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A parametric drone model in nTop generated 100+ simulation-ready configs, zero geometry failures. PhysicsX.ai ran CFD on all of them, trained a surrogate within ~5%, then ran it live inside nTop to predict pressure fields in under a second as geometry changes. AI-accelerated design exploration with nTop + PhysicsX... show more

nTop

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44,605 次观看 • 2 个月前 •via X (Twitter)

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AI-first aircraft development: parametric geometry generated at scale without failures, Physics AI models reporting lift and drag across a wide design space, and multi-objective optimization to get to the most performant aircraft. All in minutes instead of weeks or months.

AI-first aircraft development: parametric geometry generated at scale without failures, Physics AI models reporting lift and drag across a wide design space, and multi-objective optimization to get to the most performant aircraft. All in minutes instead of weeks or months.

nTop

15,684 次观看 • 1 个月前

i gave bonsai, 3.9 gb model one spec to build a working rotary engine autonomously, using hermes agent. all on rtx 3060ti 8gb. watch it go from a black canvas to a running wankel. the epitrochoid housing, a triangular rotor turning at exactly a third of shaft speed, three chambers firing intake, compression, power, exhaust, and ten geometry tests it had to pass to count as done. a provably correct simulation, not a drawing. then i left it alone and it worked. wrote the code, ran its own tests, hit failures, read them, fixed its own lines, until the engine spun and all ten went green. a real agent loop, and i watched every step. it broke three times getting here and clawed back every one. that honest part is in the reply. and this is a sneak. i've been building a show around runs exactly like this, and it's almost ready. more very soon. just getting started.

i gave bonsai, 3.9 gb model one spec to build a working rotary engine autonomously, using hermes agent. all on rtx 3060ti 8gb. watch it go from a black canvas to a running wankel. the epitrochoid housing, a triangular rotor turning at exactly a third of shaft speed, three chambers firing intake, compression, power, exhaust, and ten geometry tests it had to pass to count as done. a provably correct simulation, not a drawing. then i left it alone and it worked. wrote the code, ran its own tests, hit failures, read them, fixed its own lines, until the engine spun and all ten went green. a real agent loop, and i watched every step. it broke three times getting here and clawed back every one. that honest part is in the reply. and this is a sneak. i've been building a show around runs exactly like this, and it's almost ready. more very soon. just getting started.

Sudo su

34,883 次观看 • 1 个月前

I had an early access to GPT-6 Astra and I can say, everyone in the world now has a 3D designer at their fingertips. I gave it an image of a house and asked to create it in 3D with all the details including toys, appliances and furniture. This a full 3D model reconstruction in Blender with geometry that you can manually tweak and run 60fps as a locally rendered "game" on device.

I had an early access to GPT-6 Astra and I can say, everyone in the world now has a 3D designer at their fingertips. I gave it an image of a house and asked to create it in 3D with all the details including toys, appliances and furniture. This a full 3D model reconstruction in Blender with geometry that you can manually tweak and run 60fps as a locally rendered "game" on device.

Tom Krcha

1,409,016 次观看 • 4 天前

Since he’s not in Paris anymore, here it is: Hudson Williams yesterday was at the balcony with Aika Flores (his hairstylist and friend) signing autographs and sending them as little paper planes and then he shouted that he ran out of paper for them to be careful with the heads and threw a clementine. via sofianealarcon & _anais_louise

Since he’s not in Paris anymore, here it is: Hudson Williams yesterday was at the balcony with Aika Flores (his hairstylist and friend) signing autographs and sending them as little paper planes and then he shouted that he ran out of paper for them to be careful with the heads and threw a clementine. via sofianealarcon & _anais_louise

Hudson Williams Updates

291,131 次观看 • 6 个月前

Before the part ever touches the machine, it's already been built. This is a 5-axis toolpath, programmed in CAM to map every angle, every pass and every cut. When it's ready, that program goes straight to our DMG MORI. The machine rotates and the tool engages. Then, it executes exactly what you see on screen, with extreme precision. Five axes of motion provide complex geometry in a single setup, with better accuracy. This is precision manufacturing for satellites at our factory in Northern California. 🇺🇸

