opens his palm the fabric drapes across his fingers, when he closes his hand it crumples in his fist, when he tilts his wrist the cloth slides off and folds with real physics, light reflecting off it like actual material. He can grab it, stretch it, throw it, catch it, all with his bare hands and zero hardware on his body. No headset, no gloves, no $3,500 face computer, no 600 gram brick on his skull, no 2 hour battery, no Apple ID, no App Store. Just a webcam, TouchDesigner and a kid who saw the Vision Pro keynote and thought, I can do that for free. Apple has 3,000 engineers, $200 billion in cash and 7 years of development time, they built a face computer most people will never own. This guy has a laptop, a webcam and a weekend, he built a future most people can actually use. The mixed reality industry just got embarrassed by a guy in a white t-shirt.

Apple spent 7 years and $3,500 per unit building Vision Pro, this guy did something better with a webcam in his bedroom. And no, this isn't a render, it's running live on his laptop right now with a webcam pointed at his hands. The webcam tracks 21 points on each of his hands in real time, every fingertip, every knuckle, every joint, mapped to a 3D skeleton at 60 frames per second. A piece of digital silk is rigged to that skeleton, so when he opens his palm the fabric drapes across his fingers, when he closes his hand it crumples in his fist, when he tilts his wrist the cloth slides off and folds with real physics, light reflecting off it like actual material. He can grab it, stretch it, throw it, catch it, all with his bare hands and zero hardware on his body. No headset, no gloves, no $3,500 face computer, no 600 gram brick on his skull, no 2 hour battery, no Apple ID, no App Store. Just a webcam, TouchDesigner and a kid who saw the Vision Pro keynote and thought, I can do that for free. Apple has 3,000 engineers, $200 billion in cash and 7 years of development time, they built a face computer most people will never own. This guy has a laptop, a webcam and a weekend, he built a future most people can actually use. The mixed reality industry just got embarrassed by a guy in a white t-shirt.

Defileo🔮

3,018,058 次观看 • 4 个月前

🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )

🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )

Kanika

14,769 次观看 • 5 个月前

🚀 FocusOs is now live on the App Store!! 🥳🎉 focusOS is a super-utility for Mac & iOS that hides all distractions with one click. It seamlessly adjusts your devices for work and supercharges your productivity. Download ➡️ Here are some of the cool things it does; 1️⃣ Dim inactive apps, limit visible apps, hide the wallpaper, and more (on Mac) 2️⃣ Block news, social media, and other distracting apps & websites 3️⃣ Play ambient sounds to improve concentration, as if you were working from a cafe or listening to the sound of light rain And also; 4️⃣ Turn on Do Not Disturb automatically with Shortcuts 5️⃣ Link your Mac, iPhone, iPad together - to sync environments in real-time It’s become essential to my workflow, especially when I just want to focus on work without a hassle. Simply flick the switch and get straight into it. See it in action ➡️ Download on the App Store ➡️ Try it out and let me know what you think! Thank you to every single person that has supported focusOS during the last few weeks, I really appreciate it! 🙂🙂

🚀 FocusOs is now live on the App Store!! 🥳🎉 focusOS is a super-utility for Mac & iOS that hides all distractions with one click. It seamlessly adjusts your devices for work and supercharges your productivity. Download ➡️ Here are some of the cool things it does; 1️⃣ Dim inactive apps, limit visible apps, hide the wallpaper, and more (on Mac) 2️⃣ Block news, social media, and other distracting apps & websites 3️⃣ Play ambient sounds to improve concentration, as if you were working from a cafe or listening to the sound of light rain And also; 4️⃣ Turn on Do Not Disturb automatically with Shortcuts 5️⃣ Link your Mac, iPhone, iPad together - to sync environments in real-time It’s become essential to my workflow, especially when I just want to focus on work without a hassle. Simply flick the switch and get straight into it. See it in action ➡️ Download on the App Store ➡️ Try it out and let me know what you think! Thank you to every single person that has supported focusOS during the last few weeks, I really appreciate it! 🙂🙂

