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Cloud and Cloud Shadow Detection From Satellite Imagery with GeoAI and OmniCloudMask In this tutorial, you’ll detect clouds and cloud shadows, compute cloud statistics, clean segmentation outputs, convert raster masks to vectors, smooth boundaries, and generate a cloud-free mask for downstream remote sensing analysis. This workflow works with imagery...

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Qiusheng Wu

53,795 subscribers

11,554 просмотров • 6 месяцев назад •via X (Twitter)

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Create Stunning Time-Series Satellite Images in Seconds! The GEE Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satellite
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Create Stunning Time-Series Satellite Images in Seconds! The GEE Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satellite

Qiusheng Wu

14,171 просмотров • 8 месяцев назад

In this setup, a Blender blockout provides the motion and composition while a reference image guides the environment, subject, and textures with MiniMax H3. With open weights, you can previs the final look locally for free or run it on Comfy Cloud. To try this workflow, link below 👇
0:12

In this setup, a Blender blockout provides the motion and composition while a reference image guides the environment, subject, and textures with MiniMax H3. With open weights, you can previs the final look locally for free or run it on Comfy Cloud. To try this workflow, link below 👇

ComfyUI

34,344 просмотров • 1 месяц назад

Introducing our new logo!⚡ This redesign symbolizes our step forward in decentralized cloud computing, setting one of the stones for a successful market entry. The letters n-u-c-o together symbolize the fusion of data, technology, and security, with the standout green dot representing activity ON, and the presence of electrical and electronic energy. Our complete re-brand aligns with our mission to become a leader in the cloud sector and will visually present PRO to large enterprises in the coming launch! ☁️
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Introducing our new logo!⚡ This redesign symbolizes our step forward in decentralized cloud computing, setting one of the stones for a successful market entry. The letters n-u-c-o together symbolize the fusion of data, technology, and security, with the standout green dot representing activity ON, and the presence of electrical and electronic energy. Our complete re-brand aligns with our mission to become a leader in the cloud sector and will visually present PRO to large enterprises in the coming launch! ☁️

nuco.cloud

63,397 просмотров • 2 лет назад

🛰️ 👀 I spotted over 🇮🇹Italy, during yesterday's Naples earthquake, a cloud formation identical to the one that went viral after the major earthquake in 🇯🇵Japan! 👇 ☁️ A cloud formation remarkably similar to the anvil cloud that went viral after the Mw 7.1 earthquake in Japan was visible in satellite imagery just hours before yesterday’s Mw 4.7 earthquake near Naples, Italy. 📈 Despite the massive difference in earthquake magnitude, the cloud structures are strikingly similar. This highlights a crucial point: ☁️ Cumulonimbus Incus (anvil) clouds are a natural product of intense atmospheric convection. Warm, moist air rises rapidly; upon reaching the tropopause, it can no longer ascend and spreads outward, creating the characteristic anvil-shaped top. After major earthquakes, people naturally tend to associate unusual atmospheric phenomena with seismic activity—a classic confirmation bias. However, available meteorological evidence indicates that both cloud formations are fully explained by standard atmospheric physics. Science is about identifying causation—not just noticing similarities. 🫆 Follow Jeo Albant for more analysis. Retweet if you find this useful! 🔄 ℹ️ Satellite Analysis: The cloud shows classic convective vertical growth (17:20–18:30 TSI) followed by horizontal spreading at the tropopause level (18:50–19:40 TSI), forming the distinct anvil (Cumulonimbus Incus) structure—identical to the one seen in Japan. #CampiFlegrei #TerremotoNapoli #Meteo #Sismologia #地震雲 #地震 #熊本地震 #Earthquake #cloud #Satellite #Meteorology #Naples #ItalyEarthquake #Science #Geology #deprem #bulut
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🛰️ 👀 I spotted over 🇮🇹Italy, during yesterday's Naples earthquake, a cloud formation identical to the one that went viral after the major earthquake in 🇯🇵Japan! 👇 ☁️ A cloud formation remarkably similar to the anvil cloud that went viral after the Mw 7.1 earthquake in Japan was visible in satellite imagery just hours before yesterday’s Mw 4.7 earthquake near Naples, Italy. 📈 Despite the massive difference in earthquake magnitude, the cloud structures are strikingly similar. This highlights a crucial point: ☁️ Cumulonimbus Incus (anvil) clouds are a natural product of intense atmospheric convection. Warm, moist air rises rapidly; upon reaching the tropopause, it can no longer ascend and spreads outward, creating the characteristic anvil-shaped top. After major earthquakes, people naturally tend to associate unusual atmospheric phenomena with seismic activity—a classic confirmation bias. However, available meteorological evidence indicates that both cloud formations are fully explained by standard atmospheric physics. Science is about identifying causation—not just noticing similarities. 🫆 Follow Jeo Albant for more analysis. Retweet if you find this useful! 🔄 ℹ️ Satellite Analysis: The cloud shows classic convective vertical growth (17:20–18:30 TSI) followed by horizontal spreading at the tropopause level (18:50–19:40 TSI), forming the distinct anvil (Cumulonimbus Incus) structure—identical to the one seen in Japan. #CampiFlegrei #TerremotoNapoli #Meteo #Sismologia #地震雲 #地震 #熊本地震 #Earthquake #cloud #Satellite #Meteorology #Naples #ItalyEarthquake #Science #Geology #deprem #bulut

