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👀Brainstem atlas animation 👀 Using high-quality NIH Human Connectome Project data, we previously built a probabilistic map of 23 major brainstem fiber bundles—overcoming distortion issues that plagued past studies. It's publicly available for all: 🧠🔬

Lab of Neuro Imaging

5,810 subscribers

15,545 次观看 • 1 年前 •via X (Twitter)

健康养生科学技术教育

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4 条评论

Laelle E. Novotny 🧠 的头像

Laelle E. Novotny 🧠1 年前

@NIH Yay open science!!!

ksminnovation 的头像

ksminnovation1 年前

AI is transforming healthcare! A KSM-led study shows AI can detect Celiac disease 4 years earlier @TalPatalon @MedPredict

Dr. Hemalatha Ramachandran 的头像

Dr. Hemalatha Ramachandran1 年前

@NIH This is fantastic work, @USCLONI. You’ve taken brainstem imaging to the next level—addressing a notoriously tricky area with precision. Open access to this high-quality atlas is a major win for both research and clinical application. #Neuroimaging #Connectome

Lab of Neuro Imaging 的头像

Lab of Neuro Imaging1 年前

@NIH Oh, thank you! It's our pleasure!

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A high-quality haptic control for robots as a weekend project? All for under $600. [📍 Save Github & arXiv for later] A team built DOGlove, an open-source haptic glove for robot teleoperation that you can assemble yourself for under $600. It is built for real control, not demos. • Tracks 21 degrees of freedom with a custom joint design • Provides cable-driven force feedback plus fingertip haptics • Can be used to collect data for imitation learning Affordable haptics could make teleoperation more reliable and improve the quality of data we use to train physical AI. Project link: Credit: DOGlove team, shared by Han Zhang —- Weekly robotics and AI insights. Subscribe free:

A high-quality haptic control for robots as a weekend project? All for under $600. [📍 Save Github & arXiv for later] A team built DOGlove, an open-source haptic glove for robot teleoperation that you can assemble yourself for under $600. It is built for real control, not demos. • Tracks 21 degrees of freedom with a custom joint design • Provides cable-driven force feedback plus fingertip haptics • Can be used to collect data for imitation learning Affordable haptics could make teleoperation more reliable and improve the quality of data we use to train physical AI. Project link: Credit: DOGlove team, shared by Han Zhang —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

18,290 次观看 • 7 个月前

3.5 years of collecting traffic data from 500 MILLION miles driven with several billion data points have now gone into one product: The Atlas Navi Map. In fact, it's not just a normal heatmap with navigation, traffic and incident data, it's an API that goes far beyond traditional GPS-based maps, for end users and developers alike. How does it work exactly? 🤖 Highly-granular data purpose-built for developers of: Large scale routing & navigation systems Autonomous driving AI model training Smart city infrastructure planning 📹 30+ million data points updating in real-time Parking availability, traffic congestion, police presence Traffic flows, road hazards, infrastructure issues Data you simply can't get from GPS alone ⚡️ Hyperlocal intelligence Busiest intersections by time/day Traffic chokepoints and incidents Most dangerous intersections with accident data Try it out here yourself: Several navigation companies have requested using our data API, more updates on this soon. #NAVI #MAP #DePIN