Before the part ever touches the machine, it's already been built. This is a 5-axis toolpath, programmed in CAM to map every angle, every pass and every cut. When it's ready, that program goes straight to our DMG MORI. The machine rotates and the tool engages. Then, it executes exactly what you see on screen, with extreme precision. Five axes of motion provide complex geometry in a single setup, with better accuracy. This is precision manufacturing for satellites at our factory in Northern California. 🇺🇸

Astranis Space Technologies

12,599 次观看 • 4 个月前

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0 is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0 is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:

Stefan 3D AI

36,034 次观看 • 1 个月前

✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan

✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan

@levelsio

112,930 次观看 • 1 年前

Merkaba isn't the vehicle, it's the road. Pleiadians teach us that "merkaba" is the divine geometric structure permeating our reality which can be harnessed to open portals. People in ancient times confused the opening of portals with the crafts traveling through them. Higher beings don't literally travel in sacred geometry flying in the air. Merkaba is the natural force that will allow the portals to open and shift us to Sheen at Elder Ikai's command. ------- #NEIOH - "In ancient dreams, many large crafts were described as wheels within wheels as lights covered the skies in mesmerizing colors. Many of these shapes were Merkaba and this shape is still noted on Earth as sacred geometry. All life forms contain patterns of sacred geometry. Whether a leaf, tree or rock, a pattern of creation is present. Your body, the water you drink and all creatures that live in your world are composed of holographic patterns of beauty. You are not random in your intricate nature of being. You were planned and created with a masterful intent. As you move and live in this moment, find peace in knowing that one spirit holds all life. You only need to shift your awareness to feel the enormity of gifts available. Know that living Merkaba surround everything in a frequency unseen. Merkaba are extremely powerful and are there to shift you into 5-D Sheen. The great portal around the Earth will transport spirit and consciousness in one instant. Merkaba is the frequency that powers the moment of this change."

Merkaba isn't the vehicle, it's the road. Pleiadians teach us that "merkaba" is the divine geometric structure permeating our reality which can be harnessed to open portals. People in ancient times confused the opening of portals with the crafts traveling through them. Higher beings don't literally travel in sacred geometry flying in the air. Merkaba is the natural force that will allow the portals to open and shift us to Sheen at Elder Ikai's command. ------- #NEIOH - "In ancient dreams, many large crafts were described as wheels within wheels as lights covered the skies in mesmerizing colors. Many of these shapes were Merkaba and this shape is still noted on Earth as sacred geometry. All life forms contain patterns of sacred geometry. Whether a leaf, tree or rock, a pattern of creation is present. Your body, the water you drink and all creatures that live in your world are composed of holographic patterns of beauty. You are not random in your intricate nature of being. You were planned and created with a masterful intent. As you move and live in this moment, find peace in knowing that one spirit holds all life. You only need to shift your awareness to feel the enormity of gifts available. Know that living Merkaba surround everything in a frequency unseen. Merkaba are extremely powerful and are there to shift you into 5-D Sheen. The great portal around the Earth will transport spirit and consciousness in one instant. Merkaba is the frequency that powers the moment of this change."

Kab

96,224 次观看 • 10 个月前

As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)

As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)

Stability AI

181,554 次观看 • 1 年前

Comparing AI video results: • Gen-3 • Kling AI 1.5 • Hailuo MiniMax • Luma Dream Machine I used a FLUX1.1 [pro] image as the input. Each model ran the same prompt 3 times, and I chose the best results: "Smooth side tracking shot of a woman jogging at twilight with the city skyline in the background, sharp focus on the woman as she pumps her arms with each stride as she jogs, depth of field, advertising commercial" Running, jogging, and walking are difficult for AI video models, and none of them produced a smooth result, but this is the worst they will be.