Jeo Albant

172,335 просмотров • 2 месяцев назад

⛓️ Aethir - the decentralized #GPU powerhouse reshaping #AI & #gaming! Aethir is building the future of high-performance computing with a global #DePIN network of 400,000+ enterprise-grade GPU containers (including #NVIDIA H100s, H200s & more) spanning 90+ countries. 📍 Two flagship products: • Aethir Earth – Bare-metal GPU cloud delivering raw power for AI training, fine-tuning & inference with zero virtualization overhead. • Aethir Atmosphere – Low-latency cloud gaming rendering that streams high-quality experiences to any device. ☁️ Cloud Hosts monetize idle GPUs and earn $ATH rewards, while customers get scalable, cost-efficient compute (up to 80% cheaper than traditional clouds), ultra-low latency, and 95%+ utilization rates. No massive CapEx, no vendor lock-in – just on-demand access closer to the edge. From AI model training to real-time cloud gaming and beyond, Aethir is democratizing enterprise GPU power and powering the next generation of innovation. 🦾 Axe Compute’s $317M in customer prepayments. That single number reframes how AI data centers get built in 2026 🧵 The decentralized cloud is here. Are you ready? 🌐 #Aethir #DePIN #AI #GPUCloud #Web3
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⛓️ Aethir - the decentralized #GPU powerhouse reshaping #AI & #gaming! Aethir is building the future of high-performance computing with a global #DePIN network of 400,000+ enterprise-grade GPU containers (including #NVIDIA H100s, H200s & more) spanning 90+ countries. 📍 Two flagship products: • Aethir Earth – Bare-metal GPU cloud delivering raw power for AI training, fine-tuning & inference with zero virtualization overhead. • Aethir Atmosphere – Low-latency cloud gaming rendering that streams high-quality experiences to any device. ☁️ Cloud Hosts monetize idle GPUs and earn $ATH rewards, while customers get scalable, cost-efficient compute (up to 80% cheaper than traditional clouds), ultra-low latency, and 95%+ utilization rates. No massive CapEx, no vendor lock-in – just on-demand access closer to the edge. From AI model training to real-time cloud gaming and beyond, Aethir is democratizing enterprise GPU power and powering the next generation of innovation. 🦾 Axe Compute’s $317M in customer prepayments. That single number reframes how AI data centers get built in 2026 🧵 The decentralized cloud is here. Are you ready? 🌐 #Aethir #DePIN #AI #GPUCloud #Web3

Crypto Holding™ 💎

230,871 просмотров • 1 месяц назад

So this is a weird one. I was looking at flight radar cause they just decided to drop like infinite trails in a row and I noticed a helicopter with strange markings I have never seen in the the middle of deep Maine woods. North of Jackman(for reference on sat imagery) I zoom into this little tiny helicopter pad in the middle of nowhere, literally, I’ve been up there and there’s nothing. Right next to the helicopter pad is a strange facility that looks a lot like it has a bunch of radar. While I’m screen recording the helicopter disappears, I go back to check the history to get a screenshot of the information, and it’s been erased. 🤔🤔🤔 so just for poops and giggles I checked the satellite imagery from that area to see if there’s any strange affects happening in cloud structure, and weirdly enough, that location seems to be the center of some very frequency type cloud structures, and there’s a couple weird anomaly lines that pop up.
1:07

