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Lazy Bones - Uploading documentation videos now. So close. Here's a slower example than before. Omabuarts Studio - Game Assets models. @higgsas simulation methods. #b3d #blender

Blue Nile

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19,769 просмотров • 2 лет назад •via X (Twitter)

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AI-GENERATED SNES GAMES? “WE’RE PRETTY CLOSE,” SAYS ELON A full Super Nintendo game fits into just 4MB - the same size as a single Veo 3 AI-generated video. On paper, that’s nothing. Today’s AI models chew through gigabytes without breaking a digital sweat. So why aren’t we getting auto-generated SNES classics? The short answer? A frustrating pile-up of bottlenecks: combining logic, physics, sprite art, music, controls, level design, and actual fun into a compressed, playable ROM is harder than it looks. Elon Musk: “We’re pretty close.” So, in other words, game design may soon join the list of creative industries about to get retro-fitted by AI. Time for next-level simulation in 16-bit clothing. Source: bone, Allen T.

AI-GENERATED SNES GAMES? “WE’RE PRETTY CLOSE,” SAYS ELON A full Super Nintendo game fits into just 4MB - the same size as a single Veo 3 AI-generated video. On paper, that’s nothing. Today’s AI models chew through gigabytes without breaking a digital sweat. So why aren’t we getting auto-generated SNES classics? The short answer? A frustrating pile-up of bottlenecks: combining logic, physics, sprite art, music, controls, level design, and actual fun into a compressed, playable ROM is harder than it looks. Elon Musk: “We’re pretty close.” So, in other words, game design may soon join the list of creative industries about to get retro-fitted by AI. Time for next-level simulation in 16-bit clothing. Source: bone, Allen T.

Mario Nawfal

47,938 просмотров • 1 год назад

Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: The Genesis physics engine and simulation platform is fully open source at We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: Project webpage: Documentation: 1/n

Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: The Genesis physics engine and simulation platform is fully open source at We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: Project webpage: Documentation: 1/n

Zhou Xian

3,820,293 просмотров • 1 год назад

junhan and deupo sehyuk besties~ 🐱 and i heard our member junhan and sehyuk are close- 🐥 is it true they're best friends? 🐱 they're best friends sehyuk: i think we've gotten really close now 🐱 if he talks with junhan like this, they must be close 🐥 what do you usually talk about? sehyuk: he's come to our studio to hang out before.. and he also promised to go to a board game cafe together 🐱 HYEONGJUN? sehyuk: we made plans, but somehow the timing keeps not working out, so please pass along the message, "let's go together," 🐱 i still haven't gone to a board game cafe with hyeongjun either 🐥 i didn't know hyeongjun was the kind of person who would suggest something like that taegyu: they've gotten close

junhan and deupo sehyuk besties~ 🐱 and i heard our member junhan and sehyuk are close- 🐥 is it true they're best friends? 🐱 they're best friends sehyuk: i think we've gotten really close now 🐱 if he talks with junhan like this, they must be close 🐥 what do you usually talk about? sehyuk: he's come to our studio to hang out before.. and he also promised to go to a board game cafe together 🐱 HYEONGJUN? sehyuk: we made plans, but somehow the timing keeps not working out, so please pass along the message, "let's go together," 🐱 i still haven't gone to a board game cafe with hyeongjun either 🐥 i didn't know hyeongjun was the kind of person who would suggest something like that taegyu: they've gotten close

ten

14,295 просмотров • 6 месяцев назад

We built a studio, we made a game, and I'm really proud of both. Before we close the doors at Midsummer Studios I'd like to share a glimpse of Burbank, the game we poured our hearts into. It's like "Life Sims + The Truman Show," but it's more than that. I believe people are storytellers, and I want them to share whatever stories and characters they can dream up. Burbank let's you do that. We have moments playing this game where characters come alive in a way we've never experienced. And for an old game developer like me that's special. What you're about to see is definitely pre-alpha. But this game was a dream of mine, our team made it come true, so watch and dream with us.

We built a studio, we made a game, and I'm really proud of both. Before we close the doors at Midsummer Studios I'd like to share a glimpse of Burbank, the game we poured our hearts into. It's like "Life Sims + The Truman Show," but it's more than that. I believe people are storytellers, and I want them to share whatever stories and characters they can dream up. Burbank let's you do that. We have moments playing this game where characters come alive in a way we've never experienced. And for an old game developer like me that's special. What you're about to see is definitely pre-alpha. But this game was a dream of mine, our team made it come true, so watch and dream with us.

