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Last night, I said if Electron can beat Tauri this badly, native should be disgusting. Well... the results for the GPUI version of @Cap are in😲 GPUI vs Tauri: 77% lower CPU. 88% less memory. GPUI vs Electron: 67% lower CPU. 57% less memory. Yes. Native is disgusting.

Richie

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103,703 görüntüleme • 24 gün önce •via X (Twitter)

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i'm writing my own gui framework in c++ and rewriting my image editor using it, which is going good so far, i wanted to move from swiftui, qt, tauri, electron, react native, and flutter so i can use metal and directx gpu apis on macos and windows as much as possible,so i think going full metal/directx is the way to go i know i have a very hard and long way to go though as there are many many flaws,bugs in this very very early version and doesnt utilize the gpu as much as i want to but i hope we will get there soon ,i also need to make the ui look somewhat decent instead of whatever mess it is right now

i'm writing my own gui framework in c++ and rewriting my image editor using it, which is going good so far, i wanted to move from swiftui, qt, tauri, electron, react native, and flutter so i can use metal and directx gpu apis on macos and windows as much as possible,so i think going full metal/directx is the way to go i know i have a very hard and long way to go though as there are many many flaws,bugs in this very very early version and doesnt utilize the gpu as much as i want to but i hope we will get there soon ,i also need to make the ui look somewhat decent instead of whatever mess it is right now

Ruben Veidt

85,053 görüntüleme • 1 yıl önce

Scenes after Uruguay vs Columbia were disgusting! Drunk Columbian fans went after the families of Uruguayan players which led Darwin Nunez and other players to climb into the stands to protect their family. This is another reason why alcohol should be banned in the stadiums! If you can't stay sober for 90 mins you have a serious problem.

Scenes after Uruguay vs Columbia were disgusting! Drunk Columbian fans went after the families of Uruguayan players which led Darwin Nunez and other players to climb into the stands to protect their family. This is another reason why alcohol should be banned in the stadiums! If you can't stay sober for 90 mins you have a serious problem.

drag

203,933 görüntüleme • 2 yıl önce

The worst one yet… this is the disabled toilet in @koynlondon last night. When I asked them about it, they said, “It’s not the disabled toilet; it’s a storage cupboard”. I then asked them to show me where the disabled toilet was. They responded, “Uhhh, well, we can clear it out.” Disgusting attitude. It is high time that councils go around and inspect restaurant-disabled toilets and give on-the-spot fines for misuse!!!

The worst one yet… this is the disabled toilet in @koynlondon last night. When I asked them about it, they said, “It’s not the disabled toilet; it’s a storage cupboard”. I then asked them to show me where the disabled toilet was. They responded, “Uhhh, well, we can clear it out.” Disgusting attitude. It is high time that councils go around and inspect restaurant-disabled toilets and give on-the-spot fines for misuse!!!

Stoma Babe

141,593 görüntüleme • 2 yıl önce

THE SICK LEECHES THAT WE ARE!!! 🤢 Disgusting and absolutely pathetic! 🤮 How actress Nidi Agarwal was mobbed by so called ‘fans’ after a film event….is a reflection of how rotten we are as a society! I feel really sorry for her and I hope she is okay! Women in this country are subjected to mobbing / molestation at various levels- from buses to temples to movies. Very few women are lucky enough to escape this absolutely disgusting behaviour. Actresses are unfortunately considered public property. Yes! That is how cheap we are. I hope the organizers/ Nidi Agarwal’s team identifies these leeches and files a police complaint against how many ever disgusting creatures as possible. Also - I am not sure if they will be prosecuted. But a fear needs to start somewhere. This disgusting filth, the sorry excuse of men should know that they won’t get away with such behaviour. Someone needs to teach them a lesson.

THE SICK LEECHES THAT WE ARE!!! 🤢 Disgusting and absolutely pathetic! 🤮 How actress Nidi Agarwal was mobbed by so called ‘fans’ after a film event….is a reflection of how rotten we are as a society! I feel really sorry for her and I hope she is okay! Women in this country are subjected to mobbing / molestation at various levels- from buses to temples to movies. Very few women are lucky enough to escape this absolutely disgusting behaviour. Actresses are unfortunately considered public property. Yes! That is how cheap we are. I hope the organizers/ Nidi Agarwal’s team identifies these leeches and files a police complaint against how many ever disgusting creatures as possible. Also - I am not sure if they will be prosecuted. But a fear needs to start somewhere. This disgusting filth, the sorry excuse of men should know that they won’t get away with such behaviour. Someone needs to teach them a lesson.

