Загрузка видео...

Не удалось загрузить видео

На главную

img2threejs - v1.4 is officially released 🚀 This release is all about reconstruction quality. ✨ What’s new: 1. Real internal structures instead of hollow shells 2. More accurate colors & PBR materials 3. Fine-grained parts for complex animations 4. Better volumetric reconstruction (not simple extrusions) 5 Measurement-driven geometry for...

NickDevFE's profile picture

Nick

2,039 subscribers

76,086 просмотров • 1 месяц назад •via X (Twitter)

Наука и технологииОбразованиеИгры
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

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)
0:30

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

hy3 vs mimo-v2.5 vs deepseek v4 flash vs minimax m3 the four models on top of the openrouter leaderboard by tokens this week: #1 hy3 (Tencent Hy) – 7.5t #2 mimo-v2.5 (Xiaomi MiMo) – 6.56t #3 deepseek v4 flash (DeepSeek) – 5.24t #4 minimax m3 (MiniMax (official)) – 4.21t so we tested them. 3 prompts, single-file html, Three.js from a cdn, fully procedural, no external assets. all run via AI/ML API each prompt is a transparent cutaway machine that has to be mechanically correct, not decorative: • 4-stroke engine with full oil circulation – slider-crank kinematics, cam at 2:1, valve lift driven by lobes, oil loop from sump to gallery to big-end • watt walking-beam steam engine – four-bar vector-loop closure, eccentric-driven slide valve, steam events synced to real port position • francis reaction water turbine – 20 guide vanes on a regulating ring, 17 lofted runner blades, gpu particle advection, precessing vortex rope at part load the takeaway up front: none of the four cleared all three scenes on the first attempt. but the price spread between them is roughly 70x – hy3 fixed included costs less than two cents overall results (summed across all 3 scenes): cost #1 hy3 – $0.016 #2 deepseek v4 flash – $0.025 #3 mimo-v2.5 – $0.97 #4 minimax m3 – $1.17 tokens #1 hy3 – 19,326 #2 deepseek v4 flash – 63,126 #3 mimo-v2.5 – 322,523 #4 minimax m3 – 702,900 lines of code #1 hy3 – 1,047 #2 mimo-v2.5 – 2,759 #3 deepseek v4 flash – 3,273 #4 minimax m3 – 3,354 scenes needing a second attempt #1 hy3 – 1 (engine) #1 mimo-v2.5 – 1 (turbine) #1 minimax m3 – 1 (turbine) #4 deepseek v4 flash – 2 (steam engine, turbine) observations: 1. the token spread is the real story – minimax burns 36x hy3's tokens and lands in the same place, one retry, ~3.3k lines 2. hy3 is the outlier on density: 1,047 lines total, fewest tokens, cheapest run, and only one scene needed a second pass. deepseek is the opposite trade – near-hy3 pricing but the most retries 3. mimo and minimax seem to overthink instead of writing the code. minimax spent 359.1k tokens on the steam engine and produced 1,346 lines – the tokens are going somewhere other than the file 4. the francis turbine broke three of the four. the spec that separates them is the one with 20 linked guide vanes and gpu particle advection, not the one with the most parts overall impression: none of these models excelled at any of the tasks we gave them. but they were close, and they were extremely cheap. the gap that matters isn't quality anymore – it's that hy3 ran all three scenes for less than two cents while the frontier labs charge dollars for the same work right now you pick these because they're good for the zero price you pay. soon that's something openai and anthropic will have to think about follow thehype. for 24/7 ai news, analysis and breakdowns
0:55

hy3 vs mimo-v2.5 vs deepseek v4 flash vs minimax m3 the four models on top of the openrouter leaderboard by tokens this week: #1 hy3 (Tencent Hy) – 7.5t #2 mimo-v2.5 (Xiaomi MiMo) – 6.56t #3 deepseek v4 flash (DeepSeek) – 5.24t #4 minimax m3 (MiniMax (official)) – 4.21t so we tested them. 3 prompts, single-file html, Three.js from a cdn, fully procedural, no external assets. all run via AI/ML API each prompt is a transparent cutaway machine that has to be mechanically correct, not decorative: • 4-stroke engine with full oil circulation – slider-crank kinematics, cam at 2:1, valve lift driven by lobes, oil loop from sump to gallery to big-end • watt walking-beam steam engine – four-bar vector-loop closure, eccentric-driven slide valve, steam events synced to real port position • francis reaction water turbine – 20 guide vanes on a regulating ring, 17 lofted runner blades, gpu particle advection, precessing vortex rope at part load the takeaway up front: none of the four cleared all three scenes on the first attempt. but the price spread between them is roughly 70x – hy3 fixed included costs less than two cents overall results (summed across all 3 scenes): cost #1 hy3 – $0.016 #2 deepseek v4 flash – $0.025 #3 mimo-v2.5 – $0.97 #4 minimax m3 – $1.17 tokens #1 hy3 – 19,326 #2 deepseek v4 flash – 63,126 #3 mimo-v2.5 – 322,523 #4 minimax m3 – 702,900 lines of code #1 hy3 – 1,047 #2 mimo-v2.5 – 2,759 #3 deepseek v4 flash – 3,273 #4 minimax m3 – 3,354 scenes needing a second attempt #1 hy3 – 1 (engine) #1 mimo-v2.5 – 1 (turbine) #1 minimax m3 – 1 (turbine) #4 deepseek v4 flash – 2 (steam engine, turbine) observations: 1. the token spread is the real story – minimax burns 36x hy3's tokens and lands in the same place, one retry, ~3.3k lines 2. hy3 is the outlier on density: 1,047 lines total, fewest tokens, cheapest run, and only one scene needed a second pass. deepseek is the opposite trade – near-hy3 pricing but the most retries 3. mimo and minimax seem to overthink instead of writing the code. minimax spent 359.1k tokens on the steam engine and produced 1,346 lines – the tokens are going somewhere other than the file 4. the francis turbine broke three of the four. the spec that separates them is the one with 20 linked guide vanes and gpu particle advection, not the one with the most parts overall impression: none of these models excelled at any of the tasks we gave them. but they were close, and they were extremely cheap. the gap that matters isn't quality anymore – it's that hy3 ran all three scenes for less than two cents while the frontier labs charge dollars for the same work right now you pick these because they're good for the zero price you pay. soon that's something openai and anthropic will have to think about follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

17,145 просмотров • 1 месяц назад

Zelda II released for Famicom January 14, 1987 (yes, I’m a few days late!). I honestly love this game and thought it would be fun to cover 10 ways the NES release is different from Famicom! 1. The NES version rewrites the intro, removes the second “n” from Ganon’s and reference to “another” sleeping Zelda, and refers to palaces rather than sanctuaries. 2. NES introduces an ominous red game over screen, removes the second “” from Ganon and incorporates his taunting laugh, which is reused from Mike Tyson’s Punch Out!! (Released September 18, 1987, while the NES version released Dec. 1, 1988). 3. Link’s sprite has a visible mouth in the NES version absent in Famicom’s. 4. Additional Pillars are added to Zelda’s North Palace chamber for NES. 5. Roaming monsters are more distinct in the NES version. 6. Link’s NES raft sprite in faces right while Famicom’s is forward. 7. Famicom used fewer brick palates for Palaces, with NES including more colors. 8. The 4the boss, Carock at Maze Island, only faces forward for Famicom but can face left or right for NES. 9. The 5th Palace boss for Famicom pits players against a stronger version Helmethead reused from the 2nd Palace, while the NES introduces a new boss, Gooma. 10. The River devil appears as an oni (devil) rather than a spider like creature. This is not exhaustive and I’d love to cover more at a later date! Thank you for watching as I try something new!
1:11

Zelda II released for Famicom January 14, 1987 (yes, I’m a few days late!). I honestly love this game and thought it would be fun to cover 10 ways the NES release is different from Famicom! 1. The NES version rewrites the intro, removes the second “n” from Ganon’s and reference to “another” sleeping Zelda, and refers to palaces rather than sanctuaries. 2. NES introduces an ominous red game over screen, removes the second “” from Ganon and incorporates his taunting laugh, which is reused from Mike Tyson’s Punch Out!! (Released September 18, 1987, while the NES version released Dec. 1, 1988). 3. Link’s sprite has a visible mouth in the NES version absent in Famicom’s. 4. Additional Pillars are added to Zelda’s North Palace chamber for NES. 5. Roaming monsters are more distinct in the NES version. 6. Link’s NES raft sprite in faces right while Famicom’s is forward. 7. Famicom used fewer brick palates for Palaces, with NES including more colors. 8. The 4the boss, Carock at Maze Island, only faces forward for Famicom but can face left or right for NES. 9. The 5th Palace boss for Famicom pits players against a stronger version Helmethead reused from the 2nd Palace, while the NES introduces a new boss, Gooma. 10. The River devil appears as an oni (devil) rather than a spider like creature. This is not exhaustive and I’d love to cover more at a later date! Thank you for watching as I try something new!

