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Meet Optimize 360: Airwallex’s AI-powered payment optimisation engine for smarter payments, more revenue, and less friction. Across thousands of merchants, Optimize 360 has delivered: ✅ 2% - 3% uplift in payment success rates, with millions in recovered revenue ✅ 3x lower false decline rates than the industry average ✅... show more

Airwallex

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11,720 Aufrufe • vor 8 Monaten •via X (Twitter)

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4 billion payments. 3 trillion data points. One model trained on all of it. Meet Razorpay Vulcan - India’s first transformer-based AI foundation model for payments. Built, trained and hosted in India, in partnership with NVIDIA and Amazon Web Services. Until now, every payments problem was solved separately: routing, fraud, risk, personalisation and more. We asked: What if one model could understand how money moves? And like LLMs are trained on text to understand language, Vulcan is trained on payments to understand how money moves. Already running in beta across 51,000+ businesses, Vulcan is delivering: - 8–10% improvement in payment success rates - the ultimate measure of whether a payment simply works. - 8x more international card fraud detected. - 5x more fraudulent or disputed transactions identified. - 1–2 lakh more purchases completed every month through better checkout personalisation. And we’re just getting started. The best part? Every payment Vulcan sees makes the next one smarter. We’ve spent years building the infrastructure that moves money for India. Now, we’re building the intelligence that understands and improves it. 🔥

4 billion payments. 3 trillion data points. One model trained on all of it. Meet Razorpay Vulcan - India’s first transformer-based AI foundation model for payments. Built, trained and hosted in India, in partnership with NVIDIA and Amazon Web Services. Until now, every payments problem was solved separately: routing, fraud, risk, personalisation and more. We asked: What if one model could understand how money moves? And like LLMs are trained on text to understand language, Vulcan is trained on payments to understand how money moves. Already running in beta across 51,000+ businesses, Vulcan is delivering: - 8–10% improvement in payment success rates - the ultimate measure of whether a payment simply works. - 8x more international card fraud detected. - 5x more fraudulent or disputed transactions identified. - 1–2 lakh more purchases completed every month through better checkout personalisation. And we’re just getting started. The best part? Every payment Vulcan sees makes the next one smarter. We’ve spent years building the infrastructure that moves money for India. Now, we’re building the intelligence that understands and improves it. 🔥

Harshil Mathur

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Today, we’re excited to share a first look at the next chapter for our payments product: Airwallex POS Payments Businesses will be able to unify online and in-store payments on one global platform, powered by Airwallex’s financial infrastructure. A true end-to-end omnichannel experience, built with the same speed, reliability, and global reach our customers expect. Together with Payments for Platforms, this will unlock a world of new opportunities for platforms to build on top of Airwallex's global infrastructure and incorporate POS payments for their customers around the world. Stay tuned. More to come.

Today, we’re excited to share a first look at the next chapter for our payments product: Airwallex POS Payments Businesses will be able to unify online and in-store payments on one global platform, powered by Airwallex’s financial infrastructure. A true end-to-end omnichannel experience, built with the same speed, reliability, and global reach our customers expect. Together with Payments for Platforms, this will unlock a world of new opportunities for platforms to build on top of Airwallex's global infrastructure and incorporate POS payments for their customers around the world. Stay tuned. More to come.

Airwallex

64,943 Aufrufe • vor 8 Monaten

The average Shopify store loses 1-2% of Black Friday Cyber Monday revenue to chargebacks. For a $500K weekend, that's $10K you'll never see again. You’ll see your biggest revenue spike in November → and wake up in January to refund abuse, chargebacks, and “friendly fraud” wiping out your profits. It’s not always hackers. Sometimes it’s your own customers clicking “dispute” instead of “return.” That’s digital shoplifting. Chargeflow is the world’s first fully automated chargeback and fraud prevention platform → trusted by 15,000+ merchants worldwide. It uses AI and real merchant data to stop fraud before it happens → and recover lost revenue automatically when it does. While most tools stop at payment detection → Chargeflow protects what happens after the transaction too. The result → up to 90% fraud reduction, less than 0.1% false positives, and millions recovered for eCommerce brands. And for BFCM 2025 → they’re giving away something huge: → $10,000 in FREE Chargeback Automation credits. → Chargeflow Prevent FREE until December 31st, 2025. This is the only time of year merchants can protect their entire BFCM season at zero cost. Sell more → stress less → and let Chargeflow handle the chaos that comes after the sales rush.