Jake Solomon

206,779 просмотров • 6 месяцев назад

Introducing Hybrid Models Alchemist AI now allows users to choose one model for ideation and another for completion, making app generation smarter, more structured, and highly detailed. With an ideation model, users can provide a simple prompt, and Alchemist AI does the heavy lifting—expanding on the idea with precise technical details. When creating a game, for example, it defines map size, terrain complexity, physics, AI behavior, and game mechanics before passing it to the completion model, which then builds the final product. This hybrid approach elevates the quality of generated applications, making it easier than ever to create highly polished games, tools, and applications—with minimal effort.

Introducing Hybrid Models Alchemist AI now allows users to choose one model for ideation and another for completion, making app generation smarter, more structured, and highly detailed. With an ideation model, users can provide a simple prompt, and Alchemist AI does the heavy lifting—expanding on the idea with precise technical details. When creating a game, for example, it defines map size, terrain complexity, physics, AI behavior, and game mechanics before passing it to the completion model, which then builds the final product. This hybrid approach elevates the quality of generated applications, making it easier than ever to create highly polished games, tools, and applications—with minimal effort.

ALCHEMIST AI 🔮

17,914 просмотров • 1 год назад

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

"I've spent $30K on a launch video, now you can make one with code." Here's my new episode with Bin Liu and Jake Moran, where they shared their 5-step playbook for using HyperFrames to make professional launch videos in Codex and Claude Code: 1. Gather video assets and create a frame.md 2. Create a storyboard.md with the scenes 3. Pull animations from the HyperFrames repo 4. Generate and review static frames 5. Build the video with HyperFrames Studio You can also start simple by using the built-in /website-to-video skill to one shot a launch video from any URL. HyperFrames is 100% free and I love how it democratizes video creation for everyone. 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

Peter Yang

68,646 просмотров • 2 месяцев назад

notes on my reinforcement learning for rocket league side quest so far: i’m in awe that — we live in a time where i can train a reinforcement learning model that is learning to play rocket league and at the same time, test community made rocket league models. where, both processes can run in parallel & locally on my hardware. in the game window — i’m playing against a reinforcement learning ppo model that’s running locally. and in the vscode window — i’m training my own reinforcement learning model (just a dummy example script for now). also, the rocket league botting ecosystem has incredible tooling where you can test out different reinforcement learning ideas against other algorithms + it has great documentation for linux and windows. it’s honestly a beautiful hidden gem of a rabbit hole :)

notes on my reinforcement learning for rocket league side quest so far: i’m in awe that — we live in a time where i can train a reinforcement learning model that is learning to play rocket league and at the same time, test community made rocket league models. where, both processes can run in parallel & locally on my hardware. in the game window — i’m playing against a reinforcement learning ppo model that’s running locally. and in the vscode window — i’m training my own reinforcement learning model (just a dummy example script for now). also, the rocket league botting ecosystem has incredible tooling where you can test out different reinforcement learning ideas against other algorithms + it has great documentation for linux and windows. it’s honestly a beautiful hidden gem of a rabbit hole :)

naklecha

46,795 просмотров • 1 год назад

I used Cursor to vibe code a simple fishing game prototype on the Unity Engine. Here's my learnings: - I did not use any Unity MCP for this. The game was built entirely by Cursor models (Sonnet 4.6 for execution and Opus 4.6 for planning) - The model was able to set up the game, getting the basic game mechanics working fairly quickly - I had to use the Unity Game Editor UI to attach components to the in-game objects manually, but it was quite easy to follow the instructions given by the Cursor model - Unity Editor is huge and slow! Compared to Godot, I find the UI really clunky I feel tired looking at it - Unity Assets Marketplace is amazing, there are so many amazing art assets there (like the ones I am using for this game). This is probably the biggest strength of Unity. - I had some issues with restoring checkpoints, probably because of how Unity Game Editor UI being really clunky and I had to manually adjust things in the Editor, which the model doesnt have knowledge of Overall, the results turn out pretty decent, but it was a rather frustrating experience, especially when I had to debug issues or rollback changes. I'll explore more vibe coding on Unity but for now, I think I prefer Godot as a game engine. I just wish there is a Godot Asset Marketplace!