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Excited to share our new work on building a multimodal atlas of human skin in health and inflammatory disease — a project I’m especially proud of, bringing together AI, high-throughput genomics, and clinical science to accelerate discovery. Over the past decade, single-cell genomics has transformed how we map cells in human tissues. But a major challenge remains: can we systematically decode how cells organize into functional niches in situ — including those invisible to standard histopathology? To address this, we integrated large-scale scRNA-seq, spatial transcriptomics, histopathology, and AI-driven modeling frameworks to build an in situ atlas of human skin across health and disease. Led by Lloyd Steele, an MD/PhD student working between Haniffa Lab and my lab at Wellcome Sanger Institute and Cambridge University . Another amazing collaboration with Muzz Haniffa, the mastermind behind the work as part of Human Cell Atlas. A key part of this study is that we didn’t build everything from scratch — we leveraged and combined AI methods that actually work! and showed how they can be used together to extract biological insight at scale. We used: • scArches to build and map into a reference scRNA-seq atlas of human skin: • NicheCompass to identify and characterize spatial niches: • MINT-Flow to extract microenvironment-induced cell states and gene programs: Together, these enabled an end-to-end workflow from atlas construction to spatial mapping, niche discovery, and cell state decoding. At scale, we integrated ~5 million cells and 100+ spatial sections, enabling a systematic view of tissue organization. Using this framework, we identified 26 niches in skin, including known histopathologic structures as well as hidden disease-associated niches not visible on H&E. Among the most striking findings were a resident memory T cell-rich sebaceous gland niche and a plasma cell-rich sweat gland niche, suggesting that appendageal structures act as active immunological microenvironments and may contribute to inflammatory memory and disease persistence. Importantly, this atlas is not just descriptive — it is usable. It can support mapping of new datasets, resolve finer cell types and niches, extract microenvironment-driven programs, and enable predictive analyses at scale. More broadly, this work shows what becomes possible when AI, spatial genomics, and atlas-scale data are integrated end-to-end: not just mapping tissues, but systematically decoding them. This was a massive collaboration, and I’m very grateful to the amazing scientists April Foster, Kenny Roberts, and Chloe Admane. Lloyd is an amazing scientist, and I’m especially excited for the community to see more of his work soon — stay tuned. The data and pre-trained models will be released soon. Preprint:

Excited to share our new work on building a multimodal atlas of human skin in health and inflammatory disease — a project I’m especially proud of, bringing together AI, high-throughput genomics, and clinical science to accelerate discovery. Over the past decade, single-cell genomics has transformed how we map cells in human tissues. But a major challenge remains: can we systematically decode how cells organize into functional niches in situ — including those invisible to standard histopathology? To address this, we integrated large-scale scRNA-seq, spatial transcriptomics, histopathology, and AI-driven modeling frameworks to build an in situ atlas of human skin across health and disease. Led by Lloyd Steele, an MD/PhD student working between Haniffa Lab and my lab at Wellcome Sanger Institute and Cambridge University . Another amazing collaboration with Muzz Haniffa, the mastermind behind the work as part of Human Cell Atlas. A key part of this study is that we didn’t build everything from scratch — we leveraged and combined AI methods that actually work! and showed how they can be used together to extract biological insight at scale. We used: • scArches to build and map into a reference scRNA-seq atlas of human skin: • NicheCompass to identify and characterize spatial niches: • MINT-Flow to extract microenvironment-induced cell states and gene programs: Together, these enabled an end-to-end workflow from atlas construction to spatial mapping, niche discovery, and cell state decoding. At scale, we integrated ~5 million cells and 100+ spatial sections, enabling a systematic view of tissue organization. Using this framework, we identified 26 niches in skin, including known histopathologic structures as well as hidden disease-associated niches not visible on H&E. Among the most striking findings were a resident memory T cell-rich sebaceous gland niche and a plasma cell-rich sweat gland niche, suggesting that appendageal structures act as active immunological microenvironments and may contribute to inflammatory memory and disease persistence. Importantly, this atlas is not just descriptive — it is usable. It can support mapping of new datasets, resolve finer cell types and niches, extract microenvironment-driven programs, and enable predictive analyses at scale. More broadly, this work shows what becomes possible when AI, spatial genomics, and atlas-scale data are integrated end-to-end: not just mapping tissues, but systematically decoding them. This was a massive collaboration, and I’m very grateful to the amazing scientists April Foster, Kenny Roberts, and Chloe Admane. Lloyd is an amazing scientist, and I’m especially excited for the community to see more of his work soon — stay tuned. The data and pre-trained models will be released soon. Preprint:

Mo Lotfollahi

11,813 次观看 • 4 个月前

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After 8 months of building in stealth and testing our infrastructure on 10000+ hours of real-world data and hundreds of unique environments, we're bringing FPV Labs into the open today. FPV Labs started with the following bet - if human data proves to be the underlying factor that determines scaling laws in general-purpose robotics, it will trigger the largest economic transformation in human history, and the underlying infrastructure that captures that data will determine how fast we get there. We will achieve this by building the full-stack infrastructure for capturing, processing, transferring, and evaluating human experience into spatial, temporal, and semantic knowledge for machines. Despite all the research novelty behind ChatGPT, its success can be attributed to one foundational fact - the scaling law of transformers. We believe the same dynamics have made their way into robotics. Recent studies showed task completion rates jumping from 30% to 70% when human demonstration data scaled from 1,000 to 20,000 hours, a log-linear trend that mirrors exactly what we saw in language and vision. Seeing these emergent signs of scaling law curves in robotics, we believe we are entering the era of general-purpose robotics policies, which makes the next few years the most exciting time in the history of this field. But the library of physical interactions required to train general-purpose robot policies does not exist yet. Over the last 8 months, we've seen dozens of companies emerge in this space. We were really happy to see new companies pushing this space forward, but we also saw the same pattern repeat: every egocentric data company was making some tradeoffs between quality, scale, and diversity. We have built FPV labs on the core principle that high-quality data is orders of magnitude more valuable than sheer volume. Case in point, self-driving cars collect thousands of hours of data per day, but only a small fraction of that data is actually useful for training better models. Several studies, like RT-2, have shown that as little as 1% of data improves as much as 25% on task success. The quality and diversity of data matter a lot more than scale, so there is clearly a power law curve in the downstream impact of data. We've spent months obsessing over data quality by building our stack, discarding it, rebuilding it, and iterating until we found a formula that doesn't compromise downstream quality at scale. We believe the downstream impact here is far more profound than most people realize. Workers globally are paid around $60 trillion per year in aggregate, and a lion's share of that compensation goes to physical labor - tasks that require navigating real spaces, manipulating real objects, and negotiating the infinite variability of the physical world. Human-to-robot transfer will be one of the most important infrastructures that will shape our society in the near future, and if it works, the economic impact will dwarf every technology transition that came before it in an exponential manner and lead to the creation of goods and services we can’t imagine today. Our mission is to lay the groundwork for us to transition into this future - the future of abundance. We are deeply grateful to our earliest believers, Paras Chopra and Lossfunk, who played a critical role in shaping our thinking.

Abhishek Anand

82,126 次观看 • 4 个月前

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

Jim Fan

165,246 次观看 • 1 年前

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”

David Fields

13,639 次观看 • 2 年前

These videos are making the rounds on social media as if it's program testimony from a member of the US Navy on UAP. It's from US Navy Servicewoman ゴーカレー The data she is sharing is a review of data from Skywatcher and data that is commonly available to UFOlogists online from the CIA's Project Stargate data release. Also we have heard three different names from different organizations for the same phenomenon... We need to come up with a standard lexicon for UAP researchers instead of inventing new terms/categories of UAP. This topic isn't new and many have previously discovered what we are currently observing. They already have names and inventing new ones just confuses people. Why are we creating new terms for Phenomena that have already been classified and discovered? These are Plasmoids. Dr Massimo Teodorani and his Intelligent Plasmoid Hypothesis is the most probable answer for the UAP/NHI conundrum. We don't need to create further language to further confuse people with. Guarantee we will see researchers in the future presenting "Look at this 8 headed tetra UAP" "oh that's a polytetragon" "well at NASA we call them 8 headed tetras. Each organization will have a different name for the same entity. Ultimately they are all different species of Plasmoids" These are Plasmoids under intelligent control and they are an NHI. #ufotwitter

These videos are making the rounds on social media as if it's program testimony from a member of the US Navy on UAP. It's from US Navy Servicewoman ゴーカレー The data she is sharing is a review of data from Skywatcher and data that is commonly available to UFOlogists online from the CIA's Project Stargate data release. Also we have heard three different names from different organizations for the same phenomenon... We need to come up with a standard lexicon for UAP researchers instead of inventing new terms/categories of UAP. This topic isn't new and many have previously discovered what we are currently observing. They already have names and inventing new ones just confuses people. Why are we creating new terms for Phenomena that have already been classified and discovered? These are Plasmoids. Dr Massimo Teodorani and his Intelligent Plasmoid Hypothesis is the most probable answer for the UAP/NHI conundrum. We don't need to create further language to further confuse people with. Guarantee we will see researchers in the future presenting "Look at this 8 headed tetra UAP" "oh that's a polytetragon" "well at NASA we call them 8 headed tetras. Each organization will have a different name for the same entity. Ultimately they are all different species of Plasmoids" These are Plasmoids under intelligent control and they are an NHI. #ufotwitter