Christina Rose

18,788 просмотров • 7 месяцев назад

🚨 $KATA FAM – THE STEAM DEMO GOES LIVE TOMORROW! 🔥 💰WIN $250 in $KATA Giveaway below! Tomorrow is the day. The Katana Inu Steam Demo will be live from April 11 to April 21. 🔥 Steam: This is your chance to jump in, play the game, and help us make some real noise around the demo launch. 😍 Once the demo phase is over, we already have a lot planned. We will share all details with you over the coming weeks, but one thing is already clear: 🎮 As a creator, you can expect the chance to win 2x PS5 for your community🎁 - More prizes and giveaways are also coming! Right now, we need your full support! 👉Wishlist the game on Steam & Play it 👉Play the demo as soon as it goes live 👉Leave your feedback on Steam, if you enjoy the game 👉Help us push Katana Inu to a bigger audience Every wishlist, every session, and every piece of feedback helps a lot! Let’s show what this community is made of. 💥 BONUS $KATA GIVEAWAY ALERT! We’re adding EVEN MORE fuel to the fire… 👉 5x $50 in $KATA 💰 Total: $250 in $KATA up for grabs! 🖼 1 Takeru Gensis NFT 🎯 How to participate? Join our Steam Demo between April 11 – April 21 🔥 1. Take a screenshot as proof that you play it 2. Wishlisted on Steam 3. Drop it in the comments below 👇 4. RT/QT this + Like ❤️ 5. Tag 3 person Influencer/Friend! ⚡ That’s it – you’re in! 🔥 More action = more hype 🔥 We choose random winners! Let’s make this event great and show everyone what $KATA FAM is made of 💥
0:49

🚨 $KATA FAM – THE STEAM DEMO GOES LIVE TOMORROW! 🔥 💰WIN $250 in $KATA Giveaway below! Tomorrow is the day. The Katana Inu Steam Demo will be live from April 11 to April 21. 🔥 Steam: This is your chance to jump in, play the game, and help us make some real noise around the demo launch. 😍 Once the demo phase is over, we already have a lot planned. We will share all details with you over the coming weeks, but one thing is already clear: 🎮 As a creator, you can expect the chance to win 2x PS5 for your community🎁 - More prizes and giveaways are also coming! Right now, we need your full support! 👉Wishlist the game on Steam & Play it 👉Play the demo as soon as it goes live 👉Leave your feedback on Steam, if you enjoy the game 👉Help us push Katana Inu to a bigger audience Every wishlist, every session, and every piece of feedback helps a lot! Let’s show what this community is made of. 💥 BONUS $KATA GIVEAWAY ALERT! We’re adding EVEN MORE fuel to the fire… 👉 5x $50 in $KATA 💰 Total: $250 in $KATA up for grabs! 🖼 1 Takeru Gensis NFT 🎯 How to participate? Join our Steam Demo between April 11 – April 21 🔥 1. Take a screenshot as proof that you play it 2. Wishlisted on Steam 3. Drop it in the comments below 👇 4. RT/QT this + Like ❤️ 5. Tag 3 person Influencer/Friend! ⚡ That’s it – you’re in! 🔥 More action = more hype 🔥 We choose random winners! Let’s make this event great and show everyone what $KATA FAM is made of 💥

Katana Inu

25,321 просмотров • 4 месяцев назад

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:
1:07

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:

SpAItial AI

176,524 просмотров • 8 месяцев назад

veo 3.1 fast vs seedance 2.0 vs grok imagine vs happyhorse 1.1 four video models pulled from the openrouter video leaderboard by request count this week (skipping the duplicate google/bytedance variants to get four distinct labs): #1 veo 3.1 fast (Google DeepMind) – 45k requests #3 seedance 2.0 (bytedance) – 22k requests #5 grok imagine video (SpaceXAI) – 9k requests #8 happyhorse 1.1 (Alibaba Group) – 4k requests so we tested them. 3 prompts, text-to-video, 16:9 / 720p / 8s, real-player likeness fed in as reference images where the model allowed it. all run via AI/ML API in the run-up to the 2026 world cup final – argentina vs spain – we built three broadcast moments from that tie. each one has to be mechanically correct, not just pretty: • stadium flyover – 80k-seat bowl, argentina vs spain, one continuous descending aerial spiral, tifo + flares, golden-hour / floodlight split • penalty – lamine yamal (spain #19) vs emiliano martínez (argentina keeper): run-up, single strike, full-stretch dive, ball in the net. real faces via reference • free kick – messi 25m out, five-man wall, curl up and over the wall into the top corner. the wall has to face the ball with arms pinned down, like a real wall the takeaway up front: the gap that decides this isn't quality – it's moderation. three of the four refuse to render real footballers' faces (grok was the only one that took every reference), so most of the test had to be reshot "faceless" – camera behind the player. the price spread on top of that is ~4x overall results: cost #1 grok – $1.56 #2 veo 3.1 fast – $3.12 #3 happyhorse – $4.38 #4 seedance 2.0 – $6.00 generation time #1 grok – 4m 16s #2 veo 3.1 fast – 4m 26s #3 happyhorse – 8m 16s #4 seedance 2.0 – 10m 38s avg bitrate (picture density) #1 grok – 12.0 mbps #2 veo 3.1 fast – 11.1 mbps #3 happyhorse – 7.4 mbps #4 seedance 2.0 – 5.3 mbps real faces allowed ✅ grok – took every reference ❌ happyhorse – yamal ok, messi blocked ❌ veo – blocked ❌ seedance – blocked observations: 1. moderation is the whole story. three of the four blocked at least one real face – veo and seedance refused every reference outright, happyhorse took yamal but rejected messi. only grok rendered all of them. everything else had to be shot from behind so no face shows 2. grok is the outlier: cheapest, densest picture, fastest, and the only one that renders real faces. it won on every axis that mattered here 3. seedance is the anti-grok – 4x the cost, 2.5x the time, half the bitrate, and no real faces. worst value in the set 4. none of them understand football out of the box follow thehype. for 24/7 ai news, analysis and breakdowns
0:23

veo 3.1 fast vs seedance 2.0 vs grok imagine vs happyhorse 1.1 four video models pulled from the openrouter video leaderboard by request count this week (skipping the duplicate google/bytedance variants to get four distinct labs): #1 veo 3.1 fast (Google DeepMind) – 45k requests #3 seedance 2.0 (bytedance) – 22k requests #5 grok imagine video (SpaceXAI) – 9k requests #8 happyhorse 1.1 (Alibaba Group) – 4k requests so we tested them. 3 prompts, text-to-video, 16:9 / 720p / 8s, real-player likeness fed in as reference images where the model allowed it. all run via AI/ML API in the run-up to the 2026 world cup final – argentina vs spain – we built three broadcast moments from that tie. each one has to be mechanically correct, not just pretty: • stadium flyover – 80k-seat bowl, argentina vs spain, one continuous descending aerial spiral, tifo + flares, golden-hour / floodlight split • penalty – lamine yamal (spain #19) vs emiliano martínez (argentina keeper): run-up, single strike, full-stretch dive, ball in the net. real faces via reference • free kick – messi 25m out, five-man wall, curl up and over the wall into the top corner. the wall has to face the ball with arms pinned down, like a real wall the takeaway up front: the gap that decides this isn't quality – it's moderation. three of the four refuse to render real footballers' faces (grok was the only one that took every reference), so most of the test had to be reshot "faceless" – camera behind the player. the price spread on top of that is ~4x overall results: cost #1 grok – $1.56 #2 veo 3.1 fast – $3.12 #3 happyhorse – $4.38 #4 seedance 2.0 – $6.00 generation time #1 grok – 4m 16s #2 veo 3.1 fast – 4m 26s #3 happyhorse – 8m 16s #4 seedance 2.0 – 10m 38s avg bitrate (picture density) #1 grok – 12.0 mbps #2 veo 3.1 fast – 11.1 mbps #3 happyhorse – 7.4 mbps #4 seedance 2.0 – 5.3 mbps real faces allowed ✅ grok – took every reference ❌ happyhorse – yamal ok, messi blocked ❌ veo – blocked ❌ seedance – blocked observations: 1. moderation is the whole story. three of the four blocked at least one real face – veo and seedance refused every reference outright, happyhorse took yamal but rejected messi. only grok rendered all of them. everything else had to be shot from behind so no face shows 2. grok is the outlier: cheapest, densest picture, fastest, and the only one that renders real faces. it won on every axis that mattered here 3. seedance is the anti-grok – 4x the cost, 2.5x the time, half the bitrate, and no real faces. worst value in the set 4. none of them understand football out of the box follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