I used Cursor to vibe code a simple fishing game prototype on the Unity Engine. Here's my learnings: - I did not use any Unity MCP for this. The game was built entirely by Cursor models (Sonnet 4.6 for execution and Opus 4.6 for planning) - The model was able to set up the game, getting the basic game mechanics working fairly quickly - I had to use the Unity Game Editor UI to attach components to the in-game objects manually, but it was quite easy to follow the instructions given by the Cursor model - Unity Editor is huge and slow! Compared to Godot, I find the UI really clunky I feel tired looking at it - Unity Assets Marketplace is amazing, there are so many amazing art assets there (like the ones I am using for this game). This is probably the biggest strength of Unity. - I had some issues with restoring checkpoints, probably because of how Unity Game Editor UI being really clunky and I had to manually adjust things in the Editor, which the model doesnt have knowledge of Overall, the results turn out pretty decent, but it was a rather frustrating experience, especially when I had to debug issues or rollback changes. I'll explore more vibe coding on Unity but for now, I think I prefer Godot as a game engine. I just wish there is a Godot Asset Marketplace!

Danny Limanseta

186,148 просмотров • 5 месяцев назад

🧑‍🚀 Day 4 of the Cursor #vibejam Proudly sponsored by Cursor + bolt.new + GLIF So the new sponsor is GLIF: Glif is like Claude Code for AI videos and content generation: you can build launch videos for your game, explore asset styles with 100+ AI models/tools and train it on your favorite workflows via skills! Use it to make trailers, game assets, promo videos and more for your Vibe Jam submission! Tomorrow fabian from Glif will share more to help you create promotion materials for your games! Because it'd be cool if after the Vibe Jam your games will take off and become actual games Again browsing the #vibejam tag on X today and there's so many people building cool, cute and fun games so it was hard, but I picked my favorite 4 ones from today: - A literal 🪰 "fly" simulator, not flight simulator 😂 by Gabriel - What looks like a multiplayer Roman combat simulator by Tim Trussner - LeBeau Motel (another?) Habbo Hotel remix by Vincent - Roomba Wars by Thijs which is descriptive enough to not need an explanation 😁 Reply in this thread with updates on your current games to share your progress! Do you want to participate? You can still start now and submit your game any time before May 1! There's $35,000 in prizes you can win, see threads below for more info!

🧑‍🚀 Day 4 of the Cursor #vibejam Proudly sponsored by Cursor + bolt.new + GLIF So the new sponsor is GLIF: Glif is like Claude Code for AI videos and content generation: you can build launch videos for your game, explore asset styles with 100+ AI models/tools and train it on your favorite workflows via skills! Use it to make trailers, game assets, promo videos and more for your Vibe Jam submission! Tomorrow fabian from Glif will share more to help you create promotion materials for your games! Because it'd be cool if after the Vibe Jam your games will take off and become actual games Again browsing the #vibejam tag on X today and there's so many people building cool, cute and fun games so it was hard, but I picked my favorite 4 ones from today: - A literal 🪰 "fly" simulator, not flight simulator 😂 by Gabriel - What looks like a multiplayer Roman combat simulator by Tim Trussner - LeBeau Motel (another?) Habbo Hotel remix by Vincent - Roomba Wars by Thijs which is descriptive enough to not need an explanation 😁 Reply in this thread with updates on your current games to share your progress! Do you want to participate? You can still start now and submit your game any time before May 1! There's $35,000 in prizes you can win, see threads below for more info!