Michael Tigas

39,150 次观看 • 2 年前

I've now built the BEST iFVG Retrace indicator. FREE. One model, mapped end to end — the raid on liquidity, the CISD closure that confirms it, and the entry on the retrace back into the inverted FVG. • Auto setup hunter — scans both directions continuously and arms the next qualifying setup on its own. Nothing to reset, nothing to redraw. • Auto invalidation — a setup kills itself the moment it's wrong: raid broken, zone body-filled, or no retrace inside the window. It clears off the chart instead of sitting there looking valid. • Drawn live as it forms — levels, zones, plan and targets all build in real time. No repainting, nothing added in after the move. • Liquidity mapped for you — PDH/PDL, PWH/PWL, Asia · London · NY AM · NY PM highs and lows, swings and equal highs/lows. Every line stops exactly where price takes it. • Runway grading — A+ open air down to C, so you can see what's standing in front of a trade before you're in it. • Lid lines — the levels stacked between your entry and 3R, drawn. • Entry, stop and target with risk/reward boxes and a written plan on every setup. • Live read-out — direction, RR, nearest draw, grade, session sweep, setups today. • HTF nesting, a V-shape reversal spotter, and alerts on armed / entry / target / stopped, webhook JSON included. No sub. No paywall. FREE. I post more free content in my Discord → Comment below if you want it, and repost so it lands in front of someone still guessing their entries.

I've now built the BEST iFVG Retrace indicator. FREE. One model, mapped end to end — the raid on liquidity, the CISD closure that confirms it, and the entry on the retrace back into the inverted FVG. • Auto setup hunter — scans both directions continuously and arms the next qualifying setup on its own. Nothing to reset, nothing to redraw. • Auto invalidation — a setup kills itself the moment it's wrong: raid broken, zone body-filled, or no retrace inside the window. It clears off the chart instead of sitting there looking valid. • Drawn live as it forms — levels, zones, plan and targets all build in real time. No repainting, nothing added in after the move. • Liquidity mapped for you — PDH/PDL, PWH/PWL, Asia · London · NY AM · NY PM highs and lows, swings and equal highs/lows. Every line stops exactly where price takes it. • Runway grading — A+ open air down to C, so you can see what's standing in front of a trade before you're in it. • Lid lines — the levels stacked between your entry and 3R, drawn. • Entry, stop and target with risk/reward boxes and a written plan on every setup. • Live read-out — direction, RR, nearest draw, grade, session sweep, setups today. • HTF nesting, a V-shape reversal spotter, and alerts on armed / entry / target / stopped, webhook JSON included. No sub. No paywall. FREE. I post more free content in my Discord → Comment below if you want it, and repost so it lands in front of someone still guessing their entries.

Blank333

27,750 次观看 • 2 个月前

Streaming iPhone data in real-time directly to Rerun 🚀 The collection process is one of the most frustrating parts of building imitation-learning datasets. I’ve got a little army of sensors—📱 iPhone, iPad, Quest 3—but getting them temporally aligned, spatially aligned, AND seeing real-time feedback while recording is tough. I stumbled on a great library from Cake Lab (WPI) called ARFlow. It’s a thin client built on Unity’s ARFoundation that connects over gRPC to a server running Rerun for live data logging. I forked it to: - Log the SLAM translation poses, and - Upgrade rerun to v0.23 for my use case. So far, it works well, but there are still a few hitches: 1. Right now, it’s solid on iPhone and iPad; my Quest 3 client is still slow and not super reliable. 2. I’m using an older ARFlow branch focused on real-time streaming only—no spatial or temporal sync yet. Unity builds for iOS keep failing. 🛠️ 3. Nothing is saved locally to the client, so packet loss is a risk on shaky networks. There’s huge potential in tapping the ubiquitous sensors we carry around every day, and ARFlow is a big step toward making that easy