Comparing AI video results: • Gen-3 • Kling AI 1.5 • Hailuo MiniMax • Luma Dream Machine I used a FLUX1.1 [pro] image as the input. Each model ran the same prompt 3 times, and I chose the best results: "Smooth side tracking shot of a woman jogging at twilight with the city skyline in the background, sharp focus on the woman as she pumps her arms with each stride as she jogs, depth of field, advertising commercial" Running, jogging, and walking are difficult for AI video models, and none of them produced a smooth result, but this is the worst they will be.

Heather Cooper

57,699 次观看 • 1 年前

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 • 1 个月前

A 22-YEAR-OLD IN CHINA SOLD HER VIRAL AI REELS TO 6 LOCAL BUSINESSES AND CLEARED $11,900 LAST MONTH She never filmed a thing. She tracked 40 faceless channels in one sheet and scored every clip that beat its own channel. One line ran the sort: views over the channel's median. Anything past 30 was a format she could reskin that week. The AI-video look was blowing up on Douyin, so she took the shape and ran it in english first. For $50 a month in apps she found the format on Monday and shipped by Wednesday. Claude prompted each format into 30 shot lists. CapCut generated the whole clip, a photoreal AI girl in a full scene, with AI voice and captions. Make posted to 3 platforms and fed the numbers back into the same sheet, so her own hits fed the next batch. She walked into a boutique with a phone and a page of outlier scores. She left with a retainer for 20 AI videos a month. A studio needs a model, a crew, and a shoot day for one clip. She generated hers overnight. Every prompt and the scenario are in the article.

A 22-YEAR-OLD IN CHINA SOLD HER VIRAL AI REELS TO 6 LOCAL BUSINESSES AND CLEARED $11,900 LAST MONTH She never filmed a thing. She tracked 40 faceless channels in one sheet and scored every clip that beat its own channel. One line ran the sort: views over the channel's median. Anything past 30 was a format she could reskin that week. The AI-video look was blowing up on Douyin, so she took the shape and ran it in english first. For $50 a month in apps she found the format on Monday and shipped by Wednesday. Claude prompted each format into 30 shot lists. CapCut generated the whole clip, a photoreal AI girl in a full scene, with AI voice and captions. Make posted to 3 platforms and fed the numbers back into the same sheet, so her own hits fed the next batch. She walked into a boutique with a phone and a page of outlier scores. She left with a retainer for 20 AI videos a month. A studio needs a model, a crew, and a shoot day for one clip. She generated hers overnight. Every prompt and the scenario are in the article.

Fokki

82,687 次观看 • 2 个月前

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

Santiago

30,244 次观看 • 2 个月前

🚨 AI MAY HAVE JUST SHATTERED A MATHEMATICAL BELIEF THAT STOOD FOR 80 YEARS. A geometry problem posed by legendary mathematician Paul Erdős in 1946 may have just been overturned… by an AI. The problem sounds simple on the surface: How many pairs of dots can exist on a flat plane while all being exactly the same distance apart? For decades, mathematicians believed there was a strict upper limit to how fast those equal-distance pairs could grow. But OpenAI’s internal model found something unexpected: There may be no universal limit at all. Using high-dimensional geometry and abstract number structures far beyond human visual intuition, the AI generated hundreds of pages of rigorous reasoning showing you can create vastly more unit-distance relationships than experts ever thought possible. Why this matters: It challenges one of the longest-standing open problems in discrete geometry. It shows AI isn’t just solving known problems faster it’s discovering entirely new mathematical territory. It raises the real possibility that machines can now explore abstract realities humans never even thought to search for. The deeper implication is almost unsettling: For centuries, mathematics was considered the purest form of human reasoning. Now AI may be helping expand the very boundaries of proof itself finding truths no human mind can fully grasp intuitively. What happens when machines start discovering mathematical realities that feel alien even to the mathematicians who study them?