@levelsio

126,975 просмотров • 4 месяцев назад

What if you could npm install 3D models? Introducing Vibe3D - the shadcn for threejs Starting with the scifi asset kit, over 180+ models, all free and oss (MIT licensed) and two reference terrain meshes. All models are installed directly into your codebase instead of pre-packaged as code imports or worse yet, FBX files 🤮 Docs: This means, a simple "bunx vibe3d add Artificial Intelligence Papers-kit/pressure-gauge" will install the fully procedural code Want to change something? just tell your ai to do it It uses some shared helper code to produce the topology and at least per kit all items reuse and share the same materials, so technically performance should be better than letting your ai run wild on its own. Also releasing with it two skills: - Vibe model skill to produce your own models and kits, just "bunx vibe-model --global" and tell your ai to vibe model some 3d assets with a reference photo, you'll see it works - Vibe terrain "bunx vibe-terrain" installs the terrain mesh modeler, yea just try it out, best results with opus 5 ngl Everything is MIT licensed, i was just joking, no hate for unreal or unity Threejs still the best tho 🖕🏻 If you just want to see all 3D models up close: Yea, you can also just vampire it and download all modes as .glb files, good luck fixing some of them then though Big thanks to ThreeJS Assets for contributing 50 assets to the scifi kit! Everyone who spends some tokens on it will be added to the contributor list Oh and before i forget fuck you kenney, we roll our own kits now

What if you could npm install 3D models? Introducing Vibe3D - the shadcn for threejs Starting with the scifi asset kit, over 180+ models, all free and oss (MIT licensed) and two reference terrain meshes. All models are installed directly into your codebase instead of pre-packaged as code imports or worse yet, FBX files 🤮 Docs: This means, a simple "bunx vibe3d add Artificial Intelligence Papers-kit/pressure-gauge" will install the fully procedural code Want to change something? just tell your ai to do it It uses some shared helper code to produce the topology and at least per kit all items reuse and share the same materials, so technically performance should be better than letting your ai run wild on its own. Also releasing with it two skills: - Vibe model skill to produce your own models and kits, just "bunx vibe-model --global" and tell your ai to vibe model some 3d assets with a reference photo, you'll see it works - Vibe terrain "bunx vibe-terrain" installs the terrain mesh modeler, yea just try it out, best results with opus 5 ngl Everything is MIT licensed, i was just joking, no hate for unreal or unity Threejs still the best tho 🖕🏻 If you just want to see all 3D models up close: Yea, you can also just vampire it and download all modes as .glb files, good luck fixing some of them then though Big thanks to ThreeJS Assets for contributing 50 assets to the scifi kit! Everyone who spends some tokens on it will be added to the contributor list Oh and before i forget fuck you kenney, we roll our own kits now

robot 2.0

57,584 просмотров • 18 дней назад

After a couple more days with Composer 2.5, I've got a pretty good sense of what it can do for game dev, specifically this mouse cursor racing game I'm building. It nailed ~80% of the features I threw at it, from planning to execution. Pretty amazing. I did have to switch to Opus 4.7 MAX a few times for features that need stronger visual understanding, like adding a 360 loop to the track or nailing a specific visual effect I had in mind. But man, Opus 4.7 MAX is expensive. Composer 2.5's visual understanding is weaker than Opus 4.7, but for most other things it's pretty damn close, and 10x cheaper. So it's now my default. The beauty of Cursor is I can switch models whenever I want, so I'm never stuck on one. Really excited for the larger incoming model. I have a feeling it's going to shine at planning. Can't wait!

After a couple more days with Composer 2.5, I've got a pretty good sense of what it can do for game dev, specifically this mouse cursor racing game I'm building. It nailed ~80% of the features I threw at it, from planning to execution. Pretty amazing. I did have to switch to Opus 4.7 MAX a few times for features that need stronger visual understanding, like adding a 360 loop to the track or nailing a specific visual effect I had in mind. But man, Opus 4.7 MAX is expensive. Composer 2.5's visual understanding is weaker than Opus 4.7, but for most other things it's pretty damn close, and 10x cheaper. So it's now my default. The beauty of Cursor is I can switch models whenever I want, so I'm never stuck on one. Really excited for the larger incoming model. I have a feeling it's going to shine at planning. Can't wait!

Danny Limanseta

172,409 просмотров • 3 месяцев назад

$i just figured out the best way to use Seedance 2.5 latest model from ByteDance lets you generate up to 30 second continuous videos and accepts up to 50 reference assets (images, videos and audio) all in one generation most people overcomplicate it, the real trick is in the details my prompt structure looks like this: [1] global scene + visual style [2] character descriptions [3] timestamped storyboard (0-5s, 5-10s, 10-15s...) [4] camera movement [5] negative prompts [6] ending constraints for example, instead of saying: "girl doing her skincare routine with x product" you tell it exactly what happens every few seconds, where the camera moves, how the emotion changes, what should never appear i put together the exact framework i use and leaking it all to you right now here's what you're getting: > the prompt formula for 30-second videos > how to Use Seedance 2.5 at a fraction of the cost > the best way to use reference images/videos > transitions, camera movements and negative prompts RT + reply "SEEDANCE" and i'll send it over (must follow so i can dm)$