Streaming iPhone data in real-time directly to Rerun 🚀 The collection process is one of the most frustrating parts of building imitation-learning datasets. I’ve got a little army of sensors—📱 iPhone, iPad, Quest 3—but getting them temporally aligned, spatially aligned, AND seeing real-time feedback while recording is tough. I stumbled on a great library from Cake Lab (WPI) called ARFlow. It’s a thin client built on Unity’s ARFoundation that connects over gRPC to a server running Rerun for live data logging. I forked it to: - Log the SLAM translation poses, and - Upgrade rerun to v0.23 for my use case. So far, it works well, but there are still a few hitches: 1. Right now, it’s solid on iPhone and iPad; my Quest 3 client is still slow and not super reliable. 2. I’m using an older ARFlow branch focused on real-time streaming only—no spatial or temporal sync yet. Unity builds for iOS keep failing. 🛠️ 3. Nothing is saved locally to the client, so packet loss is a risk on shaky networks. There’s huge potential in tapping the ubiquitous sensors we carry around every day, and ARFlow is a big step toward making that easy

Pablo Vela

27,433 次观看 • 1 年前

$We all remember. We all remember when blockchain was pitched as the next big thing. And today, we feel like we’ve been waiting and waiting. Until recently, Blockchain was too expensive, slow under load, and hard to integrate for most businesses. So enterprises ignored it. It didn’t solve their business problems. That’s changed. Why blockchain, why now? Businesses don’t care about the tech, they care about cost and performance. They’d ask a simple question “Does it save or make me more money?” For a long time, blockchain didn’t clearly do this. That’s no longer true. Blockchain is proving real business cases, especially on Avalanche. On Avalanche, transactions cost fractions of a cent. settle in about a second. And instead of forcing everything onto one shared chain, businesses can launch their own Avalanche L1s with their own rules. To understand this let’s identify the problem and then provide the solution in a way that's easy to understand. Where Businesses Lose Money Most large industries lose money due to operational inefficiencies. Data lives in different systems. Teams spend hours reconciling records that should already match. Intermediaries sit in the middle, taking fees to coordinate all of it. Individually, each step looks small. Together, they create real cost: > Labor spent on manual processes > Capital locked up during settlement delays > Fees paid to intermediaries > Risk introduced by time gaps and mismatched data This is where businesses actually lose money. Not in big, obvious ways. In constant, compounding friction. Take Private Credit, for Example Private credit is loans held outside of traditional banks. It’s a multi-trillion dollar market, and much of it still runs on spreadsheets and weekly reconciliation processes. Loan data is tracked across systems. Teams manually process requests. Funds move on traditional rails, often on delayed cycles. It doesn’t have to be this way Entire teams exist just to keep systems in sync. Now move that system onto Avalanche. Loan data updates in real time. Transactions settle in about a second. Every participant sees the same state instantly. Reconciliation isn’t a separate step because the system itself is the source of truth. The impact is straightforward. > Reduced manual work > Shortened settlement cycles > Fewer layers of coordination between parties Avalanche is Infrastructure for Real Businesses Avalanche is designed to match how businesses actually operate. Instead of sharing a single chain, they can launch their own Avalanche L1s with custom rules, built-in compliance, and predictable performance. They control the system. Avalanche’s Moment For the longest time, blockchain naysayers said this could all be done better with spreadsheets or existing systems. They were right. That’s what the technology allowed. Now it’s changed. Avalanche can replace many of those systems with real-time settlement, shared data, and automated execution. For the first time, the economics work. Built for business. 🔺$