🚨 AI MAY HAVE JUST SHATTERED A MATHEMATICAL BELIEF THAT STOOD FOR 80 YEARS. A geometry problem posed by legendary mathematician Paul Erdős in 1946 may have just been overturned… by an AI. The problem sounds simple on the surface: How many pairs of dots can exist on a flat plane while all being exactly the same distance apart? For decades, mathematicians believed there was a strict upper limit to how fast those equal-distance pairs could grow. But OpenAI’s internal model found something unexpected: There may be no universal limit at all. Using high-dimensional geometry and abstract number structures far beyond human visual intuition, the AI generated hundreds of pages of rigorous reasoning showing you can create vastly more unit-distance relationships than experts ever thought possible. Why this matters: It challenges one of the longest-standing open problems in discrete geometry. It shows AI isn’t just solving known problems faster it’s discovering entirely new mathematical territory. It raises the real possibility that machines can now explore abstract realities humans never even thought to search for. The deeper implication is almost unsettling: For centuries, mathematics was considered the purest form of human reasoning. Now AI may be helping expand the very boundaries of proof itself finding truths no human mind can fully grasp intuitively. What happens when machines start discovering mathematical realities that feel alien even to the mathematicians who study them?

TheNewPhysics

15,516 次观看 • 3 个月前

We just launched Claude Sonnet 4.5 and “Imagine with Claude”, a 5-day preview that creates dynamic experiences for you in real-time (and the first product I’ve worked on at Anthropic!). It pioneers the concept of “model-as-backend”, using a model to not only generate interfaces on the fly but also power all the functionality behind it – all made possible by our newest model, Claude Sonnet 4.5. Here’s a "choose your own adventure" version of my founder journey, as retold by Imagine with Claude:

We just launched Claude Sonnet 4.5 and “Imagine with Claude”, a 5-day preview that creates dynamic experiences for you in real-time (and the first product I’ve worked on at Anthropic!). It pioneers the concept of “model-as-backend”, using a model to not only generate interfaces on the fly but also power all the functionality behind it – all made possible by our newest model, Claude Sonnet 4.5. Here’s a "choose your own adventure" version of my founder journey, as retold by Imagine with Claude:

Sean Strong

115,693 次观看 • 11 个月前

TIMED DIALOGUE IN A NIGHTCLUB. THREE WALLS FALL AT ONCE. Nightclub sketch, cut in two halves. Black-and-white first - a couple making out on a couch, someone laughing off-camera. Then color reveals the setup: guy walks up with a drink, delivers a line, she gives him a one-sentence answer that changes the picture, he pauses, then kisses her anyway. None of them exist. It's fully generated, both halves. - What used to be four problems is now one clip Character consistency across a cut - same two faces in B&W and in color. Two-person dialogue with alternating lip sync - three separate English lines, all on time, all matching mouth shapes. Nightclub lighting - low light, saturated color wash, moving sources - was the last hard lighting environment for AI video to render without collapsing into noise. And a kiss - two faces contacting without merging into each other, which has been one of the persistent tells. Any one of these has been solvable for maybe six months. All four in one sketch was still a demo-reel problem in early 2026. - The B&W cut is doing two jobs The editing choice isn't style. It's engineering. Splitting a 15-second sketch into two 5-7 second clips means the model only has to hold consistency inside each segment, not across the whole thing. Monochrome also hides small differences between the two generations - if the girl's face is 3% off between the halves, B&W flattens the delta. Color grading in the second half does the reverse job. Two seams, both hidden by the aesthetic. - The comic beat is the actual craft Generating a kiss is one problem. Generating a kiss that lands as a punchline is a different one. The half-second where he pauses, processes, and decides not to care - that timing has to be prompted specifically. The default output of every current model is a rushed sequence with no beats. Deadpan comic delivery out of AI video means the operator wrote the prompt the way a screenwriter would - pauses, reactions, holds, all specified frame by frame. - What it costs Two 5-7 second clips at $3-5 each with in-model audio. Locked character references for both actors so the faces match across the cut. Prompt structured as a mini-script with beat notation. Realistically 40-60 rerolls to land the timing on all three spoken lines and the kiss. Under $200 in compute. A weekend from concept to publish-ready. - What this actually opens Short-form comedy has been the one segment of content nobody was making with AI video yet, because you can't fake comic timing when your output has drift and glitches. That barrier just came down. Which means every sketch account, every meme page, every stand-up clip factory now has a pipeline that doesn't require booking actors, renting a location, or getting a laugh out of a live crew. That's a real shift in a market that produces billions of views a month.

