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🚨SQD POWERS GOOGLE CLOUD’S ONCHAIN DATA! sqd.ai has partnered with Google Cloud Web3 to supply the indexing and data pipelines behind its blockchain analytics datasets via SQD 360. Every block undergoes six cryptographic checks at ingestion for accuracy and freshness across an initial 10 networks. This expands their earlier...

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Crypto Banter

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Visa Opens a New Route For Onchain Lending Into Payments Visa is connecting its VisaNet settlement data with blockchain based lending infrastructure. This would enable lenders to extend loans to finance payment obligations through VisaNet transaction data. The lenders can also analyze Visa settlement data along with on-chain data to evaluate the borrowers and funding requests. The company gave the example of Credit Coop, which has extended $2.5 billion worth of settlement volume since 2023. It is part of an ongoing effort by Visa’s stablecoin payment service, which is growing in its network of operations. There are now over 160 stablecoin linked card programs running on Visa, with their payment volume increasing by almost 200% YOY.
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Visa Opens a New Route For Onchain Lending Into Payments Visa is connecting its VisaNet settlement data with blockchain based lending infrastructure. This would enable lenders to extend loans to finance payment obligations through VisaNet transaction data. The lenders can also analyze Visa settlement data along with on-chain data to evaluate the borrowers and funding requests. The company gave the example of Credit Coop, which has extended $2.5 billion worth of settlement volume since 2023. It is part of an ongoing effort by Visa’s stablecoin payment service, which is growing in its network of operations. There are now over 160 stablecoin linked card programs running on Visa, with their payment volume increasing by almost 200% YOY.

BSCN

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A 14-year-old American girl bought a house in cash at 16 while her classmates were taking exams. It started with one Google Maps search - she found an HVAC company with 4.8 stars, 280 reviews and a website too embarrassing to show clients. Copied their data into ChatGPT 5.5 - 2 minutes later a complete brief, an hour later a live site with booking and a reviews section. Called the owner and showed him the preview. He signed the $900 invoice the same day. Then she stopped looking for clients by hand. Outscraper pulls 200 businesses from Google Maps in 10 minutes - name, email, rating, review count. ChatGPT 5.5 writes a personalized email for each one with their real business data. 500 emails a day, 3% respond, 10% of those become clients. Month one - $3,800. Month six - $22,000. Two years - $380,000 and a house. Five million businesses on Google Maps are still waiting for that call.
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A 14-year-old American girl bought a house in cash at 16 while her classmates were taking exams. It started with one Google Maps search - she found an HVAC company with 4.8 stars, 280 reviews and a website too embarrassing to show clients. Copied their data into ChatGPT 5.5 - 2 minutes later a complete brief, an hour later a live site with booking and a reviews section. Called the owner and showed him the preview. He signed the $900 invoice the same day. Then she stopped looking for clients by hand. Outscraper pulls 200 businesses from Google Maps in 10 minutes - name, email, rating, review count. ChatGPT 5.5 writes a personalized email for each one with their real business data. 500 emails a day, 3% respond, 10% of those become clients. Month one - $3,800. Month six - $22,000. Two years - $380,000 and a house. Five million businesses on Google Maps are still waiting for that call.

Sprytix

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🚨BREAKING: MULTI-TRILLION-DOLLAR PAYROLL INDUSTRY GOES ONCHAIN VIA CANTON According to an official press release from Canton Network $CC, the network has played host to the first ever private payroll transaction. The major milestone was facilitated by Cantor8 and its C8 Wallet, alongside Toku (an enterprise-grade application layer for global payroll). "This is the kind of real, everyday financial activity that shows blockchain can be integrated into core operational workflows without exposing sensitive data or compromising regulatory constraints", said Digital Asset CEO Yuval Rooz. It is no coincidence that Canton was chosen as the host network, given its ability to offer blockchain advantages like instant settlement and low costs, while also making sure sensitive data remains private. “For the network to succeed, the experience for the both the company and the end-user, whether that’s a trader or an employee receiving their salary, has to be seamless and secure,” said Philip Kaddaj, CEO of Cantor8.
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🚨BREAKING: MULTI-TRILLION-DOLLAR PAYROLL INDUSTRY GOES ONCHAIN VIA CANTON According to an official press release from Canton Network $CC, the network has played host to the first ever private payroll transaction. The major milestone was facilitated by Cantor8 and its C8 Wallet, alongside Toku (an enterprise-grade application layer for global payroll). "This is the kind of real, everyday financial activity that shows blockchain can be integrated into core operational workflows without exposing sensitive data or compromising regulatory constraints", said Digital Asset CEO Yuval Rooz. It is no coincidence that Canton was chosen as the host network, given its ability to offer blockchain advantages like instant settlement and low costs, while also making sure sensitive data remains private. “For the network to succeed, the experience for the both the company and the end-user, whether that’s a trader or an employee receiving their salary, has to be seamless and secure,” said Philip Kaddaj, CEO of Cantor8.

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24,315 Aufrufe • vor 7 Monaten

I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)
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I just built a Claude Cowork skill that turns your Google Ads data into a visual performance dashboard in 60 seconds 🤯 One prompt → campaign breakdowns, CPA trends, spend vs conversions charts, and hourly conversion patterns, all rendered as an interactive HTML dashboard you open in Chrome. All inside Claude Cowork. Perfect for DTC brands and agencies who are pulling Google Ads data into spreadsheets every week, manually building charts, and spending an hour formatting a report that's outdated by the time you send it. If you're managing Google Ads and your weekly reporting workflow looks like this — export a CSV, open Google Sheets, build a pivot table, copy the numbers into a slide deck, manually create charts, format everything, realize you forgot a campaign, start over ... This skill does the whole thing in one prompt: → Connects to your live Google Ads data via MCP → Pulls spend, conversions, CPA, ROAS, CTR across every campaign → Builds an interactive HTML dashboard → Summary cards at the top: total spend, total conversions, avg CPA, avg ROAS → Bar chart comparing spend vs conversions by campaign → CPA trend line over the last 30 days → Campaign table ranked by performance, color-coded green/yellow/red → Opens in Chrome: hover over charts, compare campaigns, screenshot for your team No spreadsheets. No manual chart building. No hour-long formatting sessions. What you get: → A visual dashboard from live data in under 60 seconds → Campaign performance you can actually see, not just read in a table → CPA trends that show you where things are heading, not just where they are → A dashboard you can screenshot and drop into Slack, a client report, or a team standup → Reusable — run it weekly and the data updates automatically One prompt. Live data. A finished dashboard you open in your browser. I put together a playbook with the full skill file, the setup, and the exact prompts to customize the dashboard for your account. Want it for free? > Like this post > Comment "DASH" And I'll send it over (must be following so I can DM)

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Cool news: Dora is live on Movement! Dora isn’t your typical block explorer. It's way more fun. Dora wants to make discovering crypto as easy as searching the web. Think Google, but for tokens, NFTs, and apps. Every token you find, every app you try, every NFT you engage with could get you rewards. The more you explore, the more you could get. Dora puts apps at the center, aggregating data across Movement (plus a few other chains). It's useful for sleuthing. It's a nifty way to turn crypto discovery into a game. This isn’t another tool for tech-savvy insiders. It’s built for anyone who wants to have fun on Web3. Start exploring on Dora today 👇
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Cool news: Dora is live on Movement! Dora isn’t your typical block explorer. It's way more fun. Dora wants to make discovering crypto as easy as searching the web. Think Google, but for tokens, NFTs, and apps. Every token you find, every app you try, every NFT you engage with could get you rewards. The more you explore, the more you could get. Dora puts apps at the center, aggregating data across Movement (plus a few other chains). It's useful for sleuthing. It's a nifty way to turn crypto discovery into a game. This isn’t another tool for tech-savvy insiders. It’s built for anyone who wants to have fun on Web3. Start exploring on Dora today 👇