raefos:AetherNet

12,860 次观看 • 1 年前

It's here! All power assets are now live on my GB Renewables Map ⚡ That's right, it's not just wind farms any more. Now you can see live and historic data for gas power plants, nuclear, grid batteries, biomass, pumped hydro and even a bit of solar. Wind farms are still the default for now, though you can enable as many or as few of the other fuel types and your selection will be remembered when you come back to the website. It's already live so go play for yourself here: There are numerous other updates as well: ⛔ Click the plug button to see a curtailment view, now including turn-up and a better visual representation of turn-down and turn-up actions ℹ️ Tooltips include loads more detail about fuel type and balancing actions ☢️ Each fuel type can be toggled using the map buttons 🧠 Map state is remembered when you reload or revisit the website ✨ Lots of new and under construction power assets are now on the map ↕️ Summary of balancing actions at the top of the map 🚦 Grid boundaries and constraints shown using a traffic light system And I'm only getting started! This update was the original goal of creating the map a few years ago. Now it's here I can shift focus to all the other ideas I have for it… Oh, and there's a new feedback button at the top. Please use it to let me know of any issues you find (there will be plenty) or suggestions to help improve this resource for everyone else. I'd also like to thank you for all the support and encouragement as I build this free resource in my free time (yup, this isn't my job). Honestly, it's been an incredible motivator and the discussions over the years have taught me a huge amount that has only made the map better for everyone. Until the next update!

It's here! All power assets are now live on my GB Renewables Map ⚡ That's right, it's not just wind farms any more. Now you can see live and historic data for gas power plants, nuclear, grid batteries, biomass, pumped hydro and even a bit of solar. Wind farms are still the default for now, though you can enable as many or as few of the other fuel types and your selection will be remembered when you come back to the website. It's already live so go play for yourself here: There are numerous other updates as well: ⛔ Click the plug button to see a curtailment view, now including turn-up and a better visual representation of turn-down and turn-up actions ℹ️ Tooltips include loads more detail about fuel type and balancing actions ☢️ Each fuel type can be toggled using the map buttons 🧠 Map state is remembered when you reload or revisit the website ✨ Lots of new and under construction power assets are now on the map ↕️ Summary of balancing actions at the top of the map 🚦 Grid boundaries and constraints shown using a traffic light system And I'm only getting started! This update was the original goal of creating the map a few years ago. Now it's here I can shift focus to all the other ideas I have for it… Oh, and there's a new feedback button at the top. Please use it to let me know of any issues you find (there will be plenty) or suggestions to help improve this resource for everyone else. I'd also like to thank you for all the support and encouragement as I build this free resource in my free time (yup, this isn't my job). Honestly, it's been an incredible motivator and the discussions over the years have taught me a huge amount that has only made the map better for everyone. Until the next update!

Robin Hawkes

37,403 次观看 • 6 个月前

BTW - This is messed up but did you know all the major shampoo brands at the big box stores are being sued for using ingredients that make your hair fall out. I wish I was kidding. Watch this video. This gentleman explains the racket. Oh, and behind the scenes these brands are all ultimately owned by hedge funds like Blackrock & Vanguard that hate you. Better yet, they even divert profits to organizations like Planned Parenthood that clearly don't align with your values. Or you could simply choose to buy some of your products from an American company that shares your values, employs Americans, and uses all-natural, high-quality ingredients. Our project is to migrate just 10% of MAGA's household budget for certain items we all use already, using money all already spend, and together deprive companies that hate us of $30 billion dollars a year. That's it. And if that's something you'd like to consider being a part of then inquire here - and if not, don't. This ain't rocket science. 😁

BTW - This is messed up but did you know all the major shampoo brands at the big box stores are being sued for using ingredients that make your hair fall out. I wish I was kidding. Watch this video. This gentleman explains the racket. Oh, and behind the scenes these brands are all ultimately owned by hedge funds like Blackrock & Vanguard that hate you. Better yet, they even divert profits to organizations like Planned Parenthood that clearly don't align with your values. Or you could simply choose to buy some of your products from an American company that shares your values, employs Americans, and uses all-natural, high-quality ingredients. Our project is to migrate just 10% of MAGA's household budget for certain items we all use already, using money all already spend, and together deprive companies that hate us of $30 billion dollars a year. That's it. And if that's something you'd like to consider being a part of then inquire here - and if not, don't. This ain't rocket science. 😁