The average Shopify store loses 1-2% of Black Friday Cyber Monday revenue to chargebacks. For a $500K weekend, that's $10K you'll never see again. You’ll see your biggest revenue spike in November → and wake up in January to refund abuse, chargebacks, and “friendly fraud” wiping out your profits. It’s not always hackers. Sometimes it’s your own customers clicking “dispute” instead of “return.” That’s digital shoplifting. Chargeflow is the world’s first fully automated chargeback and fraud prevention platform → trusted by 15,000+ merchants worldwide. It uses AI and real merchant data to stop fraud before it happens → and recover lost revenue automatically when it does. While most tools stop at payment detection → Chargeflow protects what happens after the transaction too. The result → up to 90% fraud reduction, less than 0.1% false positives, and millions recovered for eCommerce brands. And for BFCM 2025 → they’re giving away something huge: → $10,000 in FREE Chargeback Automation credits. → Chargeflow Prevent FREE until December 31st, 2025. This is the only time of year merchants can protect their entire BFCM season at zero cost. Sell more → stress less → and let Chargeflow handle the chaos that comes after the sales rush.

Jaynit Makwana

23,639 Aufrufe • vor 9 Monaten

Meet Airi: a consumer wallet, built directly into Airwallex Payments. Early merchants are already seeing up to 14% higher conversion and 3x faster checkout with no extra cost or setup required. Live now globally with agent-led checkout coming soon.

Meet Airi: a consumer wallet, built directly into Airwallex Payments. Early merchants are already seeing up to 14% higher conversion and 3x faster checkout with no extra cost or setup required. Live now globally with agent-led checkout coming soon.

Airwallex

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When you’ve worked behind the scenes at major events, you see what the audience doesn’t. Outdated systems that can’t keep up with the scale. Slow, manual processes that drain resources. Missed opportunities to connect with people in real time. I saw it all - and I knew it could be better. That’s why, together with Bogdan Radulescu, we built Rhuna. Since launch, we’ve powered 165+ large-scale events across Europe and the Middle East - concerts, sports, festivals, conferences - processing over $90M in transactions and serving millions of attendees. But we’re not stopping there. Now we’re adding a new layer to the mission - AI-driven infrastructure that touches every part of the event experience. From streamlining operations, to unlocking new revenue for organizers, to delivering faster, smarter, more personal experiences for fans. And with our collaboration with Aptos, we’re embedding instant, borderless blockchain settlements right into the heart of that system - eliminating payment delays, removing unnecessary fees, and making every transaction transparent and secure. This is more than an upgrade - it’s the start of a new standard for how live events operate.

When you’ve worked behind the scenes at major events, you see what the audience doesn’t. Outdated systems that can’t keep up with the scale. Slow, manual processes that drain resources. Missed opportunities to connect with people in real time. I saw it all - and I knew it could be better. That’s why, together with Bogdan Radulescu, we built Rhuna. Since launch, we’ve powered 165+ large-scale events across Europe and the Middle East - concerts, sports, festivals, conferences - processing over $90M in transactions and serving millions of attendees. But we’re not stopping there. Now we’re adding a new layer to the mission - AI-driven infrastructure that touches every part of the event experience. From streamlining operations, to unlocking new revenue for organizers, to delivering faster, smarter, more personal experiences for fans. And with our collaboration with Aptos, we’re embedding instant, borderless blockchain settlements right into the heart of that system - eliminating payment delays, removing unnecessary fees, and making every transaction transparent and secure. This is more than an upgrade - it’s the start of a new standard for how live events operate.

Sveat

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

Tekkaus® | InterLink • MOD • T2 Community Builder

10,912 Aufrufe • vor 1 Monat

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."