i just figured out the best way to use Seedance 2.5 latest model from ByteDance lets you generate up to 30 second continuous videos and accepts up to 50 reference assets (images, videos and audio) all in one generation most people overcomplicate it, the real trick is in the details my prompt structure looks like this: [1] global scene + visual style [2] character descriptions [3] timestamped storyboard (0-5s, 5-10s, 10-15s...) [4] camera movement [5] negative prompts [6] ending constraints for example, instead of saying: "girl doing her skincare routine with x product" you tell it exactly what happens every few seconds, where the camera moves, how the emotion changes, what should never appear i put together the exact framework i use and leaking it all to you right now here's what you're getting: > the prompt formula for 30-second videos > how to Use Seedance 2.5 at a fraction of the cost > the best way to use reference images/videos > transitions, camera movements and negative prompts RT + reply "SEEDANCE" and i'll send it over (must follow so i can dm)

MAX

95,162 просмотров • 1 месяц назад

I’ve been using Grok Bot in early access for a little over a week now, and it has been a massive boost to my game dev workflow and my productivity in general. One of the first things I asked it to do was to visit my custom art generation tool webpage and generate art assets to replace all the image placeholders in my game. It looked through my codebase to understand what each asset was, wrote a custom art generation prompt for every single one, generated the images, cropped and cleaned them up into transparent PNGs, and then wired them back into the game. In about 2 hours, it generated 74 (cleaned and cropped) art assets for the cards and integrated all of them into my game. Now, ALL my art assets workflows go through Grok bot. This blew my mind because, before this, I was doing everything manually, one asset at a time. It basically solved my entire art asset workflow and allowed me to put it on autopilot, which is amazing. I’ve also been using Grok Bot for: Playtesting my game: The bot was a little slow initially, so I asked it to build a skill specifically designed to playtest my game, with intimate knowledge of its rules and mechanics. It’s much faster now, though I’m still looking for ways to optimise its speed. Setting up my itchio page for my game: It also automated a workflow that uploads a new build to itch whenever I push one to GitHub. Going to the itch website and uploading builds manually every single time was always a pain. Flowcharts and UX design: I’m a UX designer by day, so I decided to give it a much bigger task. I fed the agent a PRD and asked it to design the UX flows and wireframes. With the help of the Figma MCP, it actually delivered. Auditing all my paid subscriptions: I had it go through my emails and hunt down subscriptions that I might have forgotten about. Unsubscribing me from marketing newsletters: It did this beautifully, though it did miss a few newsletters. What I’ve learned is that it takes time to discover all the possible use cases for Grok bot. I’ve had to reevaluate my day-to-day workflows and figure out which parts I can delegate to it. So far, it has been a huge productivity unlock for me and I am discovering more uses for my Grok bots every other day.

I’ve been using Grok Bot in early access for a little over a week now, and it has been a massive boost to my game dev workflow and my productivity in general. One of the first things I asked it to do was to visit my custom art generation tool webpage and generate art assets to replace all the image placeholders in my game. It looked through my codebase to understand what each asset was, wrote a custom art generation prompt for every single one, generated the images, cropped and cleaned them up into transparent PNGs, and then wired them back into the game. In about 2 hours, it generated 74 (cleaned and cropped) art assets for the cards and integrated all of them into my game. Now, ALL my art assets workflows go through Grok bot. This blew my mind because, before this, I was doing everything manually, one asset at a time. It basically solved my entire art asset workflow and allowed me to put it on autopilot, which is amazing. I’ve also been using Grok Bot for: Playtesting my game: The bot was a little slow initially, so I asked it to build a skill specifically designed to playtest my game, with intimate knowledge of its rules and mechanics. It’s much faster now, though I’m still looking for ways to optimise its speed. Setting up my itchio page for my game: It also automated a workflow that uploads a new build to itch whenever I push one to GitHub. Going to the itch website and uploading builds manually every single time was always a pain. Flowcharts and UX design: I’m a UX designer by day, so I decided to give it a much bigger task. I fed the agent a PRD and asked it to design the UX flows and wireframes. With the help of the Figma MCP, it actually delivered. Auditing all my paid subscriptions: I had it go through my emails and hunt down subscriptions that I might have forgotten about. Unsubscribing me from marketing newsletters: It did this beautifully, though it did miss a few newsletters. What I’ve learned is that it takes time to discover all the possible use cases for Grok bot. I’ve had to reevaluate my day-to-day workflows and figure out which parts I can delegate to it. So far, it has been a huge productivity unlock for me and I am discovering more uses for my Grok bots every other day.