So this is a weird one. I was looking at flight radar cause they just decided to drop like infinite trails in a row and I noticed a helicopter with strange markings I have never seen in the the middle of deep Maine woods. North of Jackman(for reference on sat imagery) I zoom into this little tiny helicopter pad in the middle of nowhere, literally, I’ve been up there and there’s nothing. Right next to the helicopter pad is a strange facility that looks a lot like it has a bunch of radar. While I’m screen recording the helicopter disappears, I go back to check the history to get a screenshot of the information, and it’s been erased. 🤔🤔🤔 so just for poops and giggles I checked the satellite imagery from that area to see if there’s any strange affects happening in cloud structure, and weirdly enough, that location seems to be the center of some very frequency type cloud structures, and there’s a couple weird anomaly lines that pop up.

dam blue

42,918 просмотров • 1 месяц назад

A view from a plane... What is happening! Are we living in a parallel universe? How is it possible for anyone to look out of a plane window at 38k feet and see this, above the cloud cover, and just go with the propaganda narrative that it's only condensation?
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A view from a plane... What is happening! Are we living in a parallel universe? How is it possible for anyone to look out of a plane window at 38k feet and see this, above the cloud cover, and just go with the propaganda narrative that it's only condensation?

nogps

48,869 просмотров • 5 месяцев назад

Traditionally, sensor fusion is a software-heavy process prone to temporal lag and parallax errors. With Rev8, we’ve moved that complexity to the silicon. This SLAM sequence is powered by Ouster’s our new L4 MAX chip. Because the lidar and color data are fused at the moment of measurement, the point cloud is born with 48-bit color. No extrinsic calibration, no drift, and zero latency. For perception teams, this means better classification of safety vests, traffic signals, and road markings without the compute overhead of post-processing. Learn more about Native Color and the OS1 MAX:
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Traditionally, sensor fusion is a software-heavy process prone to temporal lag and parallax errors. With Rev8, we’ve moved that complexity to the silicon. This SLAM sequence is powered by Ouster’s our new L4 MAX chip. Because the lidar and color data are fused at the moment of measurement, the point cloud is born with 48-bit color. No extrinsic calibration, no drift, and zero latency. For perception teams, this means better classification of safety vests, traffic signals, and road markings without the compute overhead of post-processing. Learn more about Native Color and the OS1 MAX:

Ouster

47,893 просмотров • 5 месяцев назад

MONTHLY RECAP 🎬 This month has been huge for us at Here's all the achievements and milestones! ↓ 1️⃣ 2,000 $NCDT holders! Earlier this month, we hit 2,000 holders for our $NCDT token!. 2️⃣ Brand Launch Date Set for April 6th! we've been hard at work giving a fresh face and with some teases through the month, we are finally ready to drop our new branding on April 6th! Our new branding will embody our journey in becoming a global leader in cloud computing. This comprehensive rebrand, including a refreshed logo and website, aligns perfectly with our mission and strategic goals. 3️⃣ PRO - Final Penetration Testing PRO is undergoing its final penetration test, ensuring that we are meeting the highest standards of security and reliability in the cloud computing industry. With PRO businesses from large enterprises to AI startups can experience reliable, and efficient computing without breaking the bank. March has been an exciting month for and April will be even better 🚀
0:10

MONTHLY RECAP 🎬 This month has been huge for us at Here's all the achievements and milestones! ↓ 1️⃣ 2,000 $NCDT holders! Earlier this month, we hit 2,000 holders for our $NCDT token!. 2️⃣ Brand Launch Date Set for April 6th! we've been hard at work giving a fresh face and with some teases through the month, we are finally ready to drop our new branding on April 6th! Our new branding will embody our journey in becoming a global leader in cloud computing. This comprehensive rebrand, including a refreshed logo and website, aligns perfectly with our mission and strategic goals. 3️⃣ PRO - Final Penetration Testing PRO is undergoing its final penetration test, ensuring that we are meeting the highest standards of security and reliability in the cloud computing industry. With PRO businesses from large enterprises to AI startups can experience reliable, and efficient computing without breaking the bank. March has been an exciting month for and April will be even better 🚀