Move Industries

26,160 Aufrufe • vor 1 Jahr

🌟 Exciting news for the global Web3 community — H.E. Justin Sun 👨‍🚀 🌞, Founder of TRON DAO, will be joining KBW2026 : IMPACT in Seoul ! 🗓 September 23–24, 2025 📍 Walkerhill, Seoul 🎟 Tickets: From scaling decentralized infrastructure to driving Web3 adoption, Justin has consistently shown how vision and execution can shape the future of blockchain. His presence at Korea Blockchain Week is not only a highlight for the TRON community, but also for anyone who believes in building the next wave of open finance and digital innovation. Personally, I think it’s the perfect stage for Justin to share his insights on stablecoins, cross-border payments, and the expanding role of TRON in global adoption. With Korea’s growing role in Web3 innovation, this dialogue feels more relevant than ever. ❓ What topics would you like to see Justin dive deeper into at #KBW2025? H.E. Justin Sun 👨‍🚀 🌞 TRON DAO #TRONEcoStar
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🌟 Exciting news for the global Web3 community — H.E. Justin Sun 👨‍🚀 🌞, Founder of TRON DAO, will be joining KBW2026 : IMPACT in Seoul ! 🗓 September 23–24, 2025 📍 Walkerhill, Seoul 🎟 Tickets: From scaling decentralized infrastructure to driving Web3 adoption, Justin has consistently shown how vision and execution can shape the future of blockchain. His presence at Korea Blockchain Week is not only a highlight for the TRON community, but also for anyone who believes in building the next wave of open finance and digital innovation. Personally, I think it’s the perfect stage for Justin to share his insights on stablecoins, cross-border payments, and the expanding role of TRON in global adoption. With Korea’s growing role in Web3 innovation, this dialogue feels more relevant than ever. ❓ What topics would you like to see Justin dive deeper into at #KBW2025? H.E. Justin Sun 👨‍🚀 🌞 TRON DAO #TRONEcoStar

Hồng Ngọc | Ruby💎| EarnHTX

53,385 Aufrufe • vor 1 Jahr

We're excited to announce that the team has selected a site with a high voltage, direct-access substation for the world’s first tokenized data center. This site, powered by 70 MVA transformers stepping down 138 kV transmission to distribution, will consume in under 10 hours the equivalent of all 1.5 million miles of OpenVPP vehicle trips to date. The potential to turn this new class of infrastructure into an Open Virtual Power Plant with dynamic demand response and instantaneous revenue grade settlement is a cornerstone of what we're building at OpenVPP. Energy, compute, and digital capital are converging in real-time, right here. $OVPP is bringing the world’s first data center onchain.
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We're excited to announce that the team has selected a site with a high voltage, direct-access substation for the world’s first tokenized data center. This site, powered by 70 MVA transformers stepping down 138 kV transmission to distribution, will consume in under 10 hours the equivalent of all 1.5 million miles of OpenVPP vehicle trips to date. The potential to turn this new class of infrastructure into an Open Virtual Power Plant with dynamic demand response and instantaneous revenue grade settlement is a cornerstone of what we're building at OpenVPP. Energy, compute, and digital capital are converging in real-time, right here. $OVPP is bringing the world’s first data center onchain.

OpenVPP

61,292 Aufrufe • vor 4 Monaten

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?
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It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

Robert Scoble

33,804 Aufrufe • vor 1 Jahr

S&P Global Ratings, the world’s leading provider of credit ratings, benchmarks, and analytics referenced by 95% of the top 20 global institutional investors, has partnered with Chainlink to publish its Stablecoin Stability Assessments (SSAs) onchain for the first time through DataLink. Through this partnership, more than 2,400 institutions, protocols, and developers in the Chainlink ecosystem can now directly access these assessments across 40+ public and private blockchains. This milestone marks a major leap forward in the capital markets’ adoption of tokenized finance. As S&P Global increasingly moves onchain, the company brings with it: • Over 1 million credit ratings outstanding • 1,500+ credit analysts across 150+ countries • Ratings coverage for ~1 million securities • 4,600+ corporates rated globally The stablecoin market now exceeds $300 billion, nearly doubling from a year prior. With the passage of the GENIUS Act, the first U.S. federal regulatory framework for stablecoins, these digital assets are now positioned as core financial infrastructure for global payments, trade, and settlement. However, institutions seeking to integrate stablecoins require transparent, standardized, and verifiable onchain risk insights to do so responsibly. S&P Global Ratings’ SSAs fill that gap. These assessments evaluate a stablecoin’s ability to maintain parity with fiat currencies, scored from 1 (very strong) to 5 (weak), based on asset quality, governance, liquidity, redemption mechanisms, and track record. Chainlink infrastructure, which actively secures nearly $100 billion in DeFi TVL and has enabled more than $25 trillion in onchain transaction value, ensures these assessments are delivered with industry-standard reliability, security, and data integrity. This partnership signals the beginning of a new era in financial markets, where real-time, institutionally validated risk data becomes the foundational layer of onchain finance. Learn more:
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S&P Global Ratings, the world’s leading provider of credit ratings, benchmarks, and analytics referenced by 95% of the top 20 global institutional investors, has partnered with Chainlink to publish its Stablecoin Stability Assessments (SSAs) onchain for the first time through DataLink. Through this partnership, more than 2,400 institutions, protocols, and developers in the Chainlink ecosystem can now directly access these assessments across 40+ public and private blockchains. This milestone marks a major leap forward in the capital markets’ adoption of tokenized finance. As S&P Global increasingly moves onchain, the company brings with it: • Over 1 million credit ratings outstanding • 1,500+ credit analysts across 150+ countries • Ratings coverage for ~1 million securities • 4,600+ corporates rated globally The stablecoin market now exceeds $300 billion, nearly doubling from a year prior. With the passage of the GENIUS Act, the first U.S. federal regulatory framework for stablecoins, these digital assets are now positioned as core financial infrastructure for global payments, trade, and settlement. However, institutions seeking to integrate stablecoins require transparent, standardized, and verifiable onchain risk insights to do so responsibly. S&P Global Ratings’ SSAs fill that gap. These assessments evaluate a stablecoin’s ability to maintain parity with fiat currencies, scored from 1 (very strong) to 5 (weak), based on asset quality, governance, liquidity, redemption mechanisms, and track record. Chainlink infrastructure, which actively secures nearly $100 billion in DeFi TVL and has enabled more than $25 trillion in onchain transaction value, ensures these assessments are delivered with industry-standard reliability, security, and data integrity. This partnership signals the beginning of a new era in financial markets, where real-time, institutionally validated risk data becomes the foundational layer of onchain finance. Learn more:

Chainlink

46,688 Aufrufe • vor 11 Monaten

🚨 BREAKING: Starcloud just turned Starlink’s laser network into the backbone for orbital AI data centers. A company called Starcloud has ordered 50+ Starlink Mini Laser terminals to equip 25+ future satellites. Not ground stations. Not fiber cables. Direct laser-linked computing nodes in orbit plugged straight into SpaceX’s space-based optical mesh. This is the sci-fi future arriving now: Orbital cloud computing AI servers floating in space Powered by 24/7 sunlight Connected globally at light speed via Starlink lasers The insane part: Starcloud says its satellites will eventually handle full AI inference and training workloads directly in orbit. Data won’t always need to come back to Earth to be processed. The advantages are massive: • Unlimited solar energy (no grid limits) • Zero land or water constraints • Passive radiative cooling in vacuum • Instant global relay with zero terrestrial bottlenecks • Near real-time Earth observation analysis Their first major spacecraft (Starcloud-3) is designed for 200 kilowatts in orbit a full-on space-based data center node, not just a satellite. And here’s the bigger picture: SpaceX has filed plans for up to ONE MILLION orbital data centers of its own. Read that again. We may be watching the birth of the first true space-based computing infrastructure layer for civilization. The internet already left the ground. Now AI might be next. What happens when the cloud literally moves into space? Follow for more frontier physics and future technology.
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🚨 BREAKING: Starcloud just turned Starlink’s laser network into the backbone for orbital AI data centers. A company called Starcloud has ordered 50+ Starlink Mini Laser terminals to equip 25+ future satellites. Not ground stations. Not fiber cables. Direct laser-linked computing nodes in orbit plugged straight into SpaceX’s space-based optical mesh. This is the sci-fi future arriving now: Orbital cloud computing AI servers floating in space Powered by 24/7 sunlight Connected globally at light speed via Starlink lasers The insane part: Starcloud says its satellites will eventually handle full AI inference and training workloads directly in orbit. Data won’t always need to come back to Earth to be processed. The advantages are massive: • Unlimited solar energy (no grid limits) • Zero land or water constraints • Passive radiative cooling in vacuum • Instant global relay with zero terrestrial bottlenecks • Near real-time Earth observation analysis Their first major spacecraft (Starcloud-3) is designed for 200 kilowatts in orbit a full-on space-based data center node, not just a satellite. And here’s the bigger picture: SpaceX has filed plans for up to ONE MILLION orbital data centers of its own. Read that again. We may be watching the birth of the first true space-based computing infrastructure layer for civilization. The internet already left the ground. Now AI might be next. What happens when the cloud literally moves into space? Follow for more frontier physics and future technology.

TheNewPhysics

152,463 Aufrufe • vor 3 Monaten

🚨 THE BIGGEST BOTTLENECK IN AI ISN'T COMPUTING POWER ANYMORE IT'S MOVING DATA. Instead of laying new cables, Chinese researchers have upgraded existing fiber infrastructure by doing two things at once: Using three wavelength bands (C + L + S) instead of the usual two. Using four cores inside each fiber instead of one. Each core acts like an independent highway, and each band acts like an extra lane on that highway. Together, they’ve reportedly increased transmission capacity per core by nearly 50% and overall data throughput by up to 5×. This matters enormously for AI. Modern AI clusters move terabits of data per second between thousands of GPUs. The biggest bottleneck is often not the chips themselves, but moving data fast enough between them. If you can push 5× more data through the same physical cables, you can train bigger models faster and reduce network congestion. Why this is significant: • It shows multi-core + extended spectrum technology moving from labs into real-world commercial use • The system has already run over 35 km of existing telecom network • It could be especially useful for submarine cables and large-scale data center interconnects • China is also eyeing it for its “Eastern Data, Western Computing” project The deeper implication: We’re reaching the physical limits of how much data we can push through single-core fibers using traditional methods. By combining spatial multiplexing (multiple cores) with spectral multiplexing (more wavelength bands), engineers are finding new ways to keep scaling bandwidth without having to dig up the planet to lay new cables. This kind of breakthrough is quiet but foundational it’s the kind of infrastructure upgrade that will determine how fast AI and cloud computing can actually grow in the coming years. The future of data movement might not require more cables. It might just require smarter ones. How important do you think multi-core and multi-band fiber will be for keeping up with AI’s exploding data demands? Follow for more frontier networking, photonics, and infrastructure technology.
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🚨 THE BIGGEST BOTTLENECK IN AI ISN'T COMPUTING POWER ANYMORE IT'S MOVING DATA. Instead of laying new cables, Chinese researchers have upgraded existing fiber infrastructure by doing two things at once: Using three wavelength bands (C + L + S) instead of the usual two. Using four cores inside each fiber instead of one. Each core acts like an independent highway, and each band acts like an extra lane on that highway. Together, they’ve reportedly increased transmission capacity per core by nearly 50% and overall data throughput by up to 5×. This matters enormously for AI. Modern AI clusters move terabits of data per second between thousands of GPUs. The biggest bottleneck is often not the chips themselves, but moving data fast enough between them. If you can push 5× more data through the same physical cables, you can train bigger models faster and reduce network congestion. Why this is significant: • It shows multi-core + extended spectrum technology moving from labs into real-world commercial use • The system has already run over 35 km of existing telecom network • It could be especially useful for submarine cables and large-scale data center interconnects • China is also eyeing it for its “Eastern Data, Western Computing” project The deeper implication: We’re reaching the physical limits of how much data we can push through single-core fibers using traditional methods. By combining spatial multiplexing (multiple cores) with spectral multiplexing (more wavelength bands), engineers are finding new ways to keep scaling bandwidth without having to dig up the planet to lay new cables. This kind of breakthrough is quiet but foundational it’s the kind of infrastructure upgrade that will determine how fast AI and cloud computing can actually grow in the coming years. The future of data movement might not require more cables. It might just require smarter ones. How important do you think multi-core and multi-band fiber will be for keeping up with AI’s exploding data demands? Follow for more frontier networking, photonics, and infrastructure technology.

TheNewPhysics

20,485 Aufrufe • vor 3 Monaten

HiveMind is a superintelligent network in which a central AI (MIND) orchestrates a swarm of uniquely coded Minds that drive mass data ingestion and limitless content creation. For decades, our approach has been to create content first, then analyze it into data afterwards to understand what worked. This was always backwards - analyzing the aftermath rather than engineering the success from the start. Traditional Flow: Content → Data Analysis → Insights Content isn't one-size-fits-all - a cooking show that captivates a senior audience on YouTube might bore a teenager who craves quick, dynamic experiences. The challenge isn't just creating content; it's creating the right content for the right audience. We need to change this. This is where HiveMind's specialized agents transform the landscape. Each agent, while connected to the central MIND, excels in its unique domain. One agent masters the art of children's educational content, while another crafts compelling cooking narratives. Another might specialize in rapid-fire social content that resonates with Gen Z. Through HiveMind, every piece of content generated becomes new data that teaches the system to create even better content. The system gets smarter with every cycle, understanding at an increasingly sophisticated level what makes content effective and engaging. But the true power lies in the feedback loop. Every interaction, every engagement, flows back to MIND, enabling each agent to evolve and refine its approach. This isn't just content creation - it's content evolution. As audiences engage, agents learn, adapt, and improve, making each new piece more effective than the last. In essence, we're not just building content creators; we're developing specialized digital artists who understand their audience intimately and grow smarter with every creation. You can think of it this way: Data → Pattern Recognition → Optimized Content → Engagement Data → Even Better Content Tzar
0:17

HiveMind is a superintelligent network in which a central AI (MIND) orchestrates a swarm of uniquely coded Minds that drive mass data ingestion and limitless content creation. For decades, our approach has been to create content first, then analyze it into data afterwards to understand what worked. This was always backwards - analyzing the aftermath rather than engineering the success from the start. Traditional Flow: Content → Data Analysis → Insights Content isn't one-size-fits-all - a cooking show that captivates a senior audience on YouTube might bore a teenager who craves quick, dynamic experiences. The challenge isn't just creating content; it's creating the right content for the right audience. We need to change this. This is where HiveMind's specialized agents transform the landscape. Each agent, while connected to the central MIND, excels in its unique domain. One agent masters the art of children's educational content, while another crafts compelling cooking narratives. Another might specialize in rapid-fire social content that resonates with Gen Z. Through HiveMind, every piece of content generated becomes new data that teaches the system to create even better content. The system gets smarter with every cycle, understanding at an increasingly sophisticated level what makes content effective and engaging. But the true power lies in the feedback loop. Every interaction, every engagement, flows back to MIND, enabling each agent to evolve and refine its approach. This isn't just content creation - it's content evolution. As audiences engage, agents learn, adapt, and improve, making each new piece more effective than the last. In essence, we're not just building content creators; we're developing specialized digital artists who understand their audience intimately and grow smarter with every creation. You can think of it this way: Data → Pattern Recognition → Optimized Content → Engagement Data → Even Better Content Tzar