We all remember. We all remember when blockchain was pitched as the next big thing. And today, we feel like we’ve been waiting and waiting. Until recently, Blockchain was too expensive, slow under load, and hard to integrate for most businesses. So enterprises ignored it. It didn’t solve their business problems. That’s changed. Why blockchain, why now? Businesses don’t care about the tech, they care about cost and performance. They’d ask a simple question “Does it save or make me more money?” For a long time, blockchain didn’t clearly do this. That’s no longer true. Blockchain is proving real business cases, especially on Avalanche. On Avalanche, transactions cost fractions of a cent. settle in about a second. And instead of forcing everything onto one shared chain, businesses can launch their own Avalanche L1s with their own rules. To understand this let’s identify the problem and then provide the solution in a way that's easy to understand. Where Businesses Lose Money Most large industries lose money due to operational inefficiencies. Data lives in different systems. Teams spend hours reconciling records that should already match. Intermediaries sit in the middle, taking fees to coordinate all of it. Individually, each step looks small. Together, they create real cost: > Labor spent on manual processes > Capital locked up during settlement delays > Fees paid to intermediaries > Risk introduced by time gaps and mismatched data This is where businesses actually lose money. Not in big, obvious ways. In constant, compounding friction. Take Private Credit, for Example Private credit is loans held outside of traditional banks. It’s a multi-trillion dollar market, and much of it still runs on spreadsheets and weekly reconciliation processes. Loan data is tracked across systems. Teams manually process requests. Funds move on traditional rails, often on delayed cycles. It doesn’t have to be this way Entire teams exist just to keep systems in sync. Now move that system onto Avalanche. Loan data updates in real time. Transactions settle in about a second. Every participant sees the same state instantly. Reconciliation isn’t a separate step because the system itself is the source of truth. The impact is straightforward. > Reduced manual work > Shortened settlement cycles > Fewer layers of coordination between parties Avalanche is Infrastructure for Real Businesses Avalanche is designed to match how businesses actually operate. Instead of sharing a single chain, they can launch their own Avalanche L1s with custom rules, built-in compliance, and predictable performance. They control the system. Avalanche’s Moment For the longest time, blockchain naysayers said this could all be done better with spreadsheets or existing systems. They were right. That’s what the technology allowed. Now it’s changed. Avalanche can replace many of those systems with real-time settlement, shared data, and automated execution. For the first time, the economics work. Built for business. 🔺

Avalanche🔺

13,142 次观看 • 5 个月前

🚨 MIT JUST DISCOVERED HOW INJECTING CO₂ ACTUALLY REWIRES CEMENT CHEMISTRY FROM THE INSIDE. For years, companies have been injecting carbon dioxide into concrete to store emissions and speed up strength gain. But no one fully understood why it worked until now. Using real-time Raman spectroscopy, MIT researchers captured the complete chemical sequence as it happened. They found that CO₂ triggers a three-act process: First, it locks up calcium and creates a temporary silica gel network throughout the paste. Then, as normal hydration resumes, this “ghostly gel” reacts with calcium hydroxide to form calcium silicate hydrate (C-S-H) but now distributed evenly across the entire matrix instead of clustered around clinker particles. Finally, the gel disappears within eight hours, leaving behind a stronger, more uniform microstructure. In testing, cement paste with just 1% CO₂ by weight showed 13% higher compressive strength at 24 hours compared to conventional mixes. Why this matters: • This is the first direct observation of the fleeting intermediate reactions that drive improved performance • The strength gain comes from better distribution of the binding phase, not from calcium carbonate acting as seeds • The process stores CO₂ while simultaneously improving the material a rare win-win in construction • It gives manufacturers a clearer scientific basis to optimize CO₂ injection rather than relying on trial and error The deeper implication: Concrete is the most used material on Earth and one of the largest sources of CO₂ emissions. Being able to see and therefore control the exact chemical mechanism behind CO₂ injection opens the door to smarter, lower-carbon cement formulations. It also shows how advanced spectroscopy can reveal hidden reaction pathways in materials we thought we already understood. We’re no longer guessing why CO₂ helps cement. We’re watching it happen in real time. How significant do you think real-time molecular imaging will be for decarbonizing construction materials in the next decade? Follow for more frontier materials science and carbon-negative construction research.

🚨 MIT JUST DISCOVERED HOW INJECTING CO₂ ACTUALLY REWIRES CEMENT CHEMISTRY FROM THE INSIDE. For years, companies have been injecting carbon dioxide into concrete to store emissions and speed up strength gain. But no one fully understood why it worked until now. Using real-time Raman spectroscopy, MIT researchers captured the complete chemical sequence as it happened. They found that CO₂ triggers a three-act process: First, it locks up calcium and creates a temporary silica gel network throughout the paste. Then, as normal hydration resumes, this “ghostly gel” reacts with calcium hydroxide to form calcium silicate hydrate (C-S-H) but now distributed evenly across the entire matrix instead of clustered around clinker particles. Finally, the gel disappears within eight hours, leaving behind a stronger, more uniform microstructure. In testing, cement paste with just 1% CO₂ by weight showed 13% higher compressive strength at 24 hours compared to conventional mixes. Why this matters: • This is the first direct observation of the fleeting intermediate reactions that drive improved performance • The strength gain comes from better distribution of the binding phase, not from calcium carbonate acting as seeds • The process stores CO₂ while simultaneously improving the material a rare win-win in construction • It gives manufacturers a clearer scientific basis to optimize CO₂ injection rather than relying on trial and error The deeper implication: Concrete is the most used material on Earth and one of the largest sources of CO₂ emissions. Being able to see and therefore control the exact chemical mechanism behind CO₂ injection opens the door to smarter, lower-carbon cement formulations. It also shows how advanced spectroscopy can reveal hidden reaction pathways in materials we thought we already understood. We’re no longer guessing why CO₂ helps cement. We’re watching it happen in real time. How significant do you think real-time molecular imaging will be for decarbonizing construction materials in the next decade? Follow for more frontier materials science and carbon-negative construction research.