Revathi

144,056 görüntüleme • 8 ay önce

I always wondered "What if I port my three.js game to Rust? Will it improve performance?" I finally ported it to both Rust Desktop and Rust WASM (that runs on the browser) Comparing the three.js version with the Rust desktop I had a clear winner: Rust desktop. But now I took the time to port it to the web using Web Assembly (WASM) And my conclusion is... A tie! Both versions averaged 42FPS (60FPS if running one at a time) So if your goal is to ship a web game, it doesn't even matter the tech you use. (Three.js is recommended because the ecossystem is huge though) As long you optmize well (Web workers, reduce triangles, draw calls, etc) you should be good to go. But in the event you want to ship a native game to publish on Steam a system language (Rust, C++, etc) will be better for you. Now I want to port the three.js game to Desktop using Electron and see the results. I'll let you know. Btw, I'm open to new freelance projects. If you have anything for me, my DMs are open!

I always wondered "What if I port my three.js game to Rust? Will it improve performance?" I finally ported it to both Rust Desktop and Rust WASM (that runs on the browser) Comparing the three.js version with the Rust desktop I had a clear winner: Rust desktop. But now I took the time to port it to the web using Web Assembly (WASM) And my conclusion is... A tie! Both versions averaged 42FPS (60FPS if running one at a time) So if your goal is to ship a web game, it doesn't even matter the tech you use. (Three.js is recommended because the ecossystem is huge though) As long you optmize well (Web workers, reduce triangles, draw calls, etc) you should be good to go. But in the event you want to ship a native game to publish on Steam a system language (Rust, C++, etc) will be better for you. Now I want to port the three.js game to Desktop using Electron and see the results. I'll let you know. Btw, I'm open to new freelance projects. If you have anything for me, my DMs are open!

André → andreelias.dev

19,531 görüntüleme • 3 ay önce

Unsure the level of concern at the moment (1.09 FIP + 27.5 K-BB%) but I think it's worth nothing that Sanchez's FB velo is down: First 3 G (2026): • 94.4 MPH (-2.1) • 94.3 MPH (-1.5) • 94.6 MPH (-0.6) *(L: '26, R: '25)* Last year: • Sanchez was a bit more efficient w/ his hip + shoulder separation • His body was more linear, helping that center of mass move correctly. • Better lower half allowing him to keep that pelvis a bit more linear -- which is likely result of the ribcage is stacked over his pelvis + sitting in that load longer on foot strike (??) This year: • Energy is leaking from that back knee into rotation • Upper + lower working w/ each other more and less of working against one another (arm doing more than it should) • His pelvis is noticeably tipping down through rotation (not a direct cue but more of a result of less lower half activation) Angles/WBC fatigue could also be at play here as well -- but assuming they're not could be some things to clean up

Unsure the level of concern at the moment (1.09 FIP + 27.5 K-BB%) but I think it's worth nothing that Sanchez's FB velo is down: First 3 G (2026): • 94.4 MPH (-2.1) • 94.3 MPH (-1.5) • 94.6 MPH (-0.6) (L: '26, R: '25) Last year: • Sanchez was a bit more efficient w/ his hip + shoulder separation • His body was more linear, helping that center of mass move correctly. • Better lower half allowing him to keep that pelvis a bit more linear -- which is likely result of the ribcage is stacked over his pelvis + sitting in that load longer on foot strike (??) This year: • Energy is leaking from that back knee into rotation • Upper + lower working w/ each other more and less of working against one another (arm doing more than it should) • His pelvis is noticeably tipping down through rotation (not a direct cue but more of a result of less lower half activation) Angles/WBC fatigue could also be at play here as well -- but assuming they're not could be some things to clean up