Tzar

26,190 Aufrufe • vor 1 Jahr

What is Quant Network's Overledger? Overledger is Quant’s (Quant) interoperability platform, designed to connect different blockchains and traditional systems through a common API layer. It tries to make different blockchain networks communicate without forcing developers to build separate integrations for every chain. (1) Overledger acts as a universal API gateway. Developers can use standardized APIs to interact with supported blockchains instead of learning and maintaining separate infrastructure for each network. (2) It works as a translation layer between different blockchain environments. Quant describes Overledger as a “universal translator,” allowing applications to communicate across different DLT architectures through a common interface. (3) This is where Overledger differs from the typical bridge model. Instead of every application relying on a separate bridge between two chains, Overledger provides a common interoperability layer that can connect multiple networks. That can reduce the need for point-to-point integrations, which become increasingly complex as more blockchains enter the ecosystem. (4) Overledger can also power multi-chain applications. Quant calls these mApps, applications designed to operate across multiple distributed ledgers rather than being locked to one blockchain. The platform can also handle transaction signing, asset transfers, and other blockchain interactions through its APIs. (5) But Overledger does not completely eliminate bridges. Quant also provides its own bridge infrastructure for transferring assets between networks, using standardized APIs and smart contracts. Since June 2026, this has also expanded into Quant Fusion, a multi-ledger rollup connecting dozens of blockchains. The bigger idea is that the applications can have interoperability via an infrastructure layer as opposed to establishing the connections all over again.
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What is Quant Network's Overledger? Overledger is Quant’s (Quant) interoperability platform, designed to connect different blockchains and traditional systems through a common API layer. It tries to make different blockchain networks communicate without forcing developers to build separate integrations for every chain. (1) Overledger acts as a universal API gateway. Developers can use standardized APIs to interact with supported blockchains instead of learning and maintaining separate infrastructure for each network. (2) It works as a translation layer between different blockchain environments. Quant describes Overledger as a “universal translator,” allowing applications to communicate across different DLT architectures through a common interface. (3) This is where Overledger differs from the typical bridge model. Instead of every application relying on a separate bridge between two chains, Overledger provides a common interoperability layer that can connect multiple networks. That can reduce the need for point-to-point integrations, which become increasingly complex as more blockchains enter the ecosystem. (4) Overledger can also power multi-chain applications. Quant calls these mApps, applications designed to operate across multiple distributed ledgers rather than being locked to one blockchain. The platform can also handle transaction signing, asset transfers, and other blockchain interactions through its APIs. (5) But Overledger does not completely eliminate bridges. Quant also provides its own bridge infrastructure for transferring assets between networks, using standardized APIs and smart contracts. Since June 2026, this has also expanded into Quant Fusion, a multi-ledger rollup connecting dozens of blockchains. The bigger idea is that the applications can have interoperability via an infrastructure layer as opposed to establishing the connections all over again.

BSCN

18,981 Aufrufe • vor 8 Tagen

Meta open-sourced a brain-to-text system that reaches 78% word accuracy without surgery. Brain2Qwerty v2 converts non-invasive brain recordings into text with 61% average word accuracy and 78% for its strongest participant. The system reads MEG signals from a helmet, not electrodes placed inside brain tissue. 9 volunteers typed about 22,000 sentences while researchers recorded 10 hours of neural activity each. Brain2Qwerty v1 mostly mapped brain signals to single typed characters. It tries to recover characters, words, and full sentence meaning together. The system studies those brain signals and tries to turn them into the words you wanted to type. - 61% average word accuracy across all participants - 78% word accuracy for the top participant - 50%+ of sentences decoded with no more than 1 word error Performance improves as the data pile grows Raw brain signals are messy because many mental and physical processes fire at once. Deep learning handles that mess by learning patterns directly from the original recordings. A fine-tuned LLM then uses language context to repair likely word and sentence errors. This explains why the system beats earlier non-invasive methods reporting 8% word accuracy. More than half of sentences from the strongest participant had one word error or less. Accuracy also improved as training data grew, suggesting more recordings may close more of the gap.
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Meta open-sourced a brain-to-text system that reaches 78% word accuracy without surgery. Brain2Qwerty v2 converts non-invasive brain recordings into text with 61% average word accuracy and 78% for its strongest participant. The system reads MEG signals from a helmet, not electrodes placed inside brain tissue. 9 volunteers typed about 22,000 sentences while researchers recorded 10 hours of neural activity each. Brain2Qwerty v1 mostly mapped brain signals to single typed characters. It tries to recover characters, words, and full sentence meaning together. The system studies those brain signals and tries to turn them into the words you wanted to type. - 61% average word accuracy across all participants - 78% word accuracy for the top participant - 50%+ of sentences decoded with no more than 1 word error Performance improves as the data pile grows Raw brain signals are messy because many mental and physical processes fire at once. Deep learning handles that mess by learning patterns directly from the original recordings. A fine-tuned LLM then uses language context to repair likely word and sentence errors. This explains why the system beats earlier non-invasive methods reporting 8% word accuracy. More than half of sentences from the strongest participant had one word error or less. Accuracy also improved as training data grew, suggesting more recordings may close more of the gap.