TheNewPhysics

62,589 次观看 • 3 个月前

NanoBanana 2 just made your static ad agency obsolete. And I just open sourced the entire tool. Drop your product page URL. It pulls your logos, product images, fonts, colors, and brand voice automatically. Builds a full brand guide for you. Then generates ad creatives at scale using nearly 4,000 high-performing ad templates across 8 niches. It dynamically matches the best templates to your brand and brief. Here's what makes it different: → Instant resizing Get any ad in 1x1, 4x5, 9x16 with one click. No regeneration. No broken text. → Highlight-to-edit See an issue? Highlight the area and tell it what to fix. → Multiple brand profiles Run different brands or segments from one tool. → Auto persona building from real customer reviews → Multiple QC loops on briefs and final assets Catches AI-isms before you do. → Upload your own templates or use ours Runs locally. Just needs your Claude and Google API keys. This is the lite version of what we use internally. You get the full finished tool AND the open source code to make it your own. Creatives still design the system, this handles iteration and scale. Want a copy to download? 1. Like this post 2. Comment "AI" Will DM you the tool along with a tutorial shortly after.

Peter Quadrel

292,980 次观看 • 6 个月前

This guy cracked the code on AI virtual influencers using real-time face filters and now D2C brands pay him $2,000 per UGC video. He got tired of watching D2C brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs hyperrealistic AI girls in real-time from his own webcam, generating viral content without actresses, studios, or makeup artists. His monthly revenue hit $89,000 last month from a network of 7 AI personas across TikTok and Instagram, while the average UGC creator caps at $6K juggling 4 brand deals. Here is the exact breakdown: → The hardware is the moat, but most people butcher the setup in the first frame. You need the face mesh locked at 60fps with zero artifacting → Persona comes first, and if you mess this up nothing saves it. Name, backstory, voice tone, niche before a single clip is shot → Face selection is not random. You A/B test features (eye spacing, jawline, hair contrast with face-framing highlights) because some faces convert better in 9:16 → You are picking who your audience trusts, not who looks cool. That is your targeting baked into bone structure → Real-time physics run before the script, and this is what kills the uncanny valley that destroys watch time in 2 seconds → The filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick. → Batching is the move 96 percent skip: one performance, multiple personas, three platforms. → The system pushes 12 pieces of content before lunch, while traditional brands test 2 creators per week and wonder why their CPAs are stuck at $94 The economics are stupid: each video costs him $4 in compute, sells for $1,500 to $3,000, and takes 14 minutes to produce. That is a 37,500 percent margin, while UGC agencies pay creators $400 to $800 per clip and net $200 after revisions. One supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to LA. They were previously paying $1,200 per UGC video and burning $6,000 per week on content that did not scale. Now they spend $210 for 14 variants and their CPA dropped from $89 to $27. The avatars hold real products. Warm window light on the persona, cold neon on the operator. Mouth shapes sync to consonants, not just vowels. Just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break.