Danny Limanseta

404,057 просмотров • 22 дней назад

Dario Amodei, the CEO of Anthropic, went on CNN and put a number on the thing most AI CEOs will not say out loud: Half of all entry-level white-collar jobs gone. Unemployment at 10 to 20%. Inside 1 to 5 years. "The most salient feature of the technology, and what is driving all of this, is how fast the technology is getting better." "A couple of years ago, you could say that AI models were maybe as good as a smart high school student. I would say that now they're as good as a smart college student, and sort of reaching past that." "I really worry, particularly at the entry level, that the AI models are very much at the center of what an entry level human worker would do." "What is striking to me about this AI boom is that it's bigger and it's broader and it's moving faster than anything has before." "People will adapt, but they may not adapt fast enough. And so there may be an adjustment period." The tell: this is not a critic outside the industry. It is the man building the models saying the quiet part on camera -- because he thinks the people whose jobs are on the line adapt slower than the models improve. High school to college in two years was the warm-up. The entry level is where it lands first.

Dario Amodei, the CEO of Anthropic, went on CNN and put a number on the thing most AI CEOs will not say out loud: Half of all entry-level white-collar jobs gone. Unemployment at 10 to 20%. Inside 1 to 5 years. "The most salient feature of the technology, and what is driving all of this, is how fast the technology is getting better." "A couple of years ago, you could say that AI models were maybe as good as a smart high school student. I would say that now they're as good as a smart college student, and sort of reaching past that." "I really worry, particularly at the entry level, that the AI models are very much at the center of what an entry level human worker would do." "What is striking to me about this AI boom is that it's bigger and it's broader and it's moving faster than anything has before." "People will adapt, but they may not adapt fast enough. And so there may be an adjustment period." The tell: this is not a critic outside the industry. It is the man building the models saying the quiet part on camera -- because he thinks the people whose jobs are on the line adapt slower than the models improve. High school to college in two years was the warm-up. The entry level is where it lands first.

Karl Mehta

341,287 просмотров • 2 месяцев назад

GUYS IM SO HYPED! This was all theoretical, made it just for fun; I did not know if a merge of two different fine tunes would be usable let alone an improvement! But the final seam-healed 18B merge is genuinely awesome! And a real improvement over either 9B alone (at least I think make your own conclusions and let me know) TLDR: I’ve merged 2 of Jackrongs excellent fine tunes into one really awesome 18B model, sitting nicely between the 9B and 27B using only 10GB of VRAM! It one shotted a bunch of web dashboards AND A SNAKE GAME THAT WORKS and looks nice too! All in the video below you can also check them in the repo! Uploading the healed model now, unfortunately T-Mobile internet is throttling me to 1MB/second upload so it will be 30 minutes or so before it’s done but it will be live at the repo in the comments! And I will post again when it’s live! In the meantime, you can open the html examples in the repo to check them out! I also have included a full documentation of the merge and healing process! WERE GONNA MAKE SO MUCH COOL STUFF WITH THIS METHOD!

GUYS IM SO HYPED! This was all theoretical, made it just for fun; I did not know if a merge of two different fine tunes would be usable let alone an improvement! But the final seam-healed 18B merge is genuinely awesome! And a real improvement over either 9B alone (at least I think make your own conclusions and let me know) TLDR: I’ve merged 2 of Jackrongs excellent fine tunes into one really awesome 18B model, sitting nicely between the 9B and 27B using only 10GB of VRAM! It one shotted a bunch of web dashboards AND A SNAKE GAME THAT WORKS and looks nice too! All in the video below you can also check them in the repo! Uploading the healed model now, unfortunately T-Mobile internet is throttling me to 1MB/second upload so it will be 30 minutes or so before it’s done but it will be live at the repo in the comments! And I will post again when it’s live! In the meantime, you can open the html examples in the repo to check them out! I also have included a full documentation of the merge and healing process! WERE GONNA MAKE SO MUCH COOL STUFF WITH THIS METHOD!