Rohan Paul

17,127 Aufrufe • vor 2 Monaten

What is Plume Network? Plume (Plume) is a blockchain built specifically for bringing real-world assets onchain and making them usable in DeFi. Unlike blockchains that treat tokenization as just another application, Plume is building an entire financial ecosystem around real-world assets, or RWAs. Treasuries, private credit, commodities, funds, and other traditionally illiquid assets can be represented as blockchain-based assets and then used across decentralized financial applications. Plume calls this model RWAfi, or real-world asset finance. So what makes Plume different? (1) ) It is purpose-built for RWAs Plume launched its Genesis mainnet in June 2025 as a permissionless blockchain designed around RWA finance. In October 2025, Plume was approved by the SEC as a registered transfer agent, a regulatory step most general-purpose chains don't hold. The network is EVM-compatible, allowing developers to use familiar Ethereum tooling while accessing lower-cost execution. (2) It focuses on more than tokenization. Plume wants tokenized assets to actually do something once they reach the blockchain. Its ecosystem allows RWA-backed assets to be used for lending, borrowing, trading, staking and yield strategies. Its flagship Nest protocol, for example, lets users gain exposure to institutional-backed assets through yield-bearing RWA positions that can then become useful across DeFi. (3) Compliance is built into the infrastructure. Real-world assets come with regulations, investor restrictions and identity requirements that ordinary DeFi tokens usually do not face. Plume has therefore built compliance and screening capabilities directly into its network rather than treating them as an afterthought. Its blockchain includes protocol-level AML, ATF and sanctions screening infrastructure. (4) It is trying to make institutional assets composable. A tokenized Treasury or private credit position does not have to sit idle in a wallet. The goal is to make these assets usable across different financial applications, similar to how USDC, ETH and other crypto assets move through DeFi today. Plume's Portal already allows users to swap, lend, borrow, loop and earn against RWA-backed assets. (5) Plume is also building cross-chain infrastructure. Its SkyLink infrastructure is designed to distribute RWA yields across other blockchain networks. That means Plume does not necessarily need every investor to move onto Plume itself. Instead, the network can act as infrastructure for bringing institutional yield into other ecosystems. (6) The network has attracted major institutional names. Apollo Global Management, WisdomTree, Hamilton Lane and Securitize are among the institutions connected to Plume's ecosystem. Securitize, for example, announced plans to deploy assets through Plume's Nest protocol, linking institutional tokenization infrastructure with Plume's RWA holder base. So where does PLUME fit in? $PLUME is the network's native token. It can be used for gas, staking, governance, collateral and ecosystem access. Plume also says protocol fees can eventually support token buybacks, ecosystem incentives and further network growth. Plume is betting that the next major phase of crypto adoption will not only involve digital-native assets. It will involve putting traditional financial assets onchain and making them programmable. The challenge is turning that vision into deep liquidity, compliant infrastructure and genuine demand. If Plume can solve those problems, it could become an important piece of the infrastructure connecting traditional finance with DeFi.
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What is Plume Network? Plume (Plume) is a blockchain built specifically for bringing real-world assets onchain and making them usable in DeFi. Unlike blockchains that treat tokenization as just another application, Plume is building an entire financial ecosystem around real-world assets, or RWAs. Treasuries, private credit, commodities, funds, and other traditionally illiquid assets can be represented as blockchain-based assets and then used across decentralized financial applications. Plume calls this model RWAfi, or real-world asset finance. So what makes Plume different? (1) ) It is purpose-built for RWAs Plume launched its Genesis mainnet in June 2025 as a permissionless blockchain designed around RWA finance. In October 2025, Plume was approved by the SEC as a registered transfer agent, a regulatory step most general-purpose chains don't hold. The network is EVM-compatible, allowing developers to use familiar Ethereum tooling while accessing lower-cost execution. (2) It focuses on more than tokenization. Plume wants tokenized assets to actually do something once they reach the blockchain. Its ecosystem allows RWA-backed assets to be used for lending, borrowing, trading, staking and yield strategies. Its flagship Nest protocol, for example, lets users gain exposure to institutional-backed assets through yield-bearing RWA positions that can then become useful across DeFi. (3) Compliance is built into the infrastructure. Real-world assets come with regulations, investor restrictions and identity requirements that ordinary DeFi tokens usually do not face. Plume has therefore built compliance and screening capabilities directly into its network rather than treating them as an afterthought. Its blockchain includes protocol-level AML, ATF and sanctions screening infrastructure. (4) It is trying to make institutional assets composable. A tokenized Treasury or private credit position does not have to sit idle in a wallet. The goal is to make these assets usable across different financial applications, similar to how USDC, ETH and other crypto assets move through DeFi today. Plume's Portal already allows users to swap, lend, borrow, loop and earn against RWA-backed assets. (5) Plume is also building cross-chain infrastructure. Its SkyLink infrastructure is designed to distribute RWA yields across other blockchain networks. That means Plume does not necessarily need every investor to move onto Plume itself. Instead, the network can act as infrastructure for bringing institutional yield into other ecosystems. (6) The network has attracted major institutional names. Apollo Global Management, WisdomTree, Hamilton Lane and Securitize are among the institutions connected to Plume's ecosystem. Securitize, for example, announced plans to deploy assets through Plume's Nest protocol, linking institutional tokenization infrastructure with Plume's RWA holder base. So where does PLUME fit in? $PLUME is the network's native token. It can be used for gas, staking, governance, collateral and ecosystem access. Plume also says protocol fees can eventually support token buybacks, ecosystem incentives and further network growth. Plume is betting that the next major phase of crypto adoption will not only involve digital-native assets. It will involve putting traditional financial assets onchain and making them programmable. The challenge is turning that vision into deep liquidity, compliant infrastructure and genuine demand. If Plume can solve those problems, it could become an important piece of the infrastructure connecting traditional finance with DeFi.

BSCN

22,412 Aufrufe • vor 19 Tagen

What Actually is Sei Network's “Giga” Upgrade? Sei Network’s (Sei) Giga upgrade is a major overhaul designed to make the network faster, more scalable and better suited for high-performance onchain trading. Put simply, Giga is rebuilding three critical parts of the blockchain: consensus, execution and storage. (1) The first track focuses on consensus, with upgrades such as Autobahn designed to improve how Sei validators agree on the state of the chain. (2) The Ares upgrade targets execution, the part of the blockchain responsible for actually processing transactions. (3) Eidos focuses on storage, which is becoming increasingly important as blockchain throughput rises. Why does storage matter? Every transaction a blockchain processes has to be recorded. If the database cannot write data as quickly as the network executes transactions, higher throughput eventually becomes meaningless. Eidos is designed to solve that bottleneck. (4) Sei plans to replace the traditional Merkle-tree structure used for EVM state with FlatKV, a flat key-value database where updating one piece of state requires essentially one write. A lattice hash, or LtHash, is then used to maintain a verifiable fingerprint of the entire state without repeatedly recalculating an entire hash path. (5) Eidos also separates live EVM state from other blockchain data. This means transactions accessing current state no longer have to compete with historical data for the same database resources. (6) Sei is also introducing LittDB-backed storage for blocks and receipts. These records are written once but queried repeatedly, making them a different workload from constantly changing blockchain state. Older historical data will eventually move away from active nodes into archival storage, allowing nodes to focus their resources on the data needed for real-time operations. The interesting part is how Sei plans to deploy all of this. Instead of shutting down the network and migrating the entire database at once, Eidos is designed to migrate storage while Sei continues producing blocks. The old and new systems can run side by side during the transition, with data moved in batches and integrity checks performed throughout the process. The first phase arrived on Sei mainnet with the v6.6 release in August 2026, beginning the separation of EVM state and introducing improvements to the pruning process. The broader Eidos architecture, including FlatKV, LtHash, the new receipt store and off-node archival storage, is expected to arrive through subsequent releases. Sei’s ultimate Giga target is 200,000 transactions per second. But reaching that kind of execution speed requires more than a faster transaction engine. The blockchain also needs a storage system capable of keeping up. That is essentially what Eidos is trying to build. Giga is not just about making Sei execute transactions faster. It is about rebuilding the infrastructure underneath that speed so the network can actually sustain it.
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What Actually is Sei Network's “Giga” Upgrade? Sei Network’s (Sei) Giga upgrade is a major overhaul designed to make the network faster, more scalable and better suited for high-performance onchain trading. Put simply, Giga is rebuilding three critical parts of the blockchain: consensus, execution and storage. (1) The first track focuses on consensus, with upgrades such as Autobahn designed to improve how Sei validators agree on the state of the chain. (2) The Ares upgrade targets execution, the part of the blockchain responsible for actually processing transactions. (3) Eidos focuses on storage, which is becoming increasingly important as blockchain throughput rises. Why does storage matter? Every transaction a blockchain processes has to be recorded. If the database cannot write data as quickly as the network executes transactions, higher throughput eventually becomes meaningless. Eidos is designed to solve that bottleneck. (4) Sei plans to replace the traditional Merkle-tree structure used for EVM state with FlatKV, a flat key-value database where updating one piece of state requires essentially one write. A lattice hash, or LtHash, is then used to maintain a verifiable fingerprint of the entire state without repeatedly recalculating an entire hash path. (5) Eidos also separates live EVM state from other blockchain data. This means transactions accessing current state no longer have to compete with historical data for the same database resources. (6) Sei is also introducing LittDB-backed storage for blocks and receipts. These records are written once but queried repeatedly, making them a different workload from constantly changing blockchain state. Older historical data will eventually move away from active nodes into archival storage, allowing nodes to focus their resources on the data needed for real-time operations. The interesting part is how Sei plans to deploy all of this. Instead of shutting down the network and migrating the entire database at once, Eidos is designed to migrate storage while Sei continues producing blocks. The old and new systems can run side by side during the transition, with data moved in batches and integrity checks performed throughout the process. The first phase arrived on Sei mainnet with the v6.6 release in August 2026, beginning the separation of EVM state and introducing improvements to the pruning process. The broader Eidos architecture, including FlatKV, LtHash, the new receipt store and off-node archival storage, is expected to arrive through subsequent releases. Sei’s ultimate Giga target is 200,000 transactions per second. But reaching that kind of execution speed requires more than a faster transaction engine. The blockchain also needs a storage system capable of keeping up. That is essentially what Eidos is trying to build. Giga is not just about making Sei execute transactions faster. It is about rebuilding the infrastructure underneath that speed so the network can actually sustain it.