Shade

136,231 次观看 • 4 个月前

$OnlyMarms Update for the end of Day 2 🦫 The receipts just keep stacking up. Since yesterday... 📺 The token has now been mentioned LIVE on television for the second time, this time on NBC. ( 🎙️ The story has now reached radio, with its first major interview airing on Radio-Canada. ( 🌐 The M.A.D. Lab has created an official OnlyMarms page on its website, documenting the community initiative and bringing everything together in one place. ( 📰 And more media outlets continue picking up the story by the hour - from major newspapers to university publications and international outlets. Take a step back for a second. $OnlyMarms sends a message and sets a statement: Meme coins can do good, and Meme coins can have real-world impact. It is the first time in a while, that we see positive media reports on a meme coin. This isn't a a simple meme that we have invented, it is actually a real world problem that we got to turn into a Crypto narrative to help the M.A.D Lab with fundraising, and awareness. The Pump.fun community, together against a real-world problem. A wildlife research lab founded in 1962 lost critical government funding after more than 60 years of continuous research. The community built around that mission. Now, every TV appearance, every radio interview, every news article, and every official update from the lab brings more attention - not just to the token, but to the research itself and the main issue: get the Lab their funding back. This is what makes OnlyMarms different. The narrative doesn't depend on price action, this is bigger than that. It evolves every time the world learns about the story. For the first time in a while, we have a narrative that I think can send a message and set a statement: Meme coins can do good, and Meme coins can have real-world impact. It is the first time in a while, that we see positive media reports on a meme coin. 🦫 Official M.A.D. Lab OnlyMarms page: 🌍 Community Website: Community Chat for raids and bagworking: Official Linktree: CA: HBrfYZgeLKdSvBBGnGkvAK4563pq8oBGpgNFAaespump Also we set up an official account where more marmot content will be posted: OnlyMarms

$OnlyMarms Update for the end of Day 2 🦫 The receipts just keep stacking up. Since yesterday... 📺 The token has now been mentioned LIVE on television for the second time, this time on NBC. ( 🎙️ The story has now reached radio, with its first major interview airing on Radio-Canada. ( 🌐 The M.A.D. Lab has created an official OnlyMarms page on its website, documenting the community initiative and bringing everything together in one place. ( 📰 And more media outlets continue picking up the story by the hour - from major newspapers to university publications and international outlets. Take a step back for a second. $OnlyMarms sends a message and sets a statement: Meme coins can do good, and Meme coins can have real-world impact. It is the first time in a while, that we see positive media reports on a meme coin. This isn't a a simple meme that we have invented, it is actually a real world problem that we got to turn into a Crypto narrative to help the M.A.D Lab with fundraising, and awareness. The Pump.fun community, together against a real-world problem. A wildlife research lab founded in 1962 lost critical government funding after more than 60 years of continuous research. The community built around that mission. Now, every TV appearance, every radio interview, every news article, and every official update from the lab brings more attention - not just to the token, but to the research itself and the main issue: get the Lab their funding back. This is what makes OnlyMarms different. The narrative doesn't depend on price action, this is bigger than that. It evolves every time the world learns about the story. For the first time in a while, we have a narrative that I think can send a message and set a statement: Meme coins can do good, and Meme coins can have real-world impact. It is the first time in a while, that we see positive media reports on a meme coin. 🦫 Official M.A.D. Lab OnlyMarms page: 🌍 Community Website: Community Chat for raids and bagworking: Official Linktree: CA: HBrfYZgeLKdSvBBGnGkvAK4563pq8oBGpgNFAaespump Also we set up an official account where more marmot content will be posted: OnlyMarms