15,453 просмотров • 1 месяц назад

Dr. Kelly Starrett has a simple philosophy. We should train to live, not live to train. He's helped athletes, teams, and everyday people build bodies that can handle the real demands of life. In this episode, Kelly (Kelly Starrett) breaks down how to think about pain, mobility, warmups, breathwork, recovery, and movement in a way that is practical, durable, and built for real life. We even get into youth sports—why so many kids burn out, why sleep and fueling are foundational for young athletes, why early specialization can backfire, and why play, broad movement skills, and better coaching may be the missing pieces in developing healthy, durable kids. If you want a more practical framework for lifelong performance, this is an episode you do not want to miss. Links to the episode on all platforms in the comments below. Timestamps: 0:00 - Introduction 2:17 - Pain isn't always injury 4:30 - Desensitizing persistent pain 9:45 - Foam rolling, reconsidered 12:55 - Evening soft tissue work 15:00 - The soreness myth 16:57 - Overhead pressing & neck pain 21:58 - Testing mobility at home 23:45 - The Cindy workout 24:42 - The real purpose of warming up 28:56 - Priming vs. protecting 31:50 - No time to warm up? 34:50 - Hip spin-up 36:17 - The sit-and-rise test 38:18 - Sit-and-rise & longevity 39:46 - Fit doesn't mean mobile 42:57 - Shoulder mobility for desk workers 47:16 - Daily shoulder maintenance 48:34 - Breath holds as a reset 51:43 - The spine as a breathing engine 54:28 - Training CO2 tolerance 57:04 - Fit vs. sport-ready 1:01:08 - Breathing under load 1:04:50 - The plank as a breathing drill 1:10:09 - Train for life, not live to train 1:13:29 - Training for non-athletes 1:19:30 - Leisure-time activity 1:23:26 - Hidden drivers of pain 1:26:31 - The couch stretch test 1:28:32 - Testing shoulder internal rotation 1:31:28 - Menopause & frozen shoulder 1:34:18 - Can running help recovery? 1:35:34 - Heat vs. cold for recovery 1:38:53 - Sauna for tendon repair 1:42:30 - A desk that invites motion 1:48:46 - Why floor sitting matters 1:51:40 - Mobility doesn't have to decline 1:57:30 - Movement snacks 2:04:28 - Never do nothing 2:09:27 - Inactivity by design 2:13:14 - The case for rucking 2:15:16 - The outdoor deficit 2:20:26 - A better nutrition framework 2:25:12 - The youth sports problem 2:27:19 - Sleep for young athletes 2:31:55 - Late practices & recovery 2:34:35 - Early sport specialization 2:37:21 - Why kids need free play 2:43:12 - Strength training for kids 2:45:45 - Martial arts & movement literacy 2:47:08 - Why kids quit sports 2:51:03 - What parents can control 2:52:39 - Fueling picky eaters 2:56:00 - Handstands & skipping 2:58:17 - Can jumping prevent ACL injuries? 3:00:38 - Ten minutes of daily play 3:02:15 - Subtract before adding
3:05:17

Dr. Kelly Starrett has a simple philosophy. We should train to live, not live to train. He's helped athletes, teams, and everyday people build bodies that can handle the real demands of life. In this episode, Kelly (Kelly Starrett) breaks down how to think about pain, mobility, warmups, breathwork, recovery, and movement in a way that is practical, durable, and built for real life. We even get into youth sports—why so many kids burn out, why sleep and fueling are foundational for young athletes, why early specialization can backfire, and why play, broad movement skills, and better coaching may be the missing pieces in developing healthy, durable kids. If you want a more practical framework for lifelong performance, this is an episode you do not want to miss. Links to the episode on all platforms in the comments below. Timestamps: 0:00 - Introduction 2:17 - Pain isn't always injury 4:30 - Desensitizing persistent pain 9:45 - Foam rolling, reconsidered 12:55 - Evening soft tissue work 15:00 - The soreness myth 16:57 - Overhead pressing & neck pain 21:58 - Testing mobility at home 23:45 - The Cindy workout 24:42 - The real purpose of warming up 28:56 - Priming vs. protecting 31:50 - No time to warm up? 34:50 - Hip spin-up 36:17 - The sit-and-rise test 38:18 - Sit-and-rise & longevity 39:46 - Fit doesn't mean mobile 42:57 - Shoulder mobility for desk workers 47:16 - Daily shoulder maintenance 48:34 - Breath holds as a reset 51:43 - The spine as a breathing engine 54:28 - Training CO2 tolerance 57:04 - Fit vs. sport-ready 1:01:08 - Breathing under load 1:04:50 - The plank as a breathing drill 1:10:09 - Train for life, not live to train 1:13:29 - Training for non-athletes 1:19:30 - Leisure-time activity 1:23:26 - Hidden drivers of pain 1:26:31 - The couch stretch test 1:28:32 - Testing shoulder internal rotation 1:31:28 - Menopause & frozen shoulder 1:34:18 - Can running help recovery? 1:35:34 - Heat vs. cold for recovery 1:38:53 - Sauna for tendon repair 1:42:30 - A desk that invites motion 1:48:46 - Why floor sitting matters 1:51:40 - Mobility doesn't have to decline 1:57:30 - Movement snacks 2:04:28 - Never do nothing 2:09:27 - Inactivity by design 2:13:14 - The case for rucking 2:15:16 - The outdoor deficit 2:20:26 - A better nutrition framework 2:25:12 - The youth sports problem 2:27:19 - Sleep for young athletes 2:31:55 - Late practices & recovery 2:34:35 - Early sport specialization 2:37:21 - Why kids need free play 2:43:12 - Strength training for kids 2:45:45 - Martial arts & movement literacy 2:47:08 - Why kids quit sports 2:51:03 - What parents can control 2:52:39 - Fueling picky eaters 2:56:00 - Handstands & skipping 2:58:17 - Can jumping prevent ACL injuries? 3:00:38 - Ten minutes of daily play 3:02:15 - Subtract before adding

Dr. Rhonda Patrick

78,097 просмотров • 4 месяцев назад

Something amazing is coming to Apache Kafka… Consumer Groups v2! If you’ve ever used consumer groups in production at any non-trivial scale, you probably know all the problems with it: - ⛔️ Group-wide synchronization barrier acts as a cap on scalability A single misbehaving consumer can disturb the whole group. Even if you have cooperative rebalancing and static membership enabled, you will still have rebalances happen. 🤷‍♂️ It’s a fact of life I've heard - death, taxes & consumer group rebalances. And the problem is that even with cooperative rebalancing (which helped a lot!), you’re bound on waiting for the slowest member of the group to complete the rebalance(s). 🐌 The problem is that no consumer can commit offsets while a rebalance is in progress. ❌ Another subtle thing is that with cooperative rebalancing, a rebalance will take longer than usual. Why? Because consumers are allowed to process partitions during rebalances. They will call the poll() method more infrequently -- they're busy processing records after all. Thus, the overall rebalance time will increase. This makes it pretty hard to scale to 1000s of members. - 🤯 Complexity There’s a reason you’re reading this! The current protocol is pretty complex and hard to understand. It's used for a bunch of stuff, including metadata propagation in Kafka Streams. This compexity results in more: - 🐛 bugs The harder to reason about and the more moving parts you have - the greater chance for bugs. There have been quite a few in the protocol. And due to the fact that a lot of the protocol’s logic lives on the clients, that results in: - 🐌 slow fixes Bugs require client-side fixes, which are slow to be adopted. If you run a Kafka ops team, you know how hard it is to get all of your clients' teams to upgrade! If you're using a cloud service, you need to wait for a new Kafka release to go out. Can't have the cloud provider handle it for you behind the scenes! - 🔍 hard to debug Debugging is harder because you need client logs. In the cloud, that's hard to do again. On-prem, it requires reading through a lot of logs and collecting a lot of files. - ⚙️ very extendable There’s a reusable embedded protocol within the rebalance protocol, where clients are free to attach raw bytes that only they can then parse themselves. It's challenging to build compatible software for this cross-client protocol, as well as near-impossible to inspect from the broker side. - 😢 inconsistent metadata Clients are responsible for triggering rebalances based on the metadata, but different clients can have different views of the metadata. - 😵‍💫 interoperability Different implementations of the clients (i.e. anything besides the Java client) may have bugs. The complex logic needs to be re-implemented quite a few times. This usually means more bugs and slower time to ship features in your favorite client. A combination nobody likes. ... So what should an open source community do? Move the logic to the broker! Then? Simplify it. The new protocol is very elegant - it streamlines all of the regular Kafka consumer logic inside a new heartbeat API. It has the broker decide what partition assignments the consumers should have, and totally omits the notion of a Group Leader client. Another major change is that the notion of a group-wide rebalance is removed now. The rebalance is more fine-grained now. 👌 When you think about it, a rebalance is simply a reassignment of some partitions from some consumers to others. 💡 Why does the whole group need to stop and know about this? It had to before because the logic was on the client. It doesn’t now. 🎂 The new protocol is fine-grained in its assignments. It maintains per-member epochs, as well as separate epochs for the general group membership and the global assignment. The goal is simple - get all of those epoch numbers to be the same. The order is the following: 1. the group-wide epoch is bumped. 2. the target assignment epoch is bumped. 3. individual consumers catch up to the epoch via the heartbeat request, individually. (fine-grained) In general, what you have is a simple state machine inside the Group Coordinator broker that’s running a constant reconciliation loop. 💥 Because every member converges to the target state independently, the coordinator is free to simplify that convergence member by member. 👍 It has the logic to resolve dependencies between members - the act of: 1. revoking one member’s partition. 2. confirming the success of that. 3. bumping that member's epoch before assigning that partition to another consumer. Here is an example visual of what happens when two members join a consumer group one by one:
1:37