Molly O’Shea

12,816 Aufrufe • vor 1 Monat

A team tested Pi0, Pi0 Fast, Gr00t, and ACT on real robot arms in manufacturing tasks. (🔖 Bookmark this for later!) The task was precise: place thin rectangular frames from a messy stack into a holder. The team fine-tuned each model on 100 real trajectories and compared training time, inference speed, motion quality, and success rates. ⬇️ Here’s a breakdown of what they found Pi0 (Original) ✅ Strongest overall performance in precise pick-and-place ✅ High success rate even in edge cases ✅ Longest training time (~11 hours, ~$30 per run) ✅ Inference time of 80 ms causes short pauses between actions Despite delays, it handles complex scenarios well… solid for high-precision tasks, but slow to train. Gr00t ✅ Trains fast (~2 hours, ~$5 per run) ✅ Performs almost as well as Pi0 on large-object tasks ✅ Struggles with fine precision; random movement in some trials ✅ More training didn’t fix jitter or random offsets Best suited for tasks where exact precision isn’t critical. Not ready for manufacturing-grade accuracy without more tuning. Pi0 Fast ✅ Promised faster training, but results were underwhelming ✅ Training at 6 hours still showed low success rates ✅ Inference was slower than expected ✅ Not reliable for generalizing even slightly new tasks Currently too unstable for real-world deployment. Doesn’t live up to the “Fast” name yet. ACT (Baseline) ✅ 200MB model—lightweight, but limited ✅ Struggles with stacked objects or ambiguous scenes ✅ Success rates around 70% in best-case setups ✅ Can’t match newer models on precision or generalization Still a solid baseline, but clearly a generation behind in robustness. 🚨 Extra Notes All newer models share a common issue: •Inference takes longer than a frame (80 ms vs 33 ms), so robots “pause” between chunks. •This results in jittery movements, but not a dealbreaker unless tasks are time-sensitive. Language-conditioned tasks also fell short: after training on two labeled tasks, the model couldn’t generalize to a third unseen combination using only text prompts. ✅ The good news? These models adapt well to new robot arms with quick fine-tuning. ❌ The bad news? There’s still no plug-and-play solution for improving performance after deployment. Reinforcement learning or DAgger-style data collection during real-world operation may be the next big step, something many teams in robotics are actively working on.

A team tested Pi0, Pi0 Fast, Gr00t, and ACT on real robot arms in manufacturing tasks. (🔖 Bookmark this for later!) The task was precise: place thin rectangular frames from a messy stack into a holder. The team fine-tuned each model on 100 real trajectories and compared training time, inference speed, motion quality, and success rates. ⬇️ Here’s a breakdown of what they found Pi0 (Original) ✅ Strongest overall performance in precise pick-and-place ✅ High success rate even in edge cases ✅ Longest training time (~11 hours, ~$30 per run) ✅ Inference time of 80 ms causes short pauses between actions Despite delays, it handles complex scenarios well… solid for high-precision tasks, but slow to train. Gr00t ✅ Trains fast (~2 hours, ~$5 per run) ✅ Performs almost as well as Pi0 on large-object tasks ✅ Struggles with fine precision; random movement in some trials ✅ More training didn’t fix jitter or random offsets Best suited for tasks where exact precision isn’t critical. Not ready for manufacturing-grade accuracy without more tuning. Pi0 Fast ✅ Promised faster training, but results were underwhelming ✅ Training at 6 hours still showed low success rates ✅ Inference was slower than expected ✅ Not reliable for generalizing even slightly new tasks Currently too unstable for real-world deployment. Doesn’t live up to the “Fast” name yet. ACT (Baseline) ✅ 200MB model—lightweight, but limited ✅ Struggles with stacked objects or ambiguous scenes ✅ Success rates around 70% in best-case setups ✅ Can’t match newer models on precision or generalization Still a solid baseline, but clearly a generation behind in robustness. 🚨 Extra Notes All newer models share a common issue: •Inference takes longer than a frame (80 ms vs 33 ms), so robots “pause” between chunks. •This results in jittery movements, but not a dealbreaker unless tasks are time-sensitive. Language-conditioned tasks also fell short: after training on two labeled tasks, the model couldn’t generalize to a third unseen combination using only text prompts. ✅ The good news? These models adapt well to new robot arms with quick fine-tuning. ❌ The bad news? There’s still no plug-and-play solution for improving performance after deployment. Reinforcement learning or DAgger-style data collection during real-world operation may be the next big step, something many teams in robotics are actively working on.

Ilir Aliu

21,844 Aufrufe • vor 1 Jahr

In 2026, I expect we’ll see the birth of the first AI-native university. Over the past several years, universities have dabbled in AI-enabled grading, tutoring, and scheduling. But what’s emerging now is deeper, an adaptive academic organism that learns and optimizes itself in real time. Picture an institution where courses, advising, research collaboration, and even building operations continuously adapt based on data feedback loops. Schedules optimize themselves. Reading lists evolve nightly and rewrite themselves as new research appears. Learning paths shift in real time to meet each student’s pace and context. We’re already seeing precursors. ASU’s campus-wide partnership with OpenAI produced hundreds of AI-driven projects across teaching and administration. SUNY now embeds AI literacy into its general education requirements. These are the building blocks for more foundational deployment. In the AI-native university, professors become architects of learning, curating data, tuning models, and teaching students how to interrogate machine reasoning Assessment shifts, too. Detection tools and plagiarism bans give way to AI-aware evaluation, grading students on how they use AI, not whether they used it. Transparency and tactful application replaces prohibition. And as every industry struggles to hire people who can design, govern, and collaborate with AI systems, this new university becomes the training ground, producing graduates fluent in orchestration who help augment a rapidly shifting workforce. This AI-native university will become the talent engine for a new economy. Do you think an AI native university will arise in 2026? Leave your thoughts in the comments.