Joseph Cammisa

43,317 görüntüleme • 5 ay önce

You don't need a GPU for fast studio grade voice cloning anymore. Qwen3 TTS (1.7B Q4_K_M) + mainline llama.cpp is officially the fastest way to generate zero shot voice clones using 100% pure CPU execution. Following up on my last post where we ran the Q8 model on a GPU, we just took local C++ voice synthesis a massive step further. The open source community quantized Alibaba's SOTA Qwen3 TTS model down to Q4_K_M GGUF, completely freeing local audio pipelines from dedicated graphics hardware. Here is the real world benchmark and hardware breakdown of running SOTA voice cloning on CPU: # Architecture & Model Setup Using Qwen3-TTS-12Hz-1.7B-Base-Q4_K_M.gguf paired with the 8 bit multimodal projector (mmproj-Q8_0.gguf), llama.cpp executes the entire pipeline in pure C++. No PyTorch, no CUDA dependencies, and no VRAM bottlenecks. # Real-World Memory Footprint - Baseline RAM: 1.6 GB system idle. - Peak Generation RAM: 8 GB RAM during active voice synthesis. - Requirement: Any basic machine with at least 8 GB of system RAM can run this easily. # Real World CPU Benchmarks - Google Colab Free Tier (Throttled 2 Core CPU): Synthesizes a 5 sec studio quality audio clip (~8 words) in 45 seconds. - Modern Consumer CPU (Intel i5/i7 13th/14th Gen or AMD Ryzen 7000/9000): generation should drop to 5 to 20 seconds (nearly 1:1 real-time generation speed!). # Zero Shot Voice Cloning Quality Pass any 5 to 20 second .wav audio sample to the C++ engine using the --tts-speaker-file flag. It yields clean, natural sounding cloned speech with virtually zero quality loss compared to unquantized FP16 weights. To make testing seamless, I built an updated zero config Google Colab notebook. It pulls the official pre built llama.cpp CPU binaries (zero compilation time!) launches a live Gradio web app right in your browser. Record a 5 second clip from your mic (or drop a .mp3, .wav file), type text, and generate cloned audio on CPU. Native C++ audio models are making edge based, offline AI voice agents a reality. Links to the free Q4 CPU Colab notebook and the Q4_K_M GGUF HuggingFace repository are in the replies below! Which models have you been running on your CPUs? What CPU hardware are you using for local inference?

You don't need a GPU for fast studio grade voice cloning anymore. Qwen3 TTS (1.7B Q4_K_M) + mainline llama.cpp is officially the fastest way to generate zero shot voice clones using 100% pure CPU execution. Following up on my last post where we ran the Q8 model on a GPU, we just took local C++ voice synthesis a massive step further. The open source community quantized Alibaba's SOTA Qwen3 TTS model down to Q4_K_M GGUF, completely freeing local audio pipelines from dedicated graphics hardware. Here is the real world benchmark and hardware breakdown of running SOTA voice cloning on CPU: # Architecture & Model Setup Using Qwen3-TTS-12Hz-1.7B-Base-Q4_K_M.gguf paired with the 8 bit multimodal projector (mmproj-Q8_0.gguf), llama.cpp executes the entire pipeline in pure C++. No PyTorch, no CUDA dependencies, and no VRAM bottlenecks. # Real-World Memory Footprint - Baseline RAM: 1.6 GB system idle. - Peak Generation RAM: 8 GB RAM during active voice synthesis. - Requirement: Any basic machine with at least 8 GB of system RAM can run this easily. # Real World CPU Benchmarks - Google Colab Free Tier (Throttled 2 Core CPU): Synthesizes a 5 sec studio quality audio clip (~8 words) in 45 seconds. - Modern Consumer CPU (Intel i5/i7 13th/14th Gen or AMD Ryzen 7000/9000): generation should drop to 5 to 20 seconds (nearly 1:1 real-time generation speed!). # Zero Shot Voice Cloning Quality Pass any 5 to 20 second .wav audio sample to the C++ engine using the --tts-speaker-file flag. It yields clean, natural sounding cloned speech with virtually zero quality loss compared to unquantized FP16 weights. To make testing seamless, I built an updated zero config Google Colab notebook. It pulls the official pre built llama.cpp CPU binaries (zero compilation time!) launches a live Gradio web app right in your browser. Record a 5 second clip from your mic (or drop a .mp3, .wav file), type text, and generate cloned audio on CPU. Native C++ audio models are making edge based, offline AI voice agents a reality. Links to the free Q4 CPU Colab notebook and the Q4_K_M GGUF HuggingFace repository are in the replies below! Which models have you been running on your CPUs? What CPU hardware are you using for local inference?