Something amazing is coming to Apache Kafka… Consumer Groups v2! If you’ve ever used consumer groups in production at any non-trivial scale, you probably know all the problems with it: - ⛔️ Group-wide synchronization barrier acts as a cap on scalability A single misbehaving consumer can disturb the whole group. Even if you have cooperative rebalancing and static membership enabled, you will still have rebalances happen. 🤷‍♂️ It’s a fact of life I've heard - death, taxes & consumer group rebalances. And the problem is that even with cooperative rebalancing (which helped a lot!), you’re bound on waiting for the slowest member of the group to complete the rebalance(s). 🐌 The problem is that no consumer can commit offsets while a rebalance is in progress. ❌ Another subtle thing is that with cooperative rebalancing, a rebalance will take longer than usual. Why? Because consumers are allowed to process partitions during rebalances. They will call the poll() method more infrequently -- they're busy processing records after all. Thus, the overall rebalance time will increase. This makes it pretty hard to scale to 1000s of members. - 🤯 Complexity There’s a reason you’re reading this! The current protocol is pretty complex and hard to understand. It's used for a bunch of stuff, including metadata propagation in Kafka Streams. This compexity results in more: - 🐛 bugs The harder to reason about and the more moving parts you have - the greater chance for bugs. There have been quite a few in the protocol. And due to the fact that a lot of the protocol’s logic lives on the clients, that results in: - 🐌 slow fixes Bugs require client-side fixes, which are slow to be adopted. If you run a Kafka ops team, you know how hard it is to get all of your clients' teams to upgrade! If you're using a cloud service, you need to wait for a new Kafka release to go out. Can't have the cloud provider handle it for you behind the scenes! - 🔍 hard to debug Debugging is harder because you need client logs. In the cloud, that's hard to do again. On-prem, it requires reading through a lot of logs and collecting a lot of files. - ⚙️ very extendable There’s a reusable embedded protocol within the rebalance protocol, where clients are free to attach raw bytes that only they can then parse themselves. It's challenging to build compatible software for this cross-client protocol, as well as near-impossible to inspect from the broker side. - 😢 inconsistent metadata Clients are responsible for triggering rebalances based on the metadata, but different clients can have different views of the metadata. - 😵‍💫 interoperability Different implementations of the clients (i.e. anything besides the Java client) may have bugs. The complex logic needs to be re-implemented quite a few times. This usually means more bugs and slower time to ship features in your favorite client. A combination nobody likes. ... So what should an open source community do? Move the logic to the broker! Then? Simplify it. The new protocol is very elegant - it streamlines all of the regular Kafka consumer logic inside a new heartbeat API. It has the broker decide what partition assignments the consumers should have, and totally omits the notion of a Group Leader client. Another major change is that the notion of a group-wide rebalance is removed now. The rebalance is more fine-grained now. 👌 When you think about it, a rebalance is simply a reassignment of some partitions from some consumers to others. 💡 Why does the whole group need to stop and know about this? It had to before because the logic was on the client. It doesn’t now. 🎂 The new protocol is fine-grained in its assignments. It maintains per-member epochs, as well as separate epochs for the general group membership and the global assignment. The goal is simple - get all of those epoch numbers to be the same. The order is the following: 1. the group-wide epoch is bumped. 2. the target assignment epoch is bumped. 3. individual consumers catch up to the epoch via the heartbeat request, individually. (fine-grained) In general, what you have is a simple state machine inside the Group Coordinator broker that’s running a constant reconciliation loop. 💥 Because every member converges to the target state independently, the coordinator is free to simplify that convergence member by member. 👍 It has the logic to resolve dependencies between members - the act of: 1. revoking one member’s partition. 2. confirming the success of that. 3. bumping that member's epoch before assigning that partition to another consumer. Here is an example visual of what happens when two members join a consumer group one by one:

Stanislav Kozlovski

52,814 просмотров • 3 лет назад

✨ I spent the last 48 hours making GPT-4 read the entire Solana validator codebase and write documentation, so doesn't have to. Introducing — an AI-powered chatbot trained on nothing but code that can answer deep technical questions. How it works 👇 But first... A huge shoutout to , Zahid Khawaja, and Sean. Their hard work made prototyping this thing a breeze. Without further ado... Devs like to write code, not documentation. Tribal knowledge is lost when devs move on to other projects, leaving future devs to sort through mountains of code and figure out not just how it works, but why it works that way. This is all about to change. GPT-4's ability to write code is stunning. It seems to understand something fundamental about writing software that previous models just didn't. This comprehension of the principles that drive the design behind a complex system carries over into its ability to document existing codebases in a truly impressive way. With the enlarged context window(s), it's now feasible to feed GPT-4 entire files of code and ask it to write documentation about how the code works. Taking this as a starting point, the process looks something like this: 1. Download repo. 2. Depth-first traversal of repo contents, ignoring things like package-lock and binary files. 3. For each file, feed to GPT-4 and ask it to write documentation in markdown. 4. Save the output in a separate location as [outputRoot]/[inputFilepath][inputFilename].md 5. For each folder, we ask GPT-4 to write a summary of the folder, taking the newly generated documentation for all files in the folder and the summaries from each of its subfolders as context. Write this to the filesystem as markdown. Now we have a filesystem that matches the structure of the input repo, but all files in the tree are markdown documentation of the corresponding code file. From here, we: 1. Load markdown documents into LangChain. 2. Embed all documents via OpenAI embeddings. 3. Store embeddings in Pinecone. When a user sends a query: 1. Embed query. 2. Find k-nearest markdown files. 3. Feed to GPT-4 with a prompt asking to answer the query based on k-nearest markdown documents provided. The craziest part of all this? GPT-4 actually wrote ~30% of the code. The results are pretty good for 2 days of work. There is certainly room for improvement. Some items that are top of mind: 1. TolyGPT will occasionally hallucinate answers. It is especially bad with links to external sources, like GitHub. The base model seems to know a bit about Solana already, and sometimes this creeps in. Fine-tuning the prompt can solve some of this. 2. Context selection is difficult in a codebase this large. For example, sometimes it will pull in details about the Solana SDK when asked about transaction processing. The SDK files can seem relevant depending on the phrasing of the question. It may be worth breaking the documentation into subsystems to limit this. 3. Not all files fit into the 32k token window. As of now, there are 23 (out of ~1,100) files that cannot be documented in their entirety. Some of these files are very important to how Solana works. Final thoughts: 1. GPT-4 is super powerful, and we're going to see a ton of tools that supercharge the entire software development lifecycle. This is not 12 months away. For the people that can afford it, these tools are here now. And they're only getting better. Act accordingly. 2. The price of inference has to come down for this to go mainstream. I spent about $300 prototyping this project, and the final crawl cost about the same. The high cost of GPT-4 will push developers to other, cheaper alternatives with similar performance. This is coming very soon. If you have a large software project and you're interested in something like this for your codebase, fill out this form and we'll be in touch this week. Or just DM me :)
0:51

✨ I spent the last 48 hours making GPT-4 read the entire Solana validator codebase and write documentation, so doesn't have to. Introducing — an AI-powered chatbot trained on nothing but code that can answer deep technical questions. How it works 👇 But first... A huge shoutout to , Zahid Khawaja, and Sean. Their hard work made prototyping this thing a breeze. Without further ado... Devs like to write code, not documentation. Tribal knowledge is lost when devs move on to other projects, leaving future devs to sort through mountains of code and figure out not just how it works, but why it works that way. This is all about to change. GPT-4's ability to write code is stunning. It seems to understand something fundamental about writing software that previous models just didn't. This comprehension of the principles that drive the design behind a complex system carries over into its ability to document existing codebases in a truly impressive way. With the enlarged context window(s), it's now feasible to feed GPT-4 entire files of code and ask it to write documentation about how the code works. Taking this as a starting point, the process looks something like this: 1. Download repo. 2. Depth-first traversal of repo contents, ignoring things like package-lock and binary files. 3. For each file, feed to GPT-4 and ask it to write documentation in markdown. 4. Save the output in a separate location as [outputRoot]/[inputFilepath][inputFilename].md 5. For each folder, we ask GPT-4 to write a summary of the folder, taking the newly generated documentation for all files in the folder and the summaries from each of its subfolders as context. Write this to the filesystem as markdown. Now we have a filesystem that matches the structure of the input repo, but all files in the tree are markdown documentation of the corresponding code file. From here, we: 1. Load markdown documents into LangChain. 2. Embed all documents via OpenAI embeddings. 3. Store embeddings in Pinecone. When a user sends a query: 1. Embed query. 2. Find k-nearest markdown files. 3. Feed to GPT-4 with a prompt asking to answer the query based on k-nearest markdown documents provided. The craziest part of all this? GPT-4 actually wrote ~30% of the code. The results are pretty good for 2 days of work. There is certainly room for improvement. Some items that are top of mind: 1. TolyGPT will occasionally hallucinate answers. It is especially bad with links to external sources, like GitHub. The base model seems to know a bit about Solana already, and sometimes this creeps in. Fine-tuning the prompt can solve some of this. 2. Context selection is difficult in a codebase this large. For example, sometimes it will pull in details about the Solana SDK when asked about transaction processing. The SDK files can seem relevant depending on the phrasing of the question. It may be worth breaking the documentation into subsystems to limit this. 3. Not all files fit into the 32k token window. As of now, there are 23 (out of ~1,100) files that cannot be documented in their entirety. Some of these files are very important to how Solana works. Final thoughts: 1. GPT-4 is super powerful, and we're going to see a ton of tools that supercharge the entire software development lifecycle. This is not 12 months away. For the people that can afford it, these tools are here now. And they're only getting better. Act accordingly. 2. The price of inference has to come down for this to go mainstream. I spent about $300 prototyping this project, and the final crawl cost about the same. The high cost of GPT-4 will push developers to other, cheaper alternatives with similar performance. This is coming very soon. If you have a large software project and you're interested in something like this for your codebase, fill out this form and we'll be in touch this week. Or just DM me :)