AwakenedOutlaw⚒️

1,120,435 次观看 • 3 年前

🚨 NEW: What if your inbox was just...handled? That's why we built Cora: the AI chief-of-staff for your email that only costs $15 / month—not $150k. Today, Cora is out of private beta and available publicly! 🚀 It does three things: - Screens your emails so you only see the 20% that matter - Drafts responses in your voice - Turns 80% of your inbox into a brief you can read in 30 seconds Cora learns you inside and out, so you never miss anything important. You can also chat or email with it like a human—it will remember everything you ask for. Cora has been wildly successful in its beta period, and it manages email for over 2,500 users—today it's your turn. Cora is available as a standalone product or included as part of an Every 🧱 subscription along with all of the writing we publish, Spiral, Sparkle, and everything else we make. Give Cora your inbox and take back your life →

🚨 NEW: What if your inbox was just...handled? That's why we built Cora: the AI chief-of-staff for your email that only costs $15 / month—not $150k. Today, Cora is out of private beta and available publicly! 🚀 It does three things: - Screens your emails so you only see the 20% that matter - Drafts responses in your voice - Turns 80% of your inbox into a brief you can read in 30 seconds Cora learns you inside and out, so you never miss anything important. You can also chat or email with it like a human—it will remember everything you ask for. Cora has been wildly successful in its beta period, and it manages email for over 2,500 users—today it's your turn. Cora is available as a standalone product or included as part of an Every 🧱 subscription along with all of the writing we publish, Spiral, Sparkle, and everything else we make. Give Cora your inbox and take back your life →

Dan Shipper 📧

223,348 次观看 • 1 年前

🚨 Georgia Power is forcing a family off their farm with eminent domain for a Data Center “I'm fighting for survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This data center project affects over 330 private properties. Georgia Power says it will negotiate purchases and easements and use eminent domain Georgia Power claims its to strengthen the grid for the growing energy demand in Georgia (due to many new data centers) The lines are widely linked to Project Sail This isn’t a small operation. Project Sail is a $17 billion hyperscale data center campus by Prologis, Atlas that includes 9 massive buildings totaling up to 4.34 million square feet on 829 acres. It will demand hundreds of megawatts of continuous power equivalent to what a small city uses We cannon allow data centers to take priority over farmers

🚨 Georgia Power is forcing a family off their farm with eminent domain for a Data Center “I'm fighting for survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This data center project affects over 330 private properties. Georgia Power says it will negotiate purchases and easements and use eminent domain Georgia Power claims its to strengthen the grid for the growing energy demand in Georgia (due to many new data centers) The lines are widely linked to Project Sail This isn’t a small operation. Project Sail is a $17 billion hyperscale data center campus by Prologis, Atlas that includes 9 massive buildings totaling up to 4.34 million square feet on 829 acres. It will demand hundreds of megawatts of continuous power equivalent to what a small city uses We cannon allow data centers to take priority over farmers

Wall Street Apes

435,456 次观看 • 3 个月前

Georgia Power is trying to push a family off their farm via eminent domain for a data center: “I'm fighting for the survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center.” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table, wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This project impacts more than 330 private properties. Georgia Power says it will negotiate purchases and easements and, if needed, use eminent domain. They claim it's to strengthen the grid for Georgia's rising energy demand from new data centers. The lines are widely linked to Project Sail — a $17 billion hyperscale campus by Prologis, Atlas with 9 massive buildings totaling up to 4.34 million sq ft on 829 acres, demanding hundreds of megawatts, roughly a small city's power. We cannot allow data centers to be prioritized over farmers.