Alok

103,956 görüntüleme • 1 ay önce

THIS $599 MAC MINI CAN DRIVE THREE DISPLAYS NATIVELY - THIS SETUP TOOK "MORE SCREEN SPACE" SO FAR IT ENDED WITH BINOCULARS. the M4 Mac mini shrinks a full desktop into a 5 x 5-inch box. the base model launched with: 10-core CPU 10-core GPU 16GB unified memory support for two 6K displays plus one 5K display the M4 Pro version can drive three 6K displays at 60Hz, pushing more than 60 million pixels at once. no DisplayLink software is required for the supported three-screen configuration. the video turns that spec into a monitor wall, then delivers the punchline when the creator reaches for binoculars. honest line: Apple guarantees up to three native displays. the clip does not prove every screen in the room is connected to this one Mac mini. the tiny computer solved the screen limit. the next bottleneck is finding the window you opened. bookmark & watch today ↓

THIS $599 MAC MINI CAN DRIVE THREE DISPLAYS NATIVELY - THIS SETUP TOOK "MORE SCREEN SPACE" SO FAR IT ENDED WITH BINOCULARS. the M4 Mac mini shrinks a full desktop into a 5 x 5-inch box. the base model launched with: 10-core CPU 10-core GPU 16GB unified memory support for two 6K displays plus one 5K display the M4 Pro version can drive three 6K displays at 60Hz, pushing more than 60 million pixels at once. no DisplayLink software is required for the supported three-screen configuration. the video turns that spec into a monitor wall, then delivers the punchline when the creator reaches for binoculars. honest line: Apple guarantees up to three native displays. the clip does not prove every screen in the room is connected to this one Mac mini. the tiny computer solved the screen limit. the next bottleneck is finding the window you opened. bookmark & watch today ↓

Grimmer

16,290 görüntüleme • 1 ay önce

First look at the TGL indoor golf arena! Are you more or less hyped? I’m starting to get interested, this looks cool. Justin Thomas and Justin Rose provide the tour. The screen is huge and it looks like a legit sports venue. If they can get some lively fans in there, it could be fun. I’m ready for casual night golf if it’s actually competitive. I see these guys caring, they have equity!

First look at the TGL indoor golf arena! Are you more or less hyped? I’m starting to get interested, this looks cool. Justin Thomas and Justin Rose provide the tour. The screen is huge and it looks like a legit sports venue. If they can get some lively fans in there, it could be fun. I’m ready for casual night golf if it’s actually competitive. I see these guys caring, they have equity!

Rick Golfs

125,555 görüntüleme • 1 yıl önce

Dear Ashwini Vaishnaw ji, We are so happy that you are relaunching the IRCTC website in 30 days. Instead of working on CAPCHA, please ensure the following: 1. The Site should not crash during Tatkal bookings. Zero crashes especially during payments. 2. Ensure that Senior Citizens get Lower Berths (even now, many Senior citizens get Middle or Upper) even if they book a little later (Algorithm can be fixed) 3. Introduce More General Coaches to accommodate more Travelers 4. Strict Penalty for Unreserved Passengers occupying Reserved Seats. Work on AI cameras to detect this 5. RAC passengers should only pay half the fare for half the seat. So, once chart is prepared, please refund the 50% fare. This can easily be incorporated using simple technology. 6. If any train is delayed for more than 2 hours, refund should be issued automatically. 10% per hour delay. This can be done with some technology. 7. People's time should be valued. Tech can be used for the same. CAPCHA can wait. These things cannot !!! Request my audience to add more points so that the new website can have all these things in next 30 days 😍 #FI

Dear Ashwini Vaishnaw ji, We are so happy that you are relaunching the IRCTC website in 30 days. Instead of working on CAPCHA, please ensure the following: 1. The Site should not crash during Tatkal bookings. Zero crashes especially during payments. 2. Ensure that Senior Citizens get Lower Berths (even now, many Senior citizens get Middle or Upper) even if they book a little later (Algorithm can be fixed) 3. Introduce More General Coaches to accommodate more Travelers 4. Strict Penalty for Unreserved Passengers occupying Reserved Seats. Work on AI cameras to detect this 5. RAC passengers should only pay half the fare for half the seat. So, once chart is prepared, please refund the 50% fare. This can easily be incorporated using simple technology. 6. If any train is delayed for more than 2 hours, refund should be issued automatically. 10% per hour delay. This can be done with some technology. 7. People's time should be valued. Tech can be used for the same. CAPCHA can wait. These things cannot !!! Request my audience to add more points so that the new website can have all these things in next 30 days 😍 #FI