Sam Hogan 🇺🇸

374,673 просмотров • 3 лет назад

My AI made Shopify pages are getting better and better everyday Here’s an example of a Shopify section I built with the reference page and the result on my store 👇 Guide: To make good AI landing pages, you need to use the same method as making good AI UGC or AI product images you have to take something that's already good as a reference for Claude/gemini to analyze and adapt for your product/brand for now you can't adapt full landing pages to your product because the Claude context gets bloated fast and you get poor output. Listicles are the only kind of page you can "one shot" with Claude. But Product pages are another story Analyze an existing page and adapting it to your product section by section is the way to go. The results are 10x better. here's an example (on the video): 1- I found this good product section from im8's product page. I screen-recorded the section on both desktop and mobile, going through the animations to capture the dynamism that a screenshot wouldn’t show. Then I asked Claude Web or Gemini to analyze the recording and produce a very detailed report. Full prompt is on my TG channel, it's quite long. 2- then ask Claude (inside your Shopify brand project folder): "I have a detailed UI/UX specification document for a product page section I want to adapt to my product. Recreate this exactly on Shopify as a section template and adapt it to [name of the product] using the brand guidelines" (paste the result prompt from step 1 ). 3- you will have your section ready after 3-4 minutes. you'll probably have to change a few things. spacing, small visual bugs, price not appearing correctly. it will take you 5 minutes maximum. 4- then you can ask Claude to make 4 different variations of the section using different designs and pick the best one using this prompt: "Create 4 design variations of this section. Keep the content and layout structure identical across all, only vary the visual treatment (color usage, typography hierarchy, spacing, component styling). I will choose the one I like the most." after that you have a pretty good section, and you can do the process again for all sections of the page. The less complex the section, the faster the process will be. note: I know the AI result is not perfect, but it's pretty impressive imo and it will only get better.
0:27

My AI made Shopify pages are getting better and better everyday Here’s an example of a Shopify section I built with the reference page and the result on my store 👇 Guide: To make good AI landing pages, you need to use the same method as making good AI UGC or AI product images you have to take something that's already good as a reference for Claude/gemini to analyze and adapt for your product/brand for now you can't adapt full landing pages to your product because the Claude context gets bloated fast and you get poor output. Listicles are the only kind of page you can "one shot" with Claude. But Product pages are another story Analyze an existing page and adapting it to your product section by section is the way to go. The results are 10x better. here's an example (on the video): 1- I found this good product section from im8's product page. I screen-recorded the section on both desktop and mobile, going through the animations to capture the dynamism that a screenshot wouldn’t show. Then I asked Claude Web or Gemini to analyze the recording and produce a very detailed report. Full prompt is on my TG channel, it's quite long. 2- then ask Claude (inside your Shopify brand project folder): "I have a detailed UI/UX specification document for a product page section I want to adapt to my product. Recreate this exactly on Shopify as a section template and adapt it to [name of the product] using the brand guidelines" (paste the result prompt from step 1 ). 3- you will have your section ready after 3-4 minutes. you'll probably have to change a few things. spacing, small visual bugs, price not appearing correctly. it will take you 5 minutes maximum. 4- then you can ask Claude to make 4 different variations of the section using different designs and pick the best one using this prompt: "Create 4 design variations of this section. Keep the content and layout structure identical across all, only vary the visual treatment (color usage, typography hierarchy, spacing, component styling). I will choose the one I like the most." after that you have a pretty good section, and you can do the process again for all sections of the page. The less complex the section, the faster the process will be. note: I know the AI result is not perfect, but it's pretty impressive imo and it will only get better.

Olivier

84,679 просмотров • 5 месяцев назад

Ripple - XRP - America - Clarity Act WHAT THIS MEANS FOR AMERICA America has been stuck with an old, slow, confusing money system for decades—one that loses people’s hard-earned dollars, hides fees, lets middlemen skim off the top, and keeps the average person in the dark. But what’s happening now changes everything: 1. Money will finally move the way life moves - fast. No more waiting days for paychecks to clear, transfers to settle, or banks to “process” something simple. Money will move instantly, 24/7, with no hidden nonsense. 2. Fees drop. Transparency rises. No more backroom games. The current system hides fees, delays payments, and makes mistakes that nobody can trace. This new system works like a public calculator where errors can’t hide. You’ll see exactly where your money goes. 3. New American jobs, new industries, new small-business growth. Any time a new “highway” gets built—whether it’s roads, electricity, or the internet - millions of new jobs come with it. This new financial “highway” is no different. America will build it, run it, and benefit from it. 4. A stronger dollar that people all over the world trust again. Instead of printing money into worthlessness, America uses real value, real transparency, and real accountability to support the dollar. A strong dollar means: • higher purchasing power • lower inflation • more respect on the world stage 5. Less power for hidden middlemen. More power for Americans. For years, the financial system rewarded insiders and punished regular people. This shift puts the power back where it belongs—in the hands of the public, not the bureaucrats, not the big banks, not the middlemen. 6. America becomes the world’s financial “light tower” again. Instead of reacting to world events, America leads. Other nations turn to us—not because we force them, but because our system is fair, fast, and trustworthy. 7. Our money becomes safer, clearer, and more honest. No tricks. No gimmicks. No fine print. Just honest accounting and immediate settlements. In Plain English: This is America fixing what was broken - with honesty, accountability, technology, and common sense. It means: • Better jobs • Better money • Better opportunities • A better future for families, workers, veterans, retirees, and small business owners It means we stop repeating old mistakes… and start building a system worthy of the people who live in this country. This isn’t about crypto. This isn’t about politics. This is about America upgrading its financial engine so everyone can finally run on equal ground. If our U.S. Treasury and Ripple both held 17% of XRP at $250, shareholders of both entities would have an asset valued at $4.2 Trillion. Starting from Ripple’s most recent $40B post-money valuation, if XRP truly ran to $250 and Ripple still held 17B XRP under a Treasury-blessed XRPL/RLUSD/XRP global monetary regime, reasonable mechanical valuation frameworks spit out multi-trillion-dollar Ripple equity numbers - roughly $1 to $7T+, with the low end already bigger than Visa and Mastercard combined, and the high end bumping into “this changes our world forever” territory. The Art of The Deal Cometh. Ripple Treasury Department Donald J. Trump Treasury Secretary Scott Bessent Brad Garlinghouse Stuart Alderoty CFTC #XRPArmy
1:30

Ripple - XRP - America - Clarity Act WHAT THIS MEANS FOR AMERICA America has been stuck with an old, slow, confusing money system for decades—one that loses people’s hard-earned dollars, hides fees, lets middlemen skim off the top, and keeps the average person in the dark. But what’s happening now changes everything: 1. Money will finally move the way life moves - fast. No more waiting days for paychecks to clear, transfers to settle, or banks to “process” something simple. Money will move instantly, 24/7, with no hidden nonsense. 2. Fees drop. Transparency rises. No more backroom games. The current system hides fees, delays payments, and makes mistakes that nobody can trace. This new system works like a public calculator where errors can’t hide. You’ll see exactly where your money goes. 3. New American jobs, new industries, new small-business growth. Any time a new “highway” gets built—whether it’s roads, electricity, or the internet - millions of new jobs come with it. This new financial “highway” is no different. America will build it, run it, and benefit from it. 4. A stronger dollar that people all over the world trust again. Instead of printing money into worthlessness, America uses real value, real transparency, and real accountability to support the dollar. A strong dollar means: • higher purchasing power • lower inflation • more respect on the world stage 5. Less power for hidden middlemen. More power for Americans. For years, the financial system rewarded insiders and punished regular people. This shift puts the power back where it belongs—in the hands of the public, not the bureaucrats, not the big banks, not the middlemen. 6. America becomes the world’s financial “light tower” again. Instead of reacting to world events, America leads. Other nations turn to us—not because we force them, but because our system is fair, fast, and trustworthy. 7. Our money becomes safer, clearer, and more honest. No tricks. No gimmicks. No fine print. Just honest accounting and immediate settlements. In Plain English: This is America fixing what was broken - with honesty, accountability, technology, and common sense. It means: • Better jobs • Better money • Better opportunities • A better future for families, workers, veterans, retirees, and small business owners It means we stop repeating old mistakes… and start building a system worthy of the people who live in this country. This isn’t about crypto. This isn’t about politics. This is about America upgrading its financial engine so everyone can finally run on equal ground. If our U.S. Treasury and Ripple both held 17% of XRP at $250, shareholders of both entities would have an asset valued at $4.2 Trillion. Starting from Ripple’s most recent $40B post-money valuation, if XRP truly ran to $250 and Ripple still held 17B XRP under a Treasury-blessed XRPL/RLUSD/XRP global monetary regime, reasonable mechanical valuation frameworks spit out multi-trillion-dollar Ripple equity numbers - roughly $1 to $7T+, with the low end already bigger than Visa and Mastercard combined, and the high end bumping into “this changes our world forever” territory. The Art of The Deal Cometh. Ripple Treasury Department Donald J. Trump Treasury Secretary Scott Bessent Brad Garlinghouse Stuart Alderoty CFTC #XRPArmy