BSCN

27,310 Aufrufe • vor 28 Tagen

Why Having a Satellite Network is So Important In 2023, the Russians were about to close a deal with a certain North Korean MLRS, but the deal fell through exactly because the North Koreans, +20 years ago, had revolted against Russian opposition to their nuclear program and switched from GLONASS to BeiDou. Only few years ago, the NK returned to Glonass and started converting their equipment to work with dual GNSS guidance. But why did the deal sour? Because the Chinese did not authorize the use of their satellites in the Ukraine conflict. The same problem occurred with the Belarusian POLONEZ MLRS, which uses missiles based on Chinese technology. Today, Iran has switched from GPS to BeiDou, aiming for greater resistance to jammers and integration with Chinese systems. This shows that a missile program is much more than the missiles themselves. It is necessary to have one's own constellation, even if it is strictly military and regionalized, with resources for monitoring and target acquisition, in addition to the ability to deal with jammers and spoofers. When I mentioned Iran and BeiDou, it is the beginning and serves as a gateway that enables integration with Chinese networks, provided the Chinese decide to allow it. However, it is essentially a massive gateway, with numerous smaller, more specialized sub-channels operating underneath. For targeting moving objects, Iran would need to receive data from the Guowang or Yaogan networks. In the last six months, the Chinese could have provided partial integration. At this stage, since the Iranians are conducting their ISR primarily with drones, I believe the Chinese are not sharing data from the LEO satellites in those networks. Iran also has its own satellites, but the Chinese network is far more mature and likely equipped with a wide array of integration and data-sharing tools. While the Chinese are providing intelligence to Iran, I believe they are prudent in doing so to preserve the relationships they have built with other Arab states. At this moment, I believe that the sharing of intelligence from satellites isn’t in real time. For a country like Iran, it is crucial to have GNSS independence with its own program. The same applies to other medium-sized countries, which need at least an LEO constellation capable of providing the minimum ISR, and this is linked to security, but also a series of other factors. I'll give a practical example here. Drones usually lose link with 50% of their range in the Amazon due to weather conditions. With an LEO constellation, this would not occur. Today, to have independence, a constellation project is necessary.
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Why Having a Satellite Network is So Important In 2023, the Russians were about to close a deal with a certain North Korean MLRS, but the deal fell through exactly because the North Koreans, +20 years ago, had revolted against Russian opposition to their nuclear program and switched from GLONASS to BeiDou. Only few years ago, the NK returned to Glonass and started converting their equipment to work with dual GNSS guidance. But why did the deal sour? Because the Chinese did not authorize the use of their satellites in the Ukraine conflict. The same problem occurred with the Belarusian POLONEZ MLRS, which uses missiles based on Chinese technology. Today, Iran has switched from GPS to BeiDou, aiming for greater resistance to jammers and integration with Chinese systems. This shows that a missile program is much more than the missiles themselves. It is necessary to have one's own constellation, even if it is strictly military and regionalized, with resources for monitoring and target acquisition, in addition to the ability to deal with jammers and spoofers. When I mentioned Iran and BeiDou, it is the beginning and serves as a gateway that enables integration with Chinese networks, provided the Chinese decide to allow it. However, it is essentially a massive gateway, with numerous smaller, more specialized sub-channels operating underneath. For targeting moving objects, Iran would need to receive data from the Guowang or Yaogan networks. In the last six months, the Chinese could have provided partial integration. At this stage, since the Iranians are conducting their ISR primarily with drones, I believe the Chinese are not sharing data from the LEO satellites in those networks. Iran also has its own satellites, but the Chinese network is far more mature and likely equipped with a wide array of integration and data-sharing tools. While the Chinese are providing intelligence to Iran, I believe they are prudent in doing so to preserve the relationships they have built with other Arab states. At this moment, I believe that the sharing of intelligence from satellites isn’t in real time. For a country like Iran, it is crucial to have GNSS independence with its own program. The same applies to other medium-sized countries, which need at least an LEO constellation capable of providing the minimum ISR, and this is linked to security, but also a series of other factors. I'll give a practical example here. Drones usually lose link with 50% of their range in the Amazon due to weather conditions. With an LEO constellation, this would not occur. Today, to have independence, a constellation project is necessary.

Patricia Marins

19,508 Aufrufe • vor 7 Monaten

I just built a Claude skill that audits your entire Google Ads account in under 5 minutes 🤯 One prompt → a full account score, wasted spend breakdown, and a prioritized fix list telling you exactly what to change this week. All inside Claude Cowork. Perfect for DTC brands and agencies who are running Google Ads but have no idea how much budget is leaking. If you're managing Google Ads and your "optimization" process is logging in, staring at the dashboard, sorting by cost, and hoping you spot the problem before it costs you another $500... This audit skill finds it for you: → Connects to your live Google Ads data via MCP → Scores your account across 6 dimensions: wasted spend, search term quality, keyword health, quality scores, budget allocation, and creative performance → Calculates your exact wasted spend in dollars — search terms burning budget with zero conversions → Flags quality score issues dragging up your CPCs → Identifies keyword cannibalization across campaigns → Surfaces your top 5 highest-priority fixes ranked by budget impact → Generates a clean audit report you can hand to a client or share with your team No CSV exports. No pivot tables. No guessing where the money went. What you get: → A single Claude skill file you install once → An account health score (0-100) every time you run it → Exact dollar amount of wasted spend identified → Prioritized action list — not "optimize your account," but "pause these 12 search terms and save $847/month" → Works with any Google Ads account connected I'm giving away the full audit skill — the actual .md file you drop into Claude and run against your own account. Want it? Like this post Comment "SKILL" And I'll send it over (must be following so I can DM)
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I just built a Claude skill that audits your entire Google Ads account in under 5 minutes 🤯 One prompt → a full account score, wasted spend breakdown, and a prioritized fix list telling you exactly what to change this week. All inside Claude Cowork. Perfect for DTC brands and agencies who are running Google Ads but have no idea how much budget is leaking. If you're managing Google Ads and your "optimization" process is logging in, staring at the dashboard, sorting by cost, and hoping you spot the problem before it costs you another $500... This audit skill finds it for you: → Connects to your live Google Ads data via MCP → Scores your account across 6 dimensions: wasted spend, search term quality, keyword health, quality scores, budget allocation, and creative performance → Calculates your exact wasted spend in dollars — search terms burning budget with zero conversions → Flags quality score issues dragging up your CPCs → Identifies keyword cannibalization across campaigns → Surfaces your top 5 highest-priority fixes ranked by budget impact → Generates a clean audit report you can hand to a client or share with your team No CSV exports. No pivot tables. No guessing where the money went. What you get: → A single Claude skill file you install once → An account health score (0-100) every time you run it → Exact dollar amount of wasted spend identified → Prioritized action list — not "optimize your account," but "pause these 12 search terms and save $847/month" → Works with any Google Ads account connected I'm giving away the full audit skill — the actual .md file you drop into Claude and run against your own account. Want it? Like this post Comment "SKILL" And I'll send it over (must be following so I can DM)