Fundamental Investor ™ 🇮🇳

30,306 görüntüleme • 3 ay önce

LEG EXTENSIONS BEFORE SQUATS Here’s why: If you do your set(s) of Hack Squats BEFORE you do your set(s) of Leg Extensions, you will see a pretty large decline in your output on Leg Extensions….it might be something like 20-25% less than what you could do fresh On the contrary, if you do your set(s) of Leg Extensions BEFORE you do your set(s) of Hack Squats, you will NOT see nearly as large a decline in Hack Squat performance comparatively….the decline in Hack Squat performance may only be 5-10% less than what you could do fresh This is mostly due to the resistance profile/overall demands of each exercise and it’s the main reason I often program Leg Extensions before any sort of Squat pattern on Lower days in my training plans A subtle but GOATED fatigue management play! (Btw…you can easily verify this for yourself by A/B testing it)

Dean Turner

103,041 görüntüleme • 3 ay önce

This was a video of Kit I had animated with Atlabs AI in the past. I feel a bit more comfortable showing it because I have something better with similar scenes but extended, that I plan on posting later. Kit Bodega is obviously going through muscle growth here. Kit is owned by the maker of Gameoverse Rubber Ross. I really should have put Kit's arms were mechanical but oh well... Not much else that should be said, the new version that I plan on posting later has me considering a couple of ideas on how I can attempt MG content going forward. A link for the Atlabs website will be in the comments. If you have an atlabs account I hope the video I show on what models I use for my content helps you. Sorry for pushing the video creation back for September but I hope if you get adequate information it will be worth the wait. I also hope it gets some of you considering trying atlabs for Ai animations. The video I make might not cover muscle growth content but hopefully it should still help in showing how Ai video content can be directed. This video is sfw In every way. This video was animated with AtlabsAi. It was all done with Ai #AtlabsAi #musclegrowth #musclegrowthanimation #KitBodega

This was a video of Kit I had animated with Atlabs AI in the past. I feel a bit more comfortable showing it because I have something better with similar scenes but extended, that I plan on posting later. Kit Bodega is obviously going through muscle growth here. Kit is owned by the maker of Gameoverse Rubber Ross. I really should have put Kit's arms were mechanical but oh well... Not much else that should be said, the new version that I plan on posting later has me considering a couple of ideas on how I can attempt MG content going forward. A link for the Atlabs website will be in the comments. If you have an atlabs account I hope the video I show on what models I use for my content helps you. Sorry for pushing the video creation back for September but I hope if you get adequate information it will be worth the wait. I also hope it gets some of you considering trying atlabs for Ai animations. The video I make might not cover muscle growth content but hopefully it should still help in showing how Ai video content can be directed. This video is sfw In every way. This video was animated with AtlabsAi. It was all done with Ai #AtlabsAi #musclegrowth #musclegrowthanimation #KitBodega

CaleAi

16,568 görüntüleme • 25 gün önce

In 2020 I entered a summer shredding contest. This was my gameplan to go from 18% body fat to 10% or less body fat in 12 weeks: (Applicable no matter where you’re starting, bookmark this) 1. Eat bodyweight (in lbs) x 10-12 calories daily (more on higher activity days, less on lower) 2. Eat 1g of protein per pound of bodyweight (if you’re starting more overweight you can aim for goal bodyweight) 3. 10K+ steps daily and progressively more cardio sessions (0 - month 1, 2-3x45 minutes/wk month 2, 5-6x45 minutes month 3) 4. Lifted 5x/week on a push, pull, legs, rest, upper, lower, rest split with a focus on: - every set ending near failure - fighting to get stronger week by week - managing volume (less volume towards end of the cut for recovery) 5. Limited alcohol to only a few drinks/month 6. Slept 7 hours/night minimum 7. 5g creatine daily 8. Drank around a .75-1 gallon of water + electrolytes daily 9. Refeed days (bodyweight x 15 calorie goal), 1x/wk in month 3 The framework is really this simple to drop body fat. Adjustments will need to be made based on biofeedback & weight data. If you aren’t losing at a rate of 0.5-1% bodyweight per week, you must: - increase your average weekly movement (steps or cardio minutes) - and/or decrease your average weekly calorie intake. Hope this helps guide you to a leaner version of yourself. 🤝