Rob Cunningham

139,518 просмотров • 9 месяцев назад

Do Vision-Language Models represent space, and how? Spatial terms like "left" or "right" may not be enough to match images with spatial descriptions, as we often overlook the different frames of reference (FoR) used by speakers and listeners. See Figure 1 for examples! Introducing the COnsistent Multilingual Frame Of Reference Test (COMFORT), an evaluation protocol to assess the spatial reasoning capabilities of VLMs. COMFORT includes systematically designed datasets and metrics that evaluate model performance, and their deeper linguistic competence, specifically the spatial knowledge encoded in their internal representations. Find out more in the video teaser! Almost all VLMs prefer the egocentric relative FoR with reflected transform, similar to English. Yet, we reveal significant shortcomings of VLMs: notably, the models (1) exhibit poor robustness and consistency, (2) lack the flexibility to accommodate multiple FoRs, and (3) fail to adhere to language-specific or culture-specific conventions in cross-lingual tests, as English tends to dominate other languages. A shortened version will appear in Pluralistic Alignment Workshop Pluralistic Alignment Workshop #NeurIPS2024. It seems that the ArXiv moderators put it on hold and are eager to give it a thorough read first🤣! So here is the Paper/Code/Data: This collaboration turns out to be amazing, jointly led by Brian Zheyuan Zhang, @Hu_FY_ Jayjun Lee, with so many contributions and insights from Freda Shi, Parisa Kordjamshidi Michigan SLED Lab. With a growing effort to align vision-language models with human cognitive intuitions, we call for more attention to the ambiguous nature and cross-cultural diversity of spatial reasoning!
0:30

Do Vision-Language Models represent space, and how? Spatial terms like "left" or "right" may not be enough to match images with spatial descriptions, as we often overlook the different frames of reference (FoR) used by speakers and listeners. See Figure 1 for examples! Introducing the COnsistent Multilingual Frame Of Reference Test (COMFORT), an evaluation protocol to assess the spatial reasoning capabilities of VLMs. COMFORT includes systematically designed datasets and metrics that evaluate model performance, and their deeper linguistic competence, specifically the spatial knowledge encoded in their internal representations. Find out more in the video teaser! Almost all VLMs prefer the egocentric relative FoR with reflected transform, similar to English. Yet, we reveal significant shortcomings of VLMs: notably, the models (1) exhibit poor robustness and consistency, (2) lack the flexibility to accommodate multiple FoRs, and (3) fail to adhere to language-specific or culture-specific conventions in cross-lingual tests, as English tends to dominate other languages. A shortened version will appear in Pluralistic Alignment Workshop Pluralistic Alignment Workshop #NeurIPS2024. It seems that the ArXiv moderators put it on hold and are eager to give it a thorough read first🤣! So here is the Paper/Code/Data: This collaboration turns out to be amazing, jointly led by Brian Zheyuan Zhang, @Hu_FY_ Jayjun Lee, with so many contributions and insights from Freda Shi, Parisa Kordjamshidi Michigan SLED Lab. With a growing effort to align vision-language models with human cognitive intuitions, we call for more attention to the ambiguous nature and cross-cultural diversity of spatial reasoning!

Martin Ziqiao Ma

35,581 просмотров • 1 год назад

Another day, another “ Ceasefire” this one supposedly included Lebanon. According to Iran here are the terms: Iran's Mehr News Agency has released all 14 clauses of the MoU with the U.S.: 1: Permanent and immediate cessation of war on all fronts, including Lebanon. 2: The US commitment to non-interference in Iran's internal affairs and respect for the sovereignty of the Islamic Republic of Iran. 3: Complete lifting of the naval blockade within 30 days. 4: The US commitment to withdraw its forces from around Iran. 5: Reopening of the Strait of Hormuz within 30 days under Iranian arrangements. 6: Suspension of sanctions on the sale of oil, petrochemical products, and derivatives, and full access of Iran to its financial resources. 7: The necessity for the US and its allies to present reconstruction plans for Iran amounting to at least $300 billion. 8: 60 days of negotiations to reach a final agreement based on nuclear issues and the complete lifting of primary, secondary, US sanctions, and UN Security Council and IAEA Board of Governors resolutions. 9: Reiteration of Iran's commitment under the NPT treaty not to produce nuclear weapons. 10: During the negotiation period, the US has committed not to add forces in the region and not to impose new sanctions. 11: Release of $24 billion of Iran's blocked funds during the 60-day final negotiation period. Half of this amount must be made available to Iran before the start of negotiations. 12: Formation of a supervisory mechanism to implement the agreement. 13: The final agreement will be approved by a UN Security Council resolution. 14: Final negotiations will not begin before the release of half of Iran's blocked funds, suspension of Iran's oil sanctions, and lifting of the naval blockade, and the final agreement will only cover the fate of enriched materials and enrichment, lifting of sanctions, and Iran's economic reconstruction plan. Discussions about Iran's missile program and support for resistance groups are definitively removed from the agenda.
0:31

Another day, another “ Ceasefire” this one supposedly included Lebanon. According to Iran here are the terms: Iran's Mehr News Agency has released all 14 clauses of the MoU with the U.S.: 1: Permanent and immediate cessation of war on all fronts, including Lebanon. 2: The US commitment to non-interference in Iran's internal affairs and respect for the sovereignty of the Islamic Republic of Iran. 3: Complete lifting of the naval blockade within 30 days. 4: The US commitment to withdraw its forces from around Iran. 5: Reopening of the Strait of Hormuz within 30 days under Iranian arrangements. 6: Suspension of sanctions on the sale of oil, petrochemical products, and derivatives, and full access of Iran to its financial resources. 7: The necessity for the US and its allies to present reconstruction plans for Iran amounting to at least $300 billion. 8: 60 days of negotiations to reach a final agreement based on nuclear issues and the complete lifting of primary, secondary, US sanctions, and UN Security Council and IAEA Board of Governors resolutions. 9: Reiteration of Iran's commitment under the NPT treaty not to produce nuclear weapons. 10: During the negotiation period, the US has committed not to add forces in the region and not to impose new sanctions. 11: Release of $24 billion of Iran's blocked funds during the 60-day final negotiation period. Half of this amount must be made available to Iran before the start of negotiations. 12: Formation of a supervisory mechanism to implement the agreement. 13: The final agreement will be approved by a UN Security Council resolution. 14: Final negotiations will not begin before the release of half of Iran's blocked funds, suspension of Iran's oil sanctions, and lifting of the naval blockade, and the final agreement will only cover the fate of enriched materials and enrichment, lifting of sanctions, and Iran's economic reconstruction plan. Discussions about Iran's missile program and support for resistance groups are definitively removed from the agenda.

Syrian Girl

92,557 просмотров • 2 месяцев назад

🔥 Funtico Sports Has Arrived | The Hottest Release in Web3 Gaming And how to better make a splash than with not 1, not 2, not 5, but 20 RTBs (Right-to-Buy Tickets) to FIFA World Cup 2026! 😎 Yeap, largest ever FIFA RTBs campaign in the history of Web3 Gaming! 🚀 Why is this bullish: 💎 $TICO is the key: $TICO is now the entry point to all exclusive events and experiences across the Funtico Sports ecosystem. ✨ Next-level rewards: from tickets to the world’s biggest events to ultra-rare Right-To-Buy tickets (RTBs) that open the door to once-in-a-lifetime experiences. 🎮 Unlocking game dev potential: Sports-themed game developers can now connect directly through our Publisher-as-a-Service SDK, unlocking new ways to publish, distribute, and scale inside Funtico. 👀 All-access experience: Thanks to exclusive partnerships, Funtico Sports brings you closer than ever to the communities, clubs, and brands you love. 🔥 Beyond the game: Our brand-new Golazo League tournament is more than just competition for $TICO, it’s your shot at once-in-a-lifetime experiences reserved for the few. Golazo League launches soon, starting strong with a custom tournament and huge rewards: ⚽️ 20 RTBs to the FIFA World Cup 2026 ⚽️ 123,456 $TICO ⚽️ And more juicy rewards! Compete, climb, and win rewards that redefine what’s possible in Web3 gaming. 🚀 💸 Like + Repost + tag 2 friends in the comment section of this announcement to enter a $50 raffle, with 5 lucky winners.
0:56

🔥 Funtico Sports Has Arrived | The Hottest Release in Web3 Gaming And how to better make a splash than with not 1, not 2, not 5, but 20 RTBs (Right-to-Buy Tickets) to FIFA World Cup 2026! 😎 Yeap, largest ever FIFA RTBs campaign in the history of Web3 Gaming! 🚀 Why is this bullish: 💎 $TICO is the key: $TICO is now the entry point to all exclusive events and experiences across the Funtico Sports ecosystem. ✨ Next-level rewards: from tickets to the world’s biggest events to ultra-rare Right-To-Buy tickets (RTBs) that open the door to once-in-a-lifetime experiences. 🎮 Unlocking game dev potential: Sports-themed game developers can now connect directly through our Publisher-as-a-Service SDK, unlocking new ways to publish, distribute, and scale inside Funtico. 👀 All-access experience: Thanks to exclusive partnerships, Funtico Sports brings you closer than ever to the communities, clubs, and brands you love. 🔥 Beyond the game: Our brand-new Golazo League tournament is more than just competition for $TICO, it’s your shot at once-in-a-lifetime experiences reserved for the few. Golazo League launches soon, starting strong with a custom tournament and huge rewards: ⚽️ 20 RTBs to the FIFA World Cup 2026 ⚽️ 123,456 $TICO ⚽️ And more juicy rewards! Compete, climb, and win rewards that redefine what’s possible in Web3 gaming. 🚀 💸 Like + Repost + tag 2 friends in the comment section of this announcement to enter a $50 raffle, with 5 lucky winners.