TIMED DIALOGUE IN A NIGHTCLUB. THREE WALLS FALL AT ONCE. Nightclub sketch, cut in two halves. Black-and-white first - a couple making out on a couch, someone laughing off-camera. Then color reveals the setup: guy walks up with a drink, delivers a line, she gives him a one-sentence answer that changes the picture, he pauses, then kisses her anyway. None of them exist. It's fully generated, both halves. - What used to be four problems is now one clip Character consistency across a cut - same two faces in B&W and in color. Two-person dialogue with alternating lip sync - three separate English lines, all on time, all matching mouth shapes. Nightclub lighting - low light, saturated color wash, moving sources - was the last hard lighting environment for AI video to render without collapsing into noise. And a kiss - two faces contacting without merging into each other, which has been one of the persistent tells. Any one of these has been solvable for maybe six months. All four in one sketch was still a demo-reel problem in early 2026. - The B&W cut is doing two jobs The editing choice isn't style. It's engineering. Splitting a 15-second sketch into two 5-7 second clips means the model only has to hold consistency inside each segment, not across the whole thing. Monochrome also hides small differences between the two generations - if the girl's face is 3% off between the halves, B&W flattens the delta. Color grading in the second half does the reverse job. Two seams, both hidden by the aesthetic. - The comic beat is the actual craft Generating a kiss is one problem. Generating a kiss that lands as a punchline is a different one. The half-second where he pauses, processes, and decides not to care - that timing has to be prompted specifically. The default output of every current model is a rushed sequence with no beats. Deadpan comic delivery out of AI video means the operator wrote the prompt the way a screenwriter would - pauses, reactions, holds, all specified frame by frame. - What it costs Two 5-7 second clips at $3-5 each with in-model audio. Locked character references for both actors so the faces match across the cut. Prompt structured as a mini-script with beat notation. Realistically 40-60 rerolls to land the timing on all three spoken lines and the kiss. Under $200 in compute. A weekend from concept to publish-ready. - What this actually opens Short-form comedy has been the one segment of content nobody was making with AI video yet, because you can't fake comic timing when your output has drift and glitches. That barrier just came down. Which means every sketch account, every meme page, every stand-up clip factory now has a pipeline that doesn't require booking actors, renting a location, or getting a laugh out of a live crew. That's a real shift in a market that produces billions of views a month.

capONE 💎

82,533 次观看 • 23 天前

If this contract had gone live, attackers would have drained every single ETH within hours. A crowdfunding platform. Clean-looking Solidity. Ready for mainnet. The dev team was confident. Then we ran it through V2's AI Smart Contract Auditor. 9 vulnerabilities detected. 1 critical. 2 high. Under 20 minutes. The critical finding? A textbook reentrancy bug in claimRefund(). The contract sent ETH before zeroing the user's balance. An attacker could re-enter the function during the transfer and drain the same refund repeatedly until the entire contract was empty. Every backer's funds across every campaign, gone in one transaction. It also caught an emergencyWithdraw() function that let the owner pull the entire contract balance with zero restrictions. Active campaigns, pending refunds, everything. One compromised key and it's a complete rug. Plus an uncapped platform fee that could be set to 100% (creators get nothing) or above 100% (permanent DoS on all fund claims). The AI generated a 24-page report with severity classifications, exact code locations, detailed attack scenarios, and specific fixes for each issue. Final score: 89/100. Not because it was "pretty good," but because the architecture was sound and the issues were fixable. Without catching them though? Catastrophic. A traditional audit runs $5K to $50K and takes weeks. This took under 20 minutes. That's the power of V2 ⚡️