nuco.cloud

16,284 просмотров • 2 лет назад

Breaking: Hubble Telescope Opens a "Window" into the Dark Universe — First-Ever Detection of a Starless Dark Matter Cloud! In a groundbreaking discovery announced by NASA, the Hubble Space Telescope has revealed an entirely new class of cosmic object: a vast, starless cloud dominated by dark matter, rich in gas but completely devoid of stars. Nicknamed Cloud-9, this enigmatic structure lies about 14 million light-years away, on the outskirts of the spiral galaxy Messier 94 (M94).This is the first confirmed observation of such a "failed galaxy" or relic from the early universe — a massive dark matter halo that gathered hydrogen gas but never triggered star formation. Hubble's deep imaging ruled out any hidden faint stars, confirming it's truly dark and star-free.Key highlights from the discovery:Massive dark matter core — estimated at around 5 billion solar masses, anchoring a compact reservoir of gas. A cosmic fossil — likely a survivor from the universe's infancy, halted during reionization (when the first stars and galaxies lit up and ionized surrounding gas). Implications — This "phantom" object provides direct evidence for the existence of low-mass dark matter halos that never evolved into full galaxies. It suggests the universe could be filled with similar invisible structures, offering a major boost to our understanding of dark matter and galaxy formation. For decades, theorists predicted these "dark galaxies" or RELHICs (Reionization-Limited Hydrogen Clouds), but Cloud-9 marks the first solid proof caught in the act.Scientists are buzzing — this rare "wow" moment could rewrite parts of cosmic history and hint at countless other hidden building blocks of the universe lurking in the shadows.(Source: NASA/ESA Hubble release, January
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Breaking: Hubble Telescope Opens a "Window" into the Dark Universe — First-Ever Detection of a Starless Dark Matter Cloud! In a groundbreaking discovery announced by NASA, the Hubble Space Telescope has revealed an entirely new class of cosmic object: a vast, starless cloud dominated by dark matter, rich in gas but completely devoid of stars. Nicknamed Cloud-9, this enigmatic structure lies about 14 million light-years away, on the outskirts of the spiral galaxy Messier 94 (M94).This is the first confirmed observation of such a "failed galaxy" or relic from the early universe — a massive dark matter halo that gathered hydrogen gas but never triggered star formation. Hubble's deep imaging ruled out any hidden faint stars, confirming it's truly dark and star-free.Key highlights from the discovery:Massive dark matter core — estimated at around 5 billion solar masses, anchoring a compact reservoir of gas. A cosmic fossil — likely a survivor from the universe's infancy, halted during reionization (when the first stars and galaxies lit up and ionized surrounding gas). Implications — This "phantom" object provides direct evidence for the existence of low-mass dark matter halos that never evolved into full galaxies. It suggests the universe could be filled with similar invisible structures, offering a major boost to our understanding of dark matter and galaxy formation. For decades, theorists predicted these "dark galaxies" or RELHICs (Reionization-Limited Hydrogen Clouds), but Cloud-9 marks the first solid proof caught in the act.Scientists are buzzing — this rare "wow" moment could rewrite parts of cosmic history and hint at countless other hidden building blocks of the universe lurking in the shadows.(Source: NASA/ESA Hubble release, January

Black Hole

10,676 просмотров • 8 месяцев назад

Seedance 2.5 tends to pick up more natural movement and follow 3D blockouts more closely—but sometimes the results are nearly 1:1 with MiniMax. MiniMax ran at a fraction of the credit cost in this Comfy Cloud test, or can be run locally for free. Both have their place. It comes down to the use case, the results you need, and how much room you have to iterate. To try this workflow, link below 👇
0:14

Seedance 2.5 tends to pick up more natural movement and follow 3D blockouts more closely—but sometimes the results are nearly 1:1 with MiniMax. MiniMax ran at a fraction of the credit cost in this Comfy Cloud test, or can be run locally for free. Both have their place. It comes down to the use case, the results you need, and how much room you have to iterate. To try this workflow, link below 👇