Funtico 🎮🔺

16,056 просмотров • 11 месяцев назад

today i shipped the biggest gridform update yet, the latest major updates ↓ 1. ai that actually designs • design copilot: edit with chat • magic design: one prompt → complete poster • multi-agent studio • brand brain • reference image → editable layouts 2. motion & new media • keyframe motion studio • mp4, gif & animated svg export • generative shader backgrounds • slides & presentation mode 3. layouts & composition • 194 new layouts across 10 historic design movements • 566 layouts total • auto-layout constraints • snap-grid builder • layout breeding, blending & mutation 4. craft & quality • design doctor • advanced type systems • palette studio • copy-fit • smart resize 5. scale & shipping • campaign resizing • csv bulk generation • mockup studio • components & design tokens • fully offline 6. plus: magic start, smart layout match, instant branding from a logo, magic wand edits, image cutout & recolor, motion director, time machine, live share links, accessible exports, and more. 100+ early believers from around the world have helped shape this product. people i've never met spending their time testing gridform, breaking things, reporting bugs, sharing references, and telling me what's missing. most of today's update exists because of them. building products alone is hard. building with people who genuinely care about what you're making changes everything. 100% in the browser. still no sign-up. thank you for believing this early ❤️ dm for access.
2:07

today i shipped the biggest gridform update yet, the latest major updates ↓ 1. ai that actually designs • design copilot: edit with chat • magic design: one prompt → complete poster • multi-agent studio • brand brain • reference image → editable layouts 2. motion & new media • keyframe motion studio • mp4, gif & animated svg export • generative shader backgrounds • slides & presentation mode 3. layouts & composition • 194 new layouts across 10 historic design movements • 566 layouts total • auto-layout constraints • snap-grid builder • layout breeding, blending & mutation 4. craft & quality • design doctor • advanced type systems • palette studio • copy-fit • smart resize 5. scale & shipping • campaign resizing • csv bulk generation • mockup studio • components & design tokens • fully offline 6. plus: magic start, smart layout match, instant branding from a logo, magic wand edits, image cutout & recolor, motion director, time machine, live share links, accessible exports, and more. 100+ early believers from around the world have helped shape this product. people i've never met spending their time testing gridform, breaking things, reporting bugs, sharing references, and telling me what's missing. most of today's update exists because of them. building products alone is hard. building with people who genuinely care about what you're making changes everything. 100% in the browser. still no sign-up. thank you for believing this early ❤️ dm for access.

Deep | Dragoon

24,273 просмотров • 2 месяцев назад

The beauty & technology packed in the upgraded Model 3 is greatly under-appreciated, just look at all the new things that are in this car and then tell me you don’t want it. 👇 • Same prices as old Model 3, under $40K • Up to ~2.4% higher range on Long Range trim (341), same range on RWD (272) • 50% of the parts in the car are new • 4.3% more cargo capacity • Long Range is 4 lbs lighter than before, RWD is 29 lbs heavier than before • 0.1" lower ground clearance vs old 3 • 30% decrease in wind and ambient noise, 25% improvement in impact noise and 20% improvement in road noise • Redesigned interior w/ new door cards • More premium interior materials. The fabric is softer to the touch and sewn with a more refined process to present a better overall texture • Two new colors: Ultra Red ($2K) & Stealth Gray (no extra cost) • No more stalks. New steering wheel contains the turns signals, light controls, horn, new camera button, wiper controls and mic control • New dash design with textured/woven material • Multicolor ambient LED interior lighting extending from dash to rear seat doors • Updated center console w/ real metal handles, giving a more premium feel. • Acoustic glass on rear windows and back window (was only on front windows before). "360º acoustic glass" • More sound insulation for a quieter ride • Uptick in hood to let wind go over more quietly • Upgraded suspension for a more premium ride. New springs & dampers. New geometry on front suspension. New bushings. New way they mount the sub frame to the chassis • Stiffer body, better handling • More premium sounding door "thunk" • Passengers are more protected from door impacts due to new latch at the bottom of the door • Two motors close the trunk now vs one before, resulting in a quieter automatic close • Tires have more cushioning for improved ride • Center touchscreen now brighter, has smaller bezels, higher contrast & is more responsive • More comfortable rear seats • Redesigned lower rear bumper • All seats are now perforated • No fog lights anymore • Front seats are now ventilated, in addition to heated • 8" touchscreen for rear passengers in the back to control climate & enjoy entertainment. You can connect two headsets at the same time. • Better drag coefficient of 0.219 Cd • Upgraded 2.0 ventilation system. You can now separately turn off the passenger side air • Slimmer and sleeker headlight and taillight design • Single wing-shaped taillight design, meaning better reliability and low chance for leakage/part misalignment • New 17 speaker sound system (up from 14 before). It now includes 2 subwoofers and 2 amplifiers. More punchy • 65W USB-C charger in center console so you can charge a laptop • Improved bluetooth • Upgraded microphones. Now one on each passenger side. New mics make phone calls clearer and "smooth" • 5G connectivity. 50% improved cellular service. 2X greater WiFi range (dual-band) • Improved connectivity to phone so car will recognize your phone from farther away • Two new wheel designs that better optimize battery life • New Tesla lettering replaces rear Tesla logo badge • Car is 8% more efficient thanks to better aerodynamics • Car is 1" longer overall (Original vid from Andy Slye, cooked by me)
1:04

The beauty & technology packed in the upgraded Model 3 is greatly under-appreciated, just look at all the new things that are in this car and then tell me you don’t want it. 👇 • Same prices as old Model 3, under $40K • Up to ~2.4% higher range on Long Range trim (341), same range on RWD (272) • 50% of the parts in the car are new • 4.3% more cargo capacity • Long Range is 4 lbs lighter than before, RWD is 29 lbs heavier than before • 0.1" lower ground clearance vs old 3 • 30% decrease in wind and ambient noise, 25% improvement in impact noise and 20% improvement in road noise • Redesigned interior w/ new door cards • More premium interior materials. The fabric is softer to the touch and sewn with a more refined process to present a better overall texture • Two new colors: Ultra Red ($2K) & Stealth Gray (no extra cost) • No more stalks. New steering wheel contains the turns signals, light controls, horn, new camera button, wiper controls and mic control • New dash design with textured/woven material • Multicolor ambient LED interior lighting extending from dash to rear seat doors • Updated center console w/ real metal handles, giving a more premium feel. • Acoustic glass on rear windows and back window (was only on front windows before). "360º acoustic glass" • More sound insulation for a quieter ride • Uptick in hood to let wind go over more quietly • Upgraded suspension for a more premium ride. New springs & dampers. New geometry on front suspension. New bushings. New way they mount the sub frame to the chassis • Stiffer body, better handling • More premium sounding door "thunk" • Passengers are more protected from door impacts due to new latch at the bottom of the door • Two motors close the trunk now vs one before, resulting in a quieter automatic close • Tires have more cushioning for improved ride • Center touchscreen now brighter, has smaller bezels, higher contrast & is more responsive • More comfortable rear seats • Redesigned lower rear bumper • All seats are now perforated • No fog lights anymore • Front seats are now ventilated, in addition to heated • 8" touchscreen for rear passengers in the back to control climate & enjoy entertainment. You can connect two headsets at the same time. • Better drag coefficient of 0.219 Cd • Upgraded 2.0 ventilation system. You can now separately turn off the passenger side air • Slimmer and sleeker headlight and taillight design • Single wing-shaped taillight design, meaning better reliability and low chance for leakage/part misalignment • New 17 speaker sound system (up from 14 before). It now includes 2 subwoofers and 2 amplifiers. More punchy • 65W USB-C charger in center console so you can charge a laptop • Improved bluetooth • Upgraded microphones. Now one on each passenger side. New mics make phone calls clearer and "smooth" • 5G connectivity. 50% improved cellular service. 2X greater WiFi range (dual-band) • Improved connectivity to phone so car will recognize your phone from farther away • Two new wheel designs that better optimize battery life • New Tesla lettering replaces rear Tesla logo badge • Car is 8% more efficient thanks to better aerodynamics • Car is 1" longer overall (Original vid from Andy Slye, cooked by me)