If this contract had gone live, attackers would have drained every single ETH within hours. A crowdfunding platform. Clean-looking Solidity. Ready for mainnet. The dev team was confident. Then we ran it through V2's AI Smart Contract Auditor. 9 vulnerabilities detected. 1 critical. 2 high. Under 20 minutes. The critical finding? A textbook reentrancy bug in claimRefund(). The contract sent ETH before zeroing the user's balance. An attacker could re-enter the function during the transfer and drain the same refund repeatedly until the entire contract was empty. Every backer's funds across every campaign, gone in one transaction. It also caught an emergencyWithdraw() function that let the owner pull the entire contract balance with zero restrictions. Active campaigns, pending refunds, everything. One compromised key and it's a complete rug. Plus an uncapped platform fee that could be set to 100% (creators get nothing) or above 100% (permanent DoS on all fund claims). The AI generated a 24-page report with severity classifications, exact code locations, detailed attack scenarios, and specific fixes for each issue. Final score: 89/100. Not because it was "pretty good," but because the architecture was sound and the issues were fixable. Without catching them though? Catastrophic. A traditional audit runs $5K to $50K and takes weeks. This took under 20 minutes. That's the power of V2 ⚡️

ChainGPT

26,504 次观看 • 5 个月前

Polymorphic moulding: a manufacturing method that forms parts using a grid of computer-controlled pins: Each pin can move up or down independently, so together they shape a surface that acts like a custom mould. Instead of building a fixed mould for every product, the machine quickly repositions the pins to match a new digital model. This means a mould can be created in minutes, used, and then reshaped again for the next design. Because the hardware stays the same and only its configuration changes: > no permanent tooling is needed > very little material is wasted > setup time between products is minimal The system essentially turns mould making into a programmable process. Engineers send a design file, the pins form the mould geometry, and the material is cast or formed inside it. Especially useful for rapid prototyping and customised manufacturing, where many different shapes must be produced in small quantities without rebuilding tools each time. Credit: ---- Weekly robotics and AI insights. Subscribe free:

Polymorphic moulding: a manufacturing method that forms parts using a grid of computer-controlled pins: Each pin can move up or down independently, so together they shape a surface that acts like a custom mould. Instead of building a fixed mould for every product, the machine quickly repositions the pins to match a new digital model. This means a mould can be created in minutes, used, and then reshaped again for the next design. Because the hardware stays the same and only its configuration changes: > no permanent tooling is needed > very little material is wasted > setup time between products is minimal The system essentially turns mould making into a programmable process. Engineers send a design file, the pins form the mould geometry, and the material is cast or formed inside it. Especially useful for rapid prototyping and customised manufacturing, where many different shapes must be produced in small quantities without rebuilding tools each time. Credit: ---- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

38,234 次观看 • 6 个月前

A 23-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE - AND NONE OF THEM CAN LIE TO HIM he opens the dashboard live: 300 Kimi K3 agents firing in parallel, Opus 5 checking every single output against its source > pointed at 100 EV-market companies > first pass - 12 failed: wrong revenue, dead citations, empty fields > second pass - 3 failed > third pass - zero, every row filed straight into an Obsidian vault loop engineering with teeth: it refuses to stop while anything is still wrong

A 23-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE - AND NONE OF THEM CAN LIE TO HIM he opens the dashboard live: 300 Kimi K3 agents firing in parallel, Opus 5 checking every single output against its source > pointed at 100 EV-market companies > first pass - 12 failed: wrong revenue, dead citations, empty fields > second pass - 3 failed > third pass - zero, every row filed straight into an Obsidian vault loop engineering with teeth: it refuses to stop while anything is still wrong

Mr. Buzzoni

1,088,816 次观看 • 19 天前