Mike Futia

60,209 Aufrufe • vor 5 Monaten

Elon Musk is building a data center that no grid has to power and no county has to approve. Musk: “Think of it as a rack of compute in space.” Orbital hardware has always been custom. Each satellite is its own program, its own team, its own decade. SpaceX’s AI1 satellites are copies of each other. Each is built around a single Nvidia NVL72, the same rack-scale architecture running the largest data centers on the ground, redesigned to fly. Space stops being a program and becomes an inventory. Designing for orbit made the rack simpler and cheaper than the ground version, so SpaceX plans to run the space design in terrestrial data centers too. Racks alone have never made a data center. A thousand of them in a building with no network between them is a thousand computers. The interconnect is what turns them into one machine. Training a frontier model means moving enormous volumes of data between processors without pause, and the whole system runs at the speed of its slowest link. That is why the fabric between chips is fought over as hard as the chips themselves. Musk: “And then you can connect these racks of compute to either each other by the laser links, or directly to the Starlink constellation.” Light moves through glass at about two thirds of its speed in a vacuum, and fiber optic cable is glass. Every backbone route and undersea cable on Earth pays that tax. A laser between two satellites pays nothing. Over long distances, an orbital link arrives sooner than the same run in fiber. Orbit was supposed to be a trade, unlimited power in exchange for a worse network. The network is faster. The compute plugs into a delivery layer that is already finished. Thousands of satellites are up there right now carrying laser links, terminating at ground stations and dishes across most of the planet. The last mile was built years before the thing it delivers existed. Anyone else attempting this needs the rocket, the satellite bus, the solar manufacturing, the laser mesh, the ground network, and a supply line to a chipmaker. SpaceX had five of them before the project had a name. None of it was built for this. Starlink existed to sell internet subscriptions. The lasers existed so those subscriptions would work over open ocean. Starship existed for Mars. Nobody planned this. It assembled itself out of problems solved for other reasons. That is what twenty years of hard engineering leaves behind. Every previous expansion of human capability ran on a resource sitting inside somebody’s borders. Coal, oil, water, land. Sunlight in orbit belongs to nobody and never runs out. Compute still has an address. A building in Virginia, a substation, a county that had to approve it, a grid connection someone waited four years for. He is describing a version that only has an altitude.
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Elon Musk is building a data center that no grid has to power and no county has to approve. Musk: “Think of it as a rack of compute in space.” Orbital hardware has always been custom. Each satellite is its own program, its own team, its own decade. SpaceX’s AI1 satellites are copies of each other. Each is built around a single Nvidia NVL72, the same rack-scale architecture running the largest data centers on the ground, redesigned to fly. Space stops being a program and becomes an inventory. Designing for orbit made the rack simpler and cheaper than the ground version, so SpaceX plans to run the space design in terrestrial data centers too. Racks alone have never made a data center. A thousand of them in a building with no network between them is a thousand computers. The interconnect is what turns them into one machine. Training a frontier model means moving enormous volumes of data between processors without pause, and the whole system runs at the speed of its slowest link. That is why the fabric between chips is fought over as hard as the chips themselves. Musk: “And then you can connect these racks of compute to either each other by the laser links, or directly to the Starlink constellation.” Light moves through glass at about two thirds of its speed in a vacuum, and fiber optic cable is glass. Every backbone route and undersea cable on Earth pays that tax. A laser between two satellites pays nothing. Over long distances, an orbital link arrives sooner than the same run in fiber. Orbit was supposed to be a trade, unlimited power in exchange for a worse network. The network is faster. The compute plugs into a delivery layer that is already finished. Thousands of satellites are up there right now carrying laser links, terminating at ground stations and dishes across most of the planet. The last mile was built years before the thing it delivers existed. Anyone else attempting this needs the rocket, the satellite bus, the solar manufacturing, the laser mesh, the ground network, and a supply line to a chipmaker. SpaceX had five of them before the project had a name. None of it was built for this. Starlink existed to sell internet subscriptions. The lasers existed so those subscriptions would work over open ocean. Starship existed for Mars. Nobody planned this. It assembled itself out of problems solved for other reasons. That is what twenty years of hard engineering leaves behind. Every previous expansion of human capability ran on a resource sitting inside somebody’s borders. Coal, oil, water, land. Sunlight in orbit belongs to nobody and never runs out. Compute still has an address. A building in Virginia, a substation, a county that had to approve it, a grid connection someone waited four years for. He is describing a version that only has an altitude.