Teslaconomics

73,057 просмотров • 2 лет назад

The Future of Commerce Is Being Rewritten Right Now with Interlink and LinkersMap 🚀 Digital commerce is changing rapidly, and the connection between crypto payments, real-world businesses, and global consumers is becoming more important than ever. 🌐 InterLink Labs 👤 + 🌐 is taking a major step forward by expanding crypto payment utility across 50+ global brands, helping bring digital assets closer to everyday use. This is an important move towards practical adoption, where crypto is not only held or traded, but also used in real economic activity. 💳✨ From shopping 🛍️ and entertainment 🎮 to travel ✈️, technology 💻, hospitality 🏨, education 🎓, services 🧰, and global retail 🌍, digital payments are becoming part of the modern customer experience. The future of commerce is not just online. It is global, connected, mobile, and increasingly powered by digital assets. 🔥 💜 LinkersMap: Building Real-World Utility for the InterLink Ecosystem LinkersMap is emerging as a powerful marketplace and geo-commerce platform designed to connect businesses, entrepreneurs, communities, and customers in one trusted digital environment. It is built to support verified InterLink Stores, product listings, payment points, and real-world services, giving users a simple way to discover where digital commerce is active. For businesses, LinkersMap is more than just a listing platform. It is a gateway to greater visibility, stronger customer access, and future-ready participation in the growing digital economy. 🏪🌍 🏪 What LinkersMap Offers to Businesses Businesses can use LinkersMap to create a stronger digital presence and connect with customers beyond traditional local limits. Through the platform, businesses can: ✅ Register and display their store on the map ✅ Showcase products and services to a wider audience ✅ Improve brand visibility within the InterLink community ✅ Reach both local and global customers ✅ Build trust through verified store listings ✅ Position themselves for future crypto payment adoption ✅ Connect directly with users looking for real-world businesses ✅ Participate in a growing digital commerce network Whether it is a restaurant, retail shop, hotel, service provider, education centre, wellness brand, tech business, or Web3 project, LinkersMap gives businesses a practical way to become more discoverable. 📍✨ 🌍 Why This Matters for Real-World Adoption One of the biggest challenges in crypto has always been real-world utility. 💵 People need places to spend. 👪 Businesses need customers. 🏪 Communities need trusted platforms. 💳 Ecosystems need practical use cases. This is where LinkersMap plays an important role. By connecting physical businesses, digital listings, products, and payment visibility, LinkersMap helps bridge the gap between crypto users and real-world commerce. 💳🏪 As the InterLink Network grows, more businesses can join, more users can discover services, and more value can move through the ecosystem. This creates a stronger cycle of adoption: 🔁 More businesses join 🔁 More users discover them 🔁 More transactions become possible 🔁 More utility is created 🔁 The ecosystem becomes stronger 💳 Strengthening Utility for $ITL The expansion of InterLink payment utility helps support the long-term usefulness of $ITL within real-world commerce. As more stores, brands, and services become connected to the ecosystem, $ITL gains more practical relevance. This is important because strong digital assets are supported not only by community interest, but also by actual use. LinkersMap helps make this utility more visible by giving users a place to discover businesses, products, and services connected to the InterLink Network. 🌐💜 ✨ Key Benefits for the Community The growth of LinkersMap creates value for different parts of the ecosystem. For Businesses 🏪 ✅ Increased online and map-based visibility ✅ Access to a growing Web3-focused community ✅ Opportunity to attract new customers ✅ Stronger digital presence ✅ Future-ready payment positioning ✅ Better exposure for products and services For Customers 🛒 ✅ Easier discovery of verified businesses ✅ Access to InterLink-connected stores and services ✅ More real-world use cases for digital assets ✅ Simple map-based search experience ✅ Greater confidence through store verification For the InterLink Ecosystem 🌐 ✅ Stronger real-world utility for $ITL ✅ More payment points and business listings ✅ Better connection between online and offline commerce ✅ Community-driven growth ✅ Increased merchant adoption ✅ A clearer path towards mainstream use 🚀 A New Chapter for Digital Commerce The next generation of commerce is not only about payments. It is about creating a complete ecosystem where businesses can be discovered, customers can connect, communities can grow, and digital assets can be used in practical ways. LinkersMap supports this vision by making real-world business participation easier, more visible, and more accessible. It gives entrepreneurs, merchants, and service providers a platform to be part of the digital economy while helping users find businesses that are ready for the future. 🌎✨ 💼 Register Your Business Today If you are a business owner, entrepreneur, merchant, or service provider, now is the time to join the growing LinkersMap ecosystem. 📍 Add your store 🛍️ Showcase your products 🌍 Reach more customers 💳 Prepare for crypto-powered commerce 💜 Connect with the InterLink community 🌐 Register here: 💜 One Ecosystem. Unlimited Opportunities. 🌎 Global Reach. Real Utility. Future Growth. 🚀 LinkersMap is helping connect businesses, communities, and digital commerce for the future. LinkersMap Dr Altcoin ✝️ Arif Ahmed Core Ambassador | Interlink Labs InterLink Labs 👤 + 🌐 KV InterLink Foundation ITLX Wallet #Interlink #ITLG #ITL #Linkersmap #business #ecommerce #globalgrowth #onlinestore
0:24

The Future of Commerce Is Being Rewritten Right Now with Interlink and LinkersMap 🚀 Digital commerce is changing rapidly, and the connection between crypto payments, real-world businesses, and global consumers is becoming more important than ever. 🌐 InterLink Labs 👤 + 🌐 is taking a major step forward by expanding crypto payment utility across 50+ global brands, helping bring digital assets closer to everyday use. This is an important move towards practical adoption, where crypto is not only held or traded, but also used in real economic activity. 💳✨ From shopping 🛍️ and entertainment 🎮 to travel ✈️, technology 💻, hospitality 🏨, education 🎓, services 🧰, and global retail 🌍, digital payments are becoming part of the modern customer experience. The future of commerce is not just online. It is global, connected, mobile, and increasingly powered by digital assets. 🔥 💜 LinkersMap: Building Real-World Utility for the InterLink Ecosystem LinkersMap is emerging as a powerful marketplace and geo-commerce platform designed to connect businesses, entrepreneurs, communities, and customers in one trusted digital environment. It is built to support verified InterLink Stores, product listings, payment points, and real-world services, giving users a simple way to discover where digital commerce is active. For businesses, LinkersMap is more than just a listing platform. It is a gateway to greater visibility, stronger customer access, and future-ready participation in the growing digital economy. 🏪🌍 🏪 What LinkersMap Offers to Businesses Businesses can use LinkersMap to create a stronger digital presence and connect with customers beyond traditional local limits. Through the platform, businesses can: ✅ Register and display their store on the map ✅ Showcase products and services to a wider audience ✅ Improve brand visibility within the InterLink community ✅ Reach both local and global customers ✅ Build trust through verified store listings ✅ Position themselves for future crypto payment adoption ✅ Connect directly with users looking for real-world businesses ✅ Participate in a growing digital commerce network Whether it is a restaurant, retail shop, hotel, service provider, education centre, wellness brand, tech business, or Web3 project, LinkersMap gives businesses a practical way to become more discoverable. 📍✨ 🌍 Why This Matters for Real-World Adoption One of the biggest challenges in crypto has always been real-world utility. 💵 People need places to spend. 👪 Businesses need customers. 🏪 Communities need trusted platforms. 💳 Ecosystems need practical use cases. This is where LinkersMap plays an important role. By connecting physical businesses, digital listings, products, and payment visibility, LinkersMap helps bridge the gap between crypto users and real-world commerce. 💳🏪 As the InterLink Network grows, more businesses can join, more users can discover services, and more value can move through the ecosystem. This creates a stronger cycle of adoption: 🔁 More businesses join 🔁 More users discover them 🔁 More transactions become possible 🔁 More utility is created 🔁 The ecosystem becomes stronger 💳 Strengthening Utility for $ITL The expansion of InterLink payment utility helps support the long-term usefulness of $ITL within real-world commerce. As more stores, brands, and services become connected to the ecosystem, $ITL gains more practical relevance. This is important because strong digital assets are supported not only by community interest, but also by actual use. LinkersMap helps make this utility more visible by giving users a place to discover businesses, products, and services connected to the InterLink Network. 🌐💜 ✨ Key Benefits for the Community The growth of LinkersMap creates value for different parts of the ecosystem. For Businesses 🏪 ✅ Increased online and map-based visibility ✅ Access to a growing Web3-focused community ✅ Opportunity to attract new customers ✅ Stronger digital presence ✅ Future-ready payment positioning ✅ Better exposure for products and services For Customers 🛒 ✅ Easier discovery of verified businesses ✅ Access to InterLink-connected stores and services ✅ More real-world use cases for digital assets ✅ Simple map-based search experience ✅ Greater confidence through store verification For the InterLink Ecosystem 🌐 ✅ Stronger real-world utility for $ITL ✅ More payment points and business listings ✅ Better connection between online and offline commerce ✅ Community-driven growth ✅ Increased merchant adoption ✅ A clearer path towards mainstream use 🚀 A New Chapter for Digital Commerce The next generation of commerce is not only about payments. It is about creating a complete ecosystem where businesses can be discovered, customers can connect, communities can grow, and digital assets can be used in practical ways. LinkersMap supports this vision by making real-world business participation easier, more visible, and more accessible. It gives entrepreneurs, merchants, and service providers a platform to be part of the digital economy while helping users find businesses that are ready for the future. 🌎✨ 💼 Register Your Business Today If you are a business owner, entrepreneur, merchant, or service provider, now is the time to join the growing LinkersMap ecosystem. 📍 Add your store 🛍️ Showcase your products 🌍 Reach more customers 💳 Prepare for crypto-powered commerce 💜 Connect with the InterLink community 🌐 Register here: 💜 One Ecosystem. Unlimited Opportunities. 🌎 Global Reach. Real Utility. Future Growth. 🚀 LinkersMap is helping connect businesses, communities, and digital commerce for the future. LinkersMap Dr Altcoin ✝️ Arif Ahmed Core Ambassador | Interlink Labs InterLink Labs 👤 + 🌐 KV InterLink Foundation ITLX Wallet #Interlink #ITLG #ITL #Linkersmap #business #ecommerce #globalgrowth #onlinestore

Tekkaus® | InterLink • MOD • T2 Community Builder

10,912 просмотров • 2 месяцев назад