Kyle Hessling

15,212 просмотров • 4 месяцев назад

watch and let this sit for a second anon, a 35B AI model, building a complete multi-file game by itself on hermes agent. no cloud or api. not one line of code written by a human. running on a DGX spark in 2026. because not long ago this was science fiction. this is Ornith, a new open agentic coding model, running near lossless on a single DGX Spark, a 128GB box that sits on your desk. i hand it one spec and step back. it reasons about the architecture, creates the project structure, writes every module one by one, and here's the part that got me, it checks its own work as it goes. makes a call, reads the result, decides if it's right, corrects itself before moving on. no steering from me. this is what people keep underestimating about local AI. they hear "local" and think weaker, slower, a toy. watch the clip. a 35B at near full precision, planning and self correcting on a single desktop. the open models got genuinely good at agentic work, not benchmark good, actually builds the thing good. sped 5x so you can watch the whole build start to finish. this is where local AI actually is now. not coming soon. here.

watch and let this sit for a second anon, a 35B AI model, building a complete multi-file game by itself on hermes agent. no cloud or api. not one line of code written by a human. running on a DGX spark in 2026. because not long ago this was science fiction. this is Ornith, a new open agentic coding model, running near lossless on a single DGX Spark, a 128GB box that sits on your desk. i hand it one spec and step back. it reasons about the architecture, creates the project structure, writes every module one by one, and here's the part that got me, it checks its own work as it goes. makes a call, reads the result, decides if it's right, corrects itself before moving on. no steering from me. this is what people keep underestimating about local AI. they hear "local" and think weaker, slower, a toy. watch the clip. a 35B at near full precision, planning and self correcting on a single desktop. the open models got genuinely good at agentic work, not benchmark good, actually builds the thing good. sped 5x so you can watch the whole build start to finish. this is where local AI actually is now. not coming soon. here.

Sudo su

30,299 просмотров • 2 месяцев назад

pinterest trends + chatgpt workflow is actually f*cking cracked for affiliates people are turning a single Pinterest product photo into $1 UGC videos with photorealistic AI models and stacking affiliate commissions on autopilot. no camera, no actors, no inventory. the products are already proven to sell before you touch them here's the system anyone can run today: - pull Pinterest shopping trends filtered by outbound clicks (real buyer intent, not scrollers. dresses is at 37% MoM growth right now) - read the demographic data: 86% women aged 25 to 34, so the AI model matches the exact buyer - feed the product photo into Vmake Agent and get a 20 second UGC video with script, b-roll, close-ups and 360 spins. a creator charges $150 to $500 for this. the tool does it for roughly $1 - post to Pinterest with the affiliate link in the product tag (never the destination box, that gets you banned) - compile 10 videos into one YouTube upload. one creator hit 19,000 views in a day on a single dress video - recreate proven viral thumbnails in 30 seconds by swapping the face and cleaning the layout 3 pins a day, same niche, different products. commissions while you sleep. reply "SYSTEM" + RT and i'll send you the full video so you can build this too.

pinterest trends + chatgpt workflow is actually f*cking cracked for affiliates people are turning a single Pinterest product photo into $1 UGC videos with photorealistic AI models and stacking affiliate commissions on autopilot. no camera, no actors, no inventory. the products are already proven to sell before you touch them here's the system anyone can run today: - pull Pinterest shopping trends filtered by outbound clicks (real buyer intent, not scrollers. dresses is at 37% MoM growth right now) - read the demographic data: 86% women aged 25 to 34, so the AI model matches the exact buyer - feed the product photo into Vmake Agent and get a 20 second UGC video with script, b-roll, close-ups and 360 spins. a creator charges $150 to $500 for this. the tool does it for roughly $1 - post to Pinterest with the affiliate link in the product tag (never the destination box, that gets you banned) - compile 10 videos into one YouTube upload. one creator hit 19,000 views in a day on a single dress video - recreate proven viral thumbnails in 30 seconds by swapping the face and cleaning the layout 3 pins a day, same niche, different products. commissions while you sleep. reply "SYSTEM" + RT and i'll send you the full video so you can build this too.