In 2020 I entered a summer shredding contest. This was my gameplan to go from 18% body fat to 10% or less body fat in 12 weeks: (Applicable no matter where you’re starting, bookmark this) 1. Eat bodyweight (in lbs) x 10-12 calories daily (more on higher activity days, less on lower) 2. Eat 1g of protein per pound of bodyweight (if you’re starting more overweight you can aim for goal bodyweight) 3. 10K+ steps daily and progressively more cardio sessions (0 - month 1, 2-3x45 minutes/wk month 2, 5-6x45 minutes month 3) 4. Lifted 5x/week on a push, pull, legs, rest, upper, lower, rest split with a focus on: - every set ending near failure - fighting to get stronger week by week - managing volume (less volume towards end of the cut for recovery) 5. Limited alcohol to only a few drinks/month 6. Slept 7 hours/night minimum 7. 5g creatine daily 8. Drank around a .75-1 gallon of water + electrolytes daily 9. Refeed days (bodyweight x 15 calorie goal), 1x/wk in month 3 The framework is really this simple to drop body fat. Adjustments will need to be made based on biofeedback & weight data. If you aren’t losing at a rate of 0.5-1% bodyweight per week, you must: - increase your average weekly movement (steps or cardio minutes) - and/or decrease your average weekly calorie intake. Hope this helps guide you to a leaner version of yourself. 🤝

Chace Chambers

210,104 görüntüleme • 9 ay önce

“I love you!” By the start of the third trimester, your baby is beginning to absorb sound in the womb - with evidence suggesting they can both identify mom’s voice and the distinct rhythms and patterns of her native language at birth. Knowing that these are among our earliest learnings, don’t be surprised if your little one begins to mimic the musicality of certain words and phrases well before they explode into language near the end of the first year. In fact, this musicality or “prosody” is even displayed in your baby’s cries. That’s right: babies cry with an accent. With all this in mind, check out this little guy (shared to TT by bri_col44), who - at 3 months - sure appears to have said “I love you.” Developmentally, it’s probably a little early for the phrase to be associated with meaning (with our first communicative words typically emerging between 10-14 months), but amazing how well this little one matches mom’s phrasing, even as articulation and understanding are continuing to develop. It all a part of the amazing process of language development. And that’s not to even mention that smile! There’s truly nothing better.

“I love you!” By the start of the third trimester, your baby is beginning to absorb sound in the womb - with evidence suggesting they can both identify mom’s voice and the distinct rhythms and patterns of her native language at birth. Knowing that these are among our earliest learnings, don’t be surprised if your little one begins to mimic the musicality of certain words and phrases well before they explode into language near the end of the first year. In fact, this musicality or “prosody” is even displayed in your baby’s cries. That’s right: babies cry with an accent. With all this in mind, check out this little guy (shared to TT by bri_col44), who - at 3 months - sure appears to have said “I love you.” Developmentally, it’s probably a little early for the phrase to be associated with meaning (with our first communicative words typically emerging between 10-14 months), but amazing how well this little one matches mom’s phrasing, even as articulation and understanding are continuing to develop. It all a part of the amazing process of language development. And that’s not to even mention that smile! There’s truly nothing better.

Dan Wuori

32,265 görüntüleme • 1 yıl önce

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

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

slash1s

156,699 görüntüleme • 5 ay önce

48 consistent camera feeds of me all from one casual video capture. This is 4DAnyone. I am testing it out over the holiday week, the goal is 4D Gaussian Splatting from a single camera. Should out to Pablo Vela' for inspiring me to use Rerun to visualize my progress. Right now you see 6 cameras, but I can cycle through all 48. I hacked together this visualization using ChatGPT's new Astra model in VS Code. Literally took less than 10 minutes. More coming soon. Learn more about 4DAnyone Here: You can also try Pablo's 6 view 4DAnyone generator on Hugging Face here: Jeremy Park, PhD Robert Scoble #Computervision #3D #4DGS

48 consistent camera feeds of me all from one casual video capture. This is 4DAnyone. I am testing it out over the holiday week, the goal is 4D Gaussian Splatting from a single camera. Should out to Pablo Vela' for inspiring me to use Rerun to visualize my progress. Right now you see 6 cameras, but I can cycle through all 48. I hacked together this visualization using ChatGPT's new Astra model in VS Code. Literally took less than 10 minutes. More coming soon. Learn more about 4DAnyone Here: You can also try Pablo's 6 view 4DAnyone generator on Hugging Face here: Jeremy Park, PhD Robert Scoble #Computervision #3D #4DGS

Jonathan Stephens

12,549 görüntüleme • 6 gün önce