ComfyUI

33,089 просмотров • 2 месяцев назад

Claude + Obsidian + n8n + 316 TB storage built a private second brain that ships AI projects at $3,400 a month. Most people rent cloud space and pray the bills stay low. Data leaks. Models throttle. Projects slow. This stack runs everything local. → Obsidian vault grows without limits. Every note, dataset, fine-tune, client archive links in one graph. → Claude reads the full vault instantly through Projects and MCP. No token caps. No privacy risk. → n8n automates the pipelines. New data drops → auto-ingest → Claude summarizes and links. Nightly fine-tune jobs fire. Client deliverables generate on demand. → One ORICO enclosure starts at 60 TB. Add drives. 180 TB. 300 TB. Final setup hits 316 TB. HDDs for archives. SSDs for active models. Laptop-level speed in a desktop box. Plug, power, done. Month 1: Vault hits 120 GB. First local agent runs end-to-end. Month 2: Private dataset training. Sold one custom workflow for $1,200. No cloud fees. Month 3: Recurring retainers. $3,400. System trains, tests, and deploys while you review. Before: Scattered cloud tabs. Monthly bills. Slow inference. After: 316 TB under your desk. Full control. Zero latency. Projects compound. The second brain does not beg for API keys. It owns the data and prints the income. If this was useful - follow.
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Claude + Obsidian + n8n + 316 TB storage built a private second brain that ships AI projects at $3,400 a month. Most people rent cloud space and pray the bills stay low. Data leaks. Models throttle. Projects slow. This stack runs everything local. → Obsidian vault grows without limits. Every note, dataset, fine-tune, client archive links in one graph. → Claude reads the full vault instantly through Projects and MCP. No token caps. No privacy risk. → n8n automates the pipelines. New data drops → auto-ingest → Claude summarizes and links. Nightly fine-tune jobs fire. Client deliverables generate on demand. → One ORICO enclosure starts at 60 TB. Add drives. 180 TB. 300 TB. Final setup hits 316 TB. HDDs for archives. SSDs for active models. Laptop-level speed in a desktop box. Plug, power, done. Month 1: Vault hits 120 GB. First local agent runs end-to-end. Month 2: Private dataset training. Sold one custom workflow for $1,200. No cloud fees. Month 3: Recurring retainers. $3,400. System trains, tests, and deploys while you review. Before: Scattered cloud tabs. Monthly bills. Slow inference. After: 316 TB under your desk. Full control. Zero latency. Projects compound. The second brain does not beg for API keys. It owns the data and prints the income. If this was useful - follow.

HodlReaper

35,529 просмотров • 1 месяц назад

Now feels like the right time to share this. 10 seconds prior to the alleged shot, an anomaly appears in the sky and than disappears shortly after Charlie leaves the UVU campus. I don't know what it is...but I do not think it's a cloud. The first video was screen recorded from Adam Bartholomew 🗨️ youtube, and I used CapCut to turn down the brightness so it would be easier to see. Other then that no other edits were made. the second video is with a negative filter and zoomed in.
0:54

Now feels like the right time to share this. 10 seconds prior to the alleged shot, an anomaly appears in the sky and than disappears shortly after Charlie leaves the UVU campus. I don't know what it is...but I do not think it's a cloud. The first video was screen recorded from Adam Bartholomew 🗨️ youtube, and I used CapCut to turn down the brightness so it would be easier to see. Other then that no other edits were made. the second video is with a negative filter and zoomed in.

thisauthentic

11,274 просмотров • 1 месяц назад

THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?
0:13

THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?

Framez

18,004 просмотров • 2 месяцев назад

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.
0:15

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

258,823 просмотров • 3 месяцев назад

Tropical Storm Dolphin formed only 17 hours ago and already she is constructing a frantic inner core, with boiling, dry-ice bubbles of convection deep freezing the embryonic eyewall structure hidden beneath the cloud tops. This compact, fast-growing behavior seems to be priming Dolphin for explosively rapid intensification. From the very first advisory, she has been forecast to become a Super Typhoon, and everything we’re seeing right now looks to be snowballing in that direction.
0:17

Tropical Storm Dolphin formed only 17 hours ago and already she is constructing a frantic inner core, with boiling, dry-ice bubbles of convection deep freezing the embryonic eyewall structure hidden beneath the cloud tops. This compact, fast-growing behavior seems to be priming Dolphin for explosively rapid intensification. From the very first advisory, she has been forecast to become a Super Typhoon, and everything we’re seeing right now looks to be snowballing in that direction.