Sulfur

13,899 просмотров • 1 месяц назад

WHITNEY WEBB on the military now "realizing [its] initial dream for the internet" "LifeLog [has become] Facebook" "Total Information Awareness [has become] Palantir" "we're coming... close to the end game" "A lot of these 'Big Tech'... companies are just masquerading... [they] were created by military intelligence" "I think it's important to keep in mind too that even going beyond Palantir, the Internet itself was created by the military" "And... now we're coming kind of close to the end game in terms of full circle of them kind of realizing their initial dream for the Internet" This clip of Webb (Whitney Webb), author of One Nation Under Blackmail and contributing editor of unlimitedhangout(.)com, is taken from a discussion with Ryan Cristian, Hrvoje Morić, et al. posted to the Corbett Report YouTube channel on May 29, 2026. ---------------Partial transcription of clip---------------- "I mean, I remember stories 10 years ago about massive NSA data centers in like Utah and various states before people were even talking about data centers, about all the information they've been compiling on people. "And I think it's important to keep in mind too that even going beyond Palantir, the Internet itself was created by the military. And I think now we're coming kind of close to the end game in terms of full circle of them kind of realizing their initial dream for the Internet. "And then, you know, in the case of Palantir, you know, I argue, and a lot of my research points to various efforts within the DARPA military sphere aimed at the Internet being privatized. For example, LifeLog becoming Facebook, Total Information Awareness becoming Palantir. You know, these have become reality. "A lot of these big, 'Big Tech' Silicon Valley companies are just masquerading as we just started in our garage. And we're regular guys. Like, no, these are guys that were created by military intelligence and they privatized these programs and we have willingly given them our data and we continue to do so. "And so even if you have Palantir having access to privileged information, think about something in that same family of company, like Clearview AI, for example, which is also Peter Thiel–connected, that has amassed this huge database used for facial recognition by law enforcement and militaries. So, you know, to arrest and also to murder people. "And they just scraped most of that from stuff, pictures people freely and willingly posted. We voluntarily gave a lot of our data away, and they've been able to scrape a lot more of it than you, than you probably think."

WHITNEY WEBB on the military now "realizing [its] initial dream for the internet" "LifeLog [has become] Facebook" "Total Information Awareness [has become] Palantir" "we're coming... close to the end game" "A lot of these 'Big Tech'... companies are just masquerading... [they] were created by military intelligence" "I think it's important to keep in mind too that even going beyond Palantir, the Internet itself was created by the military" "And... now we're coming kind of close to the end game in terms of full circle of them kind of realizing their initial dream for the Internet" This clip of Webb (Whitney Webb), author of One Nation Under Blackmail and contributing editor of unlimitedhangout(.)com, is taken from a discussion with Ryan Cristian, Hrvoje Morić, et al. posted to the Corbett Report YouTube channel on May 29, 2026. ---------------Partial transcription of clip---------------- "I mean, I remember stories 10 years ago about massive NSA data centers in like Utah and various states before people were even talking about data centers, about all the information they've been compiling on people. "And I think it's important to keep in mind too that even going beyond Palantir, the Internet itself was created by the military. And I think now we're coming kind of close to the end game in terms of full circle of them kind of realizing their initial dream for the Internet. "And then, you know, in the case of Palantir, you know, I argue, and a lot of my research points to various efforts within the DARPA military sphere aimed at the Internet being privatized. For example, LifeLog becoming Facebook, Total Information Awareness becoming Palantir. You know, these have become reality. "A lot of these big, 'Big Tech' Silicon Valley companies are just masquerading as we just started in our garage. And we're regular guys. Like, no, these are guys that were created by military intelligence and they privatized these programs and we have willingly given them our data and we continue to do so. "And so even if you have Palantir having access to privileged information, think about something in that same family of company, like Clearview AI, for example, which is also Peter Thiel–connected, that has amassed this huge database used for facial recognition by law enforcement and militaries. So, you know, to arrest and also to murder people. "And they just scraped most of that from stuff, pictures people freely and willingly posted. We voluntarily gave a lot of our data away, and they've been able to scrape a lot more of it than you, than you probably think."

Sense Receptor

85,720 просмотров • 3 месяцев назад

Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)

Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)

kwindla

40,593 просмотров • 3 месяцев назад