Georgia Power is trying to push a family off their farm via eminent domain for a data center: “I'm fighting for the survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center.” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table, wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This project impacts more than 330 private properties. Georgia Power says it will negotiate purchases and easements and, if needed, use eminent domain. They claim it's to strengthen the grid for Georgia's rising energy demand from new data centers. The lines are widely linked to Project Sail — a $17 billion hyperscale campus by Prologis, Atlas with 9 massive buildings totaling up to 4.34 million sq ft on 829 acres, demanding hundreds of megawatts, roughly a small city's power. We cannot allow data centers to be prioritized over farmers.

redpillbot

60,418 次观看 • 3 个月前

$I'm THRILLED to share my latest VFX and animation project!!!! I seriously can't thank @/OGVFX more for helping me grow so much and get me through so many issues and frustrations. Not just all those god-level houdini techniques, he was also like a mentor of my life. AAAAAaa~~~ Christain 💙💙💙 Also shoutout to Sofia (ins: pickledsofa) for the hugeeeeeee animation help. As well as Raymond(in: dray3d) for additional feedback and final approval! 💖 Most challenges came from managing the data with such scene scale and planning effects for all universal shots (of the PC we have... X_x) I had to break almost everything into smaller parts, from fracture, RBD, pyro...to render. Lots of grinding, wellbeing and my soul over the past few months. The last 10% always takes 90% of the time, but it's finally done, and I’m super happy with the result! —— I still couldn't believe it (´; v;`) Anyway, Hope you enjoy the breakdown and have a nice weekend ｡:.ﾟヽ(*´v`)ﾉﾟ.:｡ #houdini #sidefx #autodeskmaya #creature #animation #VFX$

I'm THRILLED to share my latest VFX and animation project!!!! I seriously can't thank @/OGVFX more for helping me grow so much and get me through so many issues and frustrations. Not just all those god-level houdini techniques, he was also like a mentor of my life. AAAAAaa~~~ Christain 💙💙💙 Also shoutout to Sofia (ins: pickledsofa) for the hugeeeeeee animation help. As well as Raymond(in: dray3d) for additional feedback and final approval! 💖 Most challenges came from managing the data with such scene scale and planning effects for all universal shots (of the PC we have... X_x) I had to break almost everything into smaller parts, from fracture, RBD, pyro...to render. Lots of grinding, wellbeing and my soul over the past few months. The last 10% always takes 90% of the time, but it's finally done, and I’m super happy with the result! —— I still couldn't believe it (´; v;`) Anyway, Hope you enjoy the breakdown and have a nice weekend ｡:.ﾟヽ(*´v`)ﾉﾟ.:｡ #houdini #sidefx #autodeskmaya #creature #animation #VFX

It's Po !!

25,602 次观看 • 1 年前

Because people genuinely still don't understand how long it takes to develop major features and entire new game modes: Gavin Winter (Senior Systems Designer OW) on Emongg's stream mentioned that there's been a whole separate team dedicated to making the new Stadium mode for "a lot of the time" Gavin has been at Blizzard. For context, Gavin has been at Blizzard for nearly 4 years. He also mentions that gameplay engineers have been working on Stadium "for the past few years". Stadium having been worked on for 3 years lines up with the timeline of Hero Missions being publicly announced to be cancelled in May 16th 2023, with strong rumours that indicate Hero Missions were internally scrapped at least a year before that. Meaning that if developers were reassigned from Hero Missions to Stadium in early 2022; it has now been 3 years almost exactly to the day - lining up with the timeline Gavin alluded to in his comments. People also need to remember it's been nearly a year and a half since the Diablo collaboration when we first got to see some of the early testing of perks/skill trees in gameplay publicly. We just didn't know what project we were publicly testing for until now. It makes sense to reassign developers and convert the work done on PvE into something more in line with the true direction of OW which is PvP game play. Stadium is the result of that, taking the best parts from the old Hero Missions project and transforming it into something else that works better for the current game. All of this to say; development doesn't happen in 2 months. To the dismay of the far too many people that somehow think it does.

Because people genuinely still don't understand how long it takes to develop major features and entire new game modes: Gavin Winter (Senior Systems Designer OW) on Emongg's stream mentioned that there's been a whole separate team dedicated to making the new Stadium mode for "a lot of the time" Gavin has been at Blizzard. For context, Gavin has been at Blizzard for nearly 4 years. He also mentions that gameplay engineers have been working on Stadium "for the past few years". Stadium having been worked on for 3 years lines up with the timeline of Hero Missions being publicly announced to be cancelled in May 16th 2023, with strong rumours that indicate Hero Missions were internally scrapped at least a year before that. Meaning that if developers were reassigned from Hero Missions to Stadium in early 2022; it has now been 3 years almost exactly to the day - lining up with the timeline Gavin alluded to in his comments. People also need to remember it's been nearly a year and a half since the Diablo collaboration when we first got to see some of the early testing of perks/skill trees in gameplay publicly. We just didn't know what project we were publicly testing for until now. It makes sense to reassign developers and convert the work done on PvE into something more in line with the true direction of OW which is PvP game play. Stadium is the result of that, taking the best parts from the old Hero Missions project and transforming it into something else that works better for the current game. All of this to say; development doesn't happen in 2 months. To the dismay of the far too many people that somehow think it does.