Dustin

12,888 Aufrufe • vor 21 Tagen

In 2025, demand for blockchain applications with genuine real-world utility has collided with a technical barrier that leaves developers questioning what they can realistically build. Anyone building things like tokenized assets, supply chains, AI agents, or prediction markets still juggle a mess of middleware, and somehow end up spending more time stitching than innovating. How so? Every: - Bridges to move assets, - oracles to fetch data, - indexers to make that data searchable, - relayers and bots to keep everything on schedule— is necessary, but each layer also adds cost, latency, and new risks. The end result is an application that’s expensive to run, fragile under stress, and slower than the Web2 software it’s trying to replace. This is the problem Rialo says it wants to solve. Built by Subzero Labs and backed by $20 million from investors like Pantera Capital and Coinbase Ventures 🛡️, Rialo’s pitch is simple: instead of accepting the middleware tower as an unavoidable cost of doing business, compress it into the base chain itself. But Rialo doesn’t describe itself as another Layer 1, its very name, Rialo Isn’t a Layer One, makes that clear. The team frames it instead as a unified real-world network: a protocol rebuilt from the ground up with the assumption that external connectivity is not an afterthought but a core design principle. To understand what this means, consider how today’s dApps are typically assembled. A typical RWA dApp stack involves: - Oracle providers (Chainlink, Pyth, Band) for asset pricing and event settlement - Bridges (Wormhole, Multichain, custodians) for cross-chain asset movement - Indexers (The Graph, Aleph, Stacks API) for querying and preprocessing chain data - Schedulers/relayers for automated tasks and monitoring - Web2 integrations via cloud services, centralized APIs, and off-chain pipelines Each of these steps adds another vendor, another trust boundary, and another operational layer to monitor. By the time the application is live, it resembles a patchwork of loosely coupled services, each carrying its own risks. You don’t have to look far for proof: - Base went dark for 29-43 minutes in August 2025 when its sequencer misfired, freezing every DeFi app on it. - A few months earlier, an AWS outage rippled through Binance and KuCoin, stalling withdrawals because even “decentralized” systems leaned on centralized middleware. - When Infura has faltered, Ethereum dApps have gone offline in sync, not because Ethereum broke, but because the middleware holding it together did. What should feel like building an application instead feels like maintaining a fragile machine. Rialo architecture embeds the primitives that normally live in middleware directly into the protocol. Smart contracts on Rialo can: - be event-driven, able to respond not just to blockchain state changes but also to external events through built-in webhook and API triggers. - fetch data from the web natively, without relying on external oracles or relayers. - include privacy and identity management—KYC hooks and two-factor authentication, at the protocol level rather than as add-ons. - handle cross-chain communication without wrapped assets or third-party bridges. - run on a virtual machine that is compatible with ecosystems like Solana but extended with RISC-V to support modern programming concepts such as async/await and event loops. If these features work as intended, the implications are significant. Today, much of a team’s energy goes into building and maintaining infrastructure: fullnodes, indexers, monitoring scripts, oracle integrations, relayer logic, bridge infrastructure. Each requires engineering headcount and ongoing maintenance. With Rialo, much of this is absorbed by the protocol, freeing developers to concentrate on business logic. Projects can deliver production-grade dApps with smaller, leaner groups focused directly on product design and execution. Operational costs also shrink: indexing and oracle services can run into thousands of dollars a month; collapsing those into built-in functions reduces recurring expenses while simplifying onboarding for new developers. But folding middleware into the chain doesn’t erase complexity, it reshapes it. Some of the problems to be encountered include: - Scale and complexity: Rialo’s validators won’t just be securing transactions; they’ll also be securing APIs, cross-chain data, and scheduled triggers. Any failure in one subsystem could ripple across the entire network. - Performance vs. decentralization: Richer indexing, scheduling, and data ingress could make nodes heavier to run, narrowing who can realistically participate as a validator. That risks reducing the decentralization blockchains depend on for resilience. - Governance pressures: Disputes or failures involving real-world data feeds, external APIs, or cross-chain actions will arise more often, requiring not just technical fixes but robust social infrastructure, clear rules for voting, transparent arbitration, and mechanisms for community trust. Without them, Rialo risks re-centralizing decision-making around a handful of operators. Where, then, does this model make the most sense? That would be in sectors where external connectivity is indispensable and middleware bloat has consistently been a blocker: - Real-world assets: settling tokenized securities or commodities against off-chain events. - Supply chains: triggering a payment the moment a shipment clears customs, without relying on a third-party oracle. - Agent systems: AI agents interacting with real-world APIs and on-chain contracts simultaneously. - Real-time markets: prediction markets or insurance contracts that must resolve immediately against external data. For purely on-chain domains like DeFi primitives or NFTs, where composability matters more than external triggers, the advantages may be less pronounced. This shift is familiar to anyone who remembers the rise of Web2 platform services. Just as Heroku and Firebase abstracted away server maintenance so developers could focus on building products, Rialo is betting that a unified real-world network can let blockchain developers do the same. Adoption will ultimately depend on: - whether its protocol primitives mature quickly, - whether the ecosystem builds out SDKs and tooling that make them usable, - whether compliance features can adapt to changing regulations, - and whether governance proves resilient under adversarial conditions. The first applications will be the test case. If they show that Rialo can replace a fragile patchwork of middleware with a secure, auditable, and cost-effective base layer, it could set a new standard for real-world connectivity in blockchains. If not, it risks simply moving complexity from one part of the stack to another. But at a minimum, Rialo has forced the question: should real-world connectivity in blockchains continue to depend on layers of external vendors, or should it be built into the chain itself? That’s the question Rialo has put on the table — and it’s why I got interested in Rialo .
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In 2025, demand for blockchain applications with genuine real-world utility has collided with a technical barrier that leaves developers questioning what they can realistically build. Anyone building things like tokenized assets, supply chains, AI agents, or prediction markets still juggle a mess of middleware, and somehow end up spending more time stitching than innovating. How so? Every: - Bridges to move assets, - oracles to fetch data, - indexers to make that data searchable, - relayers and bots to keep everything on schedule— is necessary, but each layer also adds cost, latency, and new risks. The end result is an application that’s expensive to run, fragile under stress, and slower than the Web2 software it’s trying to replace. This is the problem Rialo says it wants to solve. Built by Subzero Labs and backed by $20 million from investors like Pantera Capital and Coinbase Ventures 🛡️, Rialo’s pitch is simple: instead of accepting the middleware tower as an unavoidable cost of doing business, compress it into the base chain itself. But Rialo doesn’t describe itself as another Layer 1, its very name, Rialo Isn’t a Layer One, makes that clear. The team frames it instead as a unified real-world network: a protocol rebuilt from the ground up with the assumption that external connectivity is not an afterthought but a core design principle. To understand what this means, consider how today’s dApps are typically assembled. A typical RWA dApp stack involves: - Oracle providers (Chainlink, Pyth, Band) for asset pricing and event settlement - Bridges (Wormhole, Multichain, custodians) for cross-chain asset movement - Indexers (The Graph, Aleph, Stacks API) for querying and preprocessing chain data - Schedulers/relayers for automated tasks and monitoring - Web2 integrations via cloud services, centralized APIs, and off-chain pipelines Each of these steps adds another vendor, another trust boundary, and another operational layer to monitor. By the time the application is live, it resembles a patchwork of loosely coupled services, each carrying its own risks. You don’t have to look far for proof: - Base went dark for 29-43 minutes in August 2025 when its sequencer misfired, freezing every DeFi app on it. - A few months earlier, an AWS outage rippled through Binance and KuCoin, stalling withdrawals because even “decentralized” systems leaned on centralized middleware. - When Infura has faltered, Ethereum dApps have gone offline in sync, not because Ethereum broke, but because the middleware holding it together did. What should feel like building an application instead feels like maintaining a fragile machine. Rialo architecture embeds the primitives that normally live in middleware directly into the protocol. Smart contracts on Rialo can: - be event-driven, able to respond not just to blockchain state changes but also to external events through built-in webhook and API triggers. - fetch data from the web natively, without relying on external oracles or relayers. - include privacy and identity management—KYC hooks and two-factor authentication, at the protocol level rather than as add-ons. - handle cross-chain communication without wrapped assets or third-party bridges. - run on a virtual machine that is compatible with ecosystems like Solana but extended with RISC-V to support modern programming concepts such as async/await and event loops. If these features work as intended, the implications are significant. Today, much of a team’s energy goes into building and maintaining infrastructure: fullnodes, indexers, monitoring scripts, oracle integrations, relayer logic, bridge infrastructure. Each requires engineering headcount and ongoing maintenance. With Rialo, much of this is absorbed by the protocol, freeing developers to concentrate on business logic. Projects can deliver production-grade dApps with smaller, leaner groups focused directly on product design and execution. Operational costs also shrink: indexing and oracle services can run into thousands of dollars a month; collapsing those into built-in functions reduces recurring expenses while simplifying onboarding for new developers. But folding middleware into the chain doesn’t erase complexity, it reshapes it. Some of the problems to be encountered include: - Scale and complexity: Rialo’s validators won’t just be securing transactions; they’ll also be securing APIs, cross-chain data, and scheduled triggers. Any failure in one subsystem could ripple across the entire network. - Performance vs. decentralization: Richer indexing, scheduling, and data ingress could make nodes heavier to run, narrowing who can realistically participate as a validator. That risks reducing the decentralization blockchains depend on for resilience. - Governance pressures: Disputes or failures involving real-world data feeds, external APIs, or cross-chain actions will arise more often, requiring not just technical fixes but robust social infrastructure, clear rules for voting, transparent arbitration, and mechanisms for community trust. Without them, Rialo risks re-centralizing decision-making around a handful of operators. Where, then, does this model make the most sense? That would be in sectors where external connectivity is indispensable and middleware bloat has consistently been a blocker: - Real-world assets: settling tokenized securities or commodities against off-chain events. - Supply chains: triggering a payment the moment a shipment clears customs, without relying on a third-party oracle. - Agent systems: AI agents interacting with real-world APIs and on-chain contracts simultaneously. - Real-time markets: prediction markets or insurance contracts that must resolve immediately against external data. For purely on-chain domains like DeFi primitives or NFTs, where composability matters more than external triggers, the advantages may be less pronounced. This shift is familiar to anyone who remembers the rise of Web2 platform services. Just as Heroku and Firebase abstracted away server maintenance so developers could focus on building products, Rialo is betting that a unified real-world network can let blockchain developers do the same. Adoption will ultimately depend on: - whether its protocol primitives mature quickly, - whether the ecosystem builds out SDKs and tooling that make them usable, - whether compliance features can adapt to changing regulations, - and whether governance proves resilient under adversarial conditions. The first applications will be the test case. If they show that Rialo can replace a fragile patchwork of middleware with a secure, auditable, and cost-effective base layer, it could set a new standard for real-world connectivity in blockchains. If not, it risks simply moving complexity from one part of the stack to another. But at a minimum, Rialo has forced the question: should real-world connectivity in blockchains continue to depend on layers of external vendors, or should it be built into the chain itself? That’s the question Rialo has put on the table — and it’s why I got interested in Rialo .

Jen

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