Miggl

106,610 次观看 • 1 个月前

This guy cracked the code on AI-powered fashion ecommerce using synthetic face technology and now pulls $50,000 to $150,000 per month from two Shopify stores without paying a single real model. He got tired of watching DTC fashion brands burn $20,000 monthly on photoshoots while their competitors tested 40 product angles in the same timeframe, so he built a system that generates hyperrealistic fashion content using his gaming PC and real-time AI masks instead of studios, contracts, or casting calls. His monthly profit hit $150,000 last month from just 2 stores and organic TikTok traffic, while traditional fashion brands cap out at $30K after paying models $400 to $800 per shoot and studio rentals of $200 to $500 per session. Here is the exact breakdown: → Real-time synthetic face technology becomes the only tool you need, but most people butcher the setup by skipping motion sync calibration in the first 30 seconds → Product selection comes first, and if you mess this up nothing saves it. Stick to women's accessories (bags, sunglasses, jewelry) because that is where organic TikTok engagement lives → Avatar casting is not random. You build one consistent AI face that repeats across all content so your audience recognizes the "model" and trusts the brand continuity → You are picking who your customer projects onto, not who looks expensive. That is your positioning baked into the face → Motion capture runs before generation, and this is what kills the uncanny valley effect that destroys watch time in 4 seconds → You mirror your own gestures through webcam: wave, chin tap, finger point, shoulder dance. The AI mask tracks every micro-movement and applies it to the generated face in real time → Batching is the move 94 percent skip: same outfit base, multiple product swaps, one recording session. No re-shooting, no model schedules, no usage rights negotiations → The system generates 3 to 5 TikToks before lunch, while traditional brands test 2 per week and wonder why their conversion rates are stuck at 0.8 percent The economics are stupid: each video costs him $0 in talent fees, pulls 1.5 million views organically, converts at 0.03 percent into 450 orders at $45 to $60 retail with $30 to $45 margin per sale. That is $15,750 profit per viral video, while fashion brands pay $1,200 per shoot and net $3,000 after ads. The key move nobody talks about: you cannot skip the motion synchronization test. If you generate the AI face without mirroring your own natural gestures first, the avatar moves like a mannequin. The blinks lag. The smile timing breaks. The whole thing screams "synthetic face technology" and your hook rate dies at 1.1 seconds. His system records him doing the exact dance trend first, so the AI mask inherits human timing, natural head tilts, and spontaneous energy that reads as a real creator showing off a product find, not a rendered advertisement. One accessories store generated 10 variants of the same handbag reveal in 18 minutes with different outfits, different backgrounds, different trend audios, and found the winner in 72 hours without spending $6,000 on influencer gifting. They were previously paying $800 per UGC creator and burning $4,800 per week on content that plateaued at 40K views. Now they spend $0 for 10 variants and their cost per acquisition dropped from $62 to $18. UGC agencies now panic because their entire margin was built on talent scarcity, and this removes the human bottleneck. The outfit changes between clips like a wardrobe filter. The lighting matches bedroom setups. The hand gestures sync with beat drops. No casting call. No model release. No location permits. Just a webcamera, a real-time AI mask, and the discipline to batch-test product angles before you commit ad spend to one creative.

Shade

20,471 次观看 • 4 个月前

"npx t3 connect" This one's been a lot of work. You can now set up remote control for T3 Code on any internet-connected box with literally one command. All for free. T3 Connect is a minimal open source tunnel layer allowing you to control T3 Code instances remotely without needing Tailscale set up. I've been daily driving it for a month and it has changed how I code. Julius and I put a lot of effort into making setup as smooth as possible. Step 1: Install Claude Code, Codex, OpenCode, or Grok Build Step 2: Run "npx t3 connect" Step 3: Click link and sign in Step 4: You can now control that computer on T3 Code web, desktop or mobile (dropping very soon) We are currently providing this for free (s/o CloudFlare for bumping our tunnel limits). Every user can connect up to 3 devices. We don't want to charge for this, but if the bill gets unacceptable we may have to change course. If you hit limits or have issues, you can always fork, self host, or use Tailscale. T3 Connect may seem like a small ergonomic win. Tbh that's exactly what it is. Regardless, it's one I'm really proud of.

"npx t3 connect" This one's been a lot of work. You can now set up remote control for T3 Code on any internet-connected box with literally one command. All for free. T3 Connect is a minimal open source tunnel layer allowing you to control T3 Code instances remotely without needing Tailscale set up. I've been daily driving it for a month and it has changed how I code. Julius and I put a lot of effort into making setup as smooth as possible. Step 1: Install Claude Code, Codex, OpenCode, or Grok Build Step 2: Run "npx t3 connect" Step 3: Click link and sign in Step 4: You can now control that computer on T3 Code web, desktop or mobile (dropping very soon) We are currently providing this for free (s/o CloudFlare for bumping our tunnel limits). Every user can connect up to 3 devices. We don't want to charge for this, but if the bill gets unacceptable we may have to change course. If you hit limits or have issues, you can always fork, self host, or use Tailscale. T3 Connect may seem like a small ergonomic win. Tbh that's exactly what it is. Regardless, it's one I'm really proud of.

Theo - t3.gg

325,960 次观看 • 1 个月前