Kev Walker

367,294 次观看 • 1 年前

✨We are excited to open-source Tencent HY-Motion 1.0, a billion-parameter text-to-motion model built on the Diffusion Transformer (DiT) architecture and flow matching. Tencent HY-Motion 1.0 empowers developers and individual creators alike by transforming natural language into high-fidelity, fluid, and diverse 3D character animations, delivering exceptional instruction-following capabilities across a broad range of categories. The generated 3D animation assets can be seamlessly integrated into typical 3D animation pipelines.🎮🎥 Highlights: 🔹Billion-Scale DiT: Successfully scaled flow-matching DiT to 1B+ parameters, setting a new ceiling for instruction-following capability and generated motion quality. 🔹Full-Stage Training Strategy: The industry’s first motion generation model featuring a complete Pre-training → SFT → RL loop to optimize physical plausibility and semantic accuracy. 🔹Comprehensive Category Coverage: Features 200+ motion categories across 6 major classes—the most comprehensive in the industry, curated via a meticulous data pipeline. 🌐Project Page: 🔗Github: 🤗Hugging Face: 📄Technical report:

✨We are excited to open-source Tencent HY-Motion 1.0, a billion-parameter text-to-motion model built on the Diffusion Transformer (DiT) architecture and flow matching. Tencent HY-Motion 1.0 empowers developers and individual creators alike by transforming natural language into high-fidelity, fluid, and diverse 3D character animations, delivering exceptional instruction-following capabilities across a broad range of categories. The generated 3D animation assets can be seamlessly integrated into typical 3D animation pipelines.🎮🎥 Highlights: 🔹Billion-Scale DiT: Successfully scaled flow-matching DiT to 1B+ parameters, setting a new ceiling for instruction-following capability and generated motion quality. 🔹Full-Stage Training Strategy: The industry’s first motion generation model featuring a complete Pre-training → SFT → RL loop to optimize physical plausibility and semantic accuracy. 🔹Comprehensive Category Coverage: Features 200+ motion categories across 6 major classes—the most comprehensive in the industry, curated via a meticulous data pipeline. 🌐Project Page: 🔗Github: 🤗Hugging Face: 📄Technical report:

Tencent Hy

328,874 次观看 • 7 个月前

The Ukrainian mistake that put an entire strategy into question Until the end of 2024, Ukrainian defenses using drones were very effective, slowing down not only the Russian advance but also inflicting significant casualties. During this period, the Russians heavily invested in drones, from factories to the development of fiber-optic drones, which were still produced in small quantities. By the end of 2024, a second Chinese restriction on the sale of components further complicated these transactions for both sides. Both industries were already manufacturing various components in small quantities, but still heavily dependent on Chinese imports. While the Russians expanded their intermediary networks to bypass restrictions and maintain Chinese imports, the Ukrainian Ministry of Defense decided to invest in local companies to produce fiber-optic cables. Essentially, all other components continued to be imported from China via intermediaries, but strangely, several Ukrainian companies started manufacturing low-quality cables and received government funding. The result was an unprecedented superiority of Russian drones on the battlefield, while Ukrainian fiber-optic drones were produced in much smaller numbers, with limited range and low-quality fibers that broke easily. This mistake of nationalizing such a sensitive component was initiated by the Ministry and not due to Chinese restrictions, since all other components continued to be imported through intermediaries. In my view, it was a bold strategy that ultimately failed, compromising the Ukrainian advantage until that moment. You either win the war or make money. It's hard to do both. It will be a major challenge for Ukraine to regain its front-line capacity as it previously was, facing a Russian production of 500,000 fiber-optic drones annually. This significant error weakened Ukrainian defense, which was already operating with low manpower and high desertion rates, but was still adjusting and maintaining the front through the hiring of mercenaries for many months. Given the scarcity of equipment on the front line, there is doubt whether lowering recruitment age will have the desired effect to sustain the front for a long period. It would also be necessary to resolve the issue with fiber-optic drones and for Ukraine to receive another batch of equipment from 2023, which I believe is unlikely. The situation involves multiple aspects of deterioration that have persisted for a long time, continuing to impact the AFU. While financial aid is being maintained, the absence of American support with weaponry is being felt as a crucial issue.