Backpirch Weather

13,076 просмотров • 2 месяцев назад

This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.
0:11

This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.

Gipp 🦅

591,712 просмотров • 4 месяцев назад

30 websites that feel illegal to know but are 100% legal👇 1. – Scans files and URLs using 70+ antivirus engines to detect malware. 2. – Disposable email addresses to avoid spam when signing up. 3. Turns any digital process into a visual tutorial guide instantly. 4. Free tools to convert, edit, and modify PDFs, images, and videos. 5. AI tools designed to break down overwhelming tasks into clear steps. 6. – The largest directory of AI tools updated daily. 7. Removes video backgrounds automatically with a single click. 8. AI tools to remove objects, edit photos, and build product images. 9. Quickly removes unwanted objects or text from photos. 10. Thousands of legally free fonts for personal and commercial projects. 11. – An ultra-fast color palette generator for designers and creators. 12. – Free stock video clips, music, sound effects, and video templates. 13. – Search engine for millions of free PDF books and educational materials. 14. – Open index for books, papers, and public domain content. 15. – Open access to millions of research papers and academic articles. 16. – Computes step-by-step solutions for complex math and science queries. 17. – Digital library giving free access to books, old web pages, and media. 18. – Audit thousands of free university courses from Stanford, Yale, and Harvard. 19. – Share unlimited size files direct peer-to-peer without cloud storage. 20. – Automatically creates step-by-step how-to guides while you work. 21. – Checks if your email or password was leaked in data breaches. 22. – Direct links to permanently delete your accounts from web services. 23. – A minimalist platform to publish micro-thoughts without hassle. 24. – Send encrypted text notes that self-destruct after being read once. 25. – Interactive globe to listen to live radio stations around the world. 26. – Simulate driving through major world cities with local live radio. 27. – Customizable ambient sound generators for focus and relaxation. 28. – Recommends free and open-source alternatives to expensive software. 29. – Amazon price history tracker to find real deals. 30. – Frameworks and mental models to help solve problems and make decisions. Save this. You’ll definitely need some of these later. 🔖 Follow Zakir Hossain for more useful websites, AI tools & tech resources.
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30 websites that feel illegal to know but are 100% legal👇 1. – Scans files and URLs using 70+ antivirus engines to detect malware. 2. – Disposable email addresses to avoid spam when signing up. 3. Turns any digital process into a visual tutorial guide instantly. 4. Free tools to convert, edit, and modify PDFs, images, and videos. 5. AI tools designed to break down overwhelming tasks into clear steps. 6. – The largest directory of AI tools updated daily. 7. Removes video backgrounds automatically with a single click. 8. AI tools to remove objects, edit photos, and build product images. 9. Quickly removes unwanted objects or text from photos. 10. Thousands of legally free fonts for personal and commercial projects. 11. – An ultra-fast color palette generator for designers and creators. 12. – Free stock video clips, music, sound effects, and video templates. 13. – Search engine for millions of free PDF books and educational materials. 14. – Open index for books, papers, and public domain content. 15. – Open access to millions of research papers and academic articles. 16. – Computes step-by-step solutions for complex math and science queries. 17. – Digital library giving free access to books, old web pages, and media. 18. – Audit thousands of free university courses from Stanford, Yale, and Harvard. 19. – Share unlimited size files direct peer-to-peer without cloud storage. 20. – Automatically creates step-by-step how-to guides while you work. 21. – Checks if your email or password was leaked in data breaches. 22. – Direct links to permanently delete your accounts from web services. 23. – A minimalist platform to publish micro-thoughts without hassle. 24. – Send encrypted text notes that self-destruct after being read once. 25. – Interactive globe to listen to live radio stations around the world. 26. – Simulate driving through major world cities with local live radio. 27. – Customizable ambient sound generators for focus and relaxation. 28. – Recommends free and open-source alternatives to expensive software. 29. – Amazon price history tracker to find real deals. 30. – Frameworks and mental models to help solve problems and make decisions. Save this. You’ll definitely need some of these later. 🔖 Follow Zakir Hossain for more useful websites, AI tools & tech resources.

Zakir Hossain

32,109 просмотров • 25 дней назад