The Ukrainian mistake that put an entire strategy into question Until the end of 2024, Ukrainian defenses using drones were very effective, slowing down not only the Russian advance but also inflicting significant casualties. During this period, the Russians heavily invested in drones, from factories to the development of fiber-optic drones, which were still produced in small quantities. By the end of 2024, a second Chinese restriction on the sale of components further complicated these transactions for both sides. Both industries were already manufacturing various components in small quantities, but still heavily dependent on Chinese imports. While the Russians expanded their intermediary networks to bypass restrictions and maintain Chinese imports, the Ukrainian Ministry of Defense decided to invest in local companies to produce fiber-optic cables. Essentially, all other components continued to be imported from China via intermediaries, but strangely, several Ukrainian companies started manufacturing low-quality cables and received government funding. The result was an unprecedented superiority of Russian drones on the battlefield, while Ukrainian fiber-optic drones were produced in much smaller numbers, with limited range and low-quality fibers that broke easily. This mistake of nationalizing such a sensitive component was initiated by the Ministry and not due to Chinese restrictions, since all other components continued to be imported through intermediaries. In my view, it was a bold strategy that ultimately failed, compromising the Ukrainian advantage until that moment. You either win the war or make money. It's hard to do both. It will be a major challenge for Ukraine to regain its front-line capacity as it previously was, facing a Russian production of 500,000 fiber-optic drones annually. This significant error weakened Ukrainian defense, which was already operating with low manpower and high desertion rates, but was still adjusting and maintaining the front through the hiring of mercenaries for many months. Given the scarcity of equipment on the front line, there is doubt whether lowering recruitment age will have the desired effect to sustain the front for a long period. It would also be necessary to resolve the issue with fiber-optic drones and for Ukraine to receive another batch of equipment from 2023, which I believe is unlikely. The situation involves multiple aspects of deterioration that have persisted for a long time, continuing to impact the AFU. While financial aid is being maintained, the absence of American support with weaponry is being felt as a crucial issue.

Patricia Marins

130,519 次观看 • 9 个月前

Etched has recruited legends from NVIDIA, Intel, Broadcom, Apple, and DeepMind: - Brian Loiler: built NVIDIA's HGX and DGX systems from scratch over 22 years - Wayne Cao: led 0-to-1 production for the original iPhone - David Munday: built the TPU software team at Google - Saptadeep Pal: NVIDIA's H100 architecture team - Mark Ross: ex-CTO of Cypress (acquired for $9.4B) They recruit through a process they call project-based recruiting: "We map out all of the hardest technical problems across all industries that anyone has ever had to solve. We look at who did the 0 to 1, who was actually in charge, who did the work. We talked to as many people as possible, and then we just track it. The amount of people who say yes after the first conversation is low, but the amount who say yes after the 20th is surprisingly high. The number one guy in the world versus the number ten versus the number one hundred is a huge difference in whether it's actually possible to solve the problem."

Etched has recruited legends from NVIDIA, Intel, Broadcom, Apple, and DeepMind: - Brian Loiler: built NVIDIA's HGX and DGX systems from scratch over 22 years - Wayne Cao: led 0-to-1 production for the original iPhone - David Munday: built the TPU software team at Google - Saptadeep Pal: NVIDIA's H100 architecture team - Mark Ross: ex-CTO of Cypress (acquired for $9.4B) They recruit through a process they call project-based recruiting: "We map out all of the hardest technical problems across all industries that anyone has ever had to solve. We look at who did the 0 to 1, who was actually in charge, who did the work. We talked to as many people as possible, and then we just track it. The amount of people who say yes after the first conversation is low, but the amount who say yes after the 20th is surprisingly high. The number one guy in the world versus the number ten versus the number one hundred is a huge difference in whether it's actually possible to solve the problem."

Patrick OShaughnessy

109,181 次观看 • 1 个月前