In 2026, I expect we’ll see the birth of the first AI-native university. Over the past several years, universities have dabbled in AI-enabled grading, tutoring, and scheduling. But what’s emerging now is deeper, an adaptive academic organism that learns and optimizes itself in real time. Picture an institution where courses, advising, research collaboration, and even building operations continuously adapt based on data feedback loops. Schedules optimize themselves. Reading lists evolve nightly and rewrite themselves as new research appears. Learning paths shift in real time to meet each student’s pace and context. We’re already seeing precursors. ASU’s campus-wide partnership with OpenAI produced hundreds of AI-driven projects across teaching and administration. SUNY now embeds AI literacy into its general education requirements. These are the building blocks for more foundational deployment. In the AI-native university, professors become architects of learning, curating data, tuning models, and teaching students how to interrogate machine reasoning Assessment shifts, too. Detection tools and plagiarism bans give way to AI-aware evaluation, grading students on how they use AI, not whether they used it. Transparency and tactful application replaces prohibition. And as every industry struggles to hire people who can design, govern, and collaborate with AI systems, this new university becomes the training ground, producing graduates fluent in orchestration who help augment a rapidly shifting workforce. This AI-native university will become the talent engine for a new economy. Do you think an AI native university will arise in 2026? Leave your thoughts in the comments.

Emily Bennett

37,976 Aufrufe • vor 8 Monaten

🚀 The Future of Web3 Commerce is Here 🔥 We’re not just launching a new site—we’re laying the foundation for the next evolution of on-chain e-commerce. Here’s how brands, affiliates, and communities can win with Uni-Fy 1️⃣ For Brands: Your On-Chain Sales Engine Your Brand Page is now a powerful e-commerce hub built to: ✅ Showcase your brand with stunning hero sections ✅ Feature & prioritize products for max conversions ✅ Seamlessly sell on-chain with optimized checkout 💡 Your audience. Your products. Your sales. Simplified. 2️⃣ For Affiliates: Earn Like Never Before We’ve eliminated the guesswork so you can monetize effortlessly: ✅ Automated affiliate tracking—no more lost referrals ✅ Commissions on every sale from top-tier Web3 brands ✅ Real-time dashboards to track & optimize earnings 💰 More trust. More transparency. More profits. 3️⃣ For Communities: Turn Engagement into Revenue Your audience deserves real value—now you can give it to them while getting paid: ✅ Curate & promote premium Web3 brands ✅ Earn passively with seamless referral integration ✅ On-chain verification = full transparency & trust 🎯 Monetize authentically. Grow organically. 4️⃣ Early Access Starts NOW Register Today (link in bio) ⚡ Brand Partners get first dibs—update your assets & get ahead ⚡ The biggest marketing push yet is coming—be ready ⚡ Public launch next week—but early adopters win BIG This isn’t just a platform—it’s a movement. Are you ready to lead the next wave of Web3 commerce? 🚀 #UniFy #Web3Commerce

Uni-Fy

17,513 Aufrufe • vor 1 Jahr

Four AI agents just replaced my $250,000 marketing team. I'm not talking about basic chatbots. I'm talking about AI systems that: → Write custom newsletters like Morning Brew → Generate viral social content (3.9M views on one post) → Steal competitor's best-performing ads and rebuild them → Create SEO content that ranks on page 1 of Google All running 24/7 without sick days, vacation requests, or performance reviews. The problem? Most businesses are still hiring expensive marketing teams when AI can now handle 90% of the workload for less than the cost of one employee. I've been testing this for 6 months. The results are wild: ✅ Millions of impressions generated monthly ✅ Tens of thousands in revenue on autopilot ✅ Content creation at enterprise scale ✅ Zero manual research or writing These four agents handle content research, creation, paid advertising creative, and SEO content - work that typically requires a 5-7 person marketing team. The businesses adopting AI marketing agents like these will have an insurmountable advantage while everyone else is still hiring expensive teams and dealing with human limitations. Want the exact n8n templates for all four agents? 1. Like & RT this post 2. Follow me for more AI automation breakdowns 3. Comment "AGENTS" below I'll send you the complete system for free, plus access to my YouTube tutorials showing the step-by-step builds.

Four AI agents just replaced my $250,000 marketing team. I'm not talking about basic chatbots. I'm talking about AI systems that: → Write custom newsletters like Morning Brew → Generate viral social content (3.9M views on one post) → Steal competitor's best-performing ads and rebuild them → Create SEO content that ranks on page 1 of Google All running 24/7 without sick days, vacation requests, or performance reviews. The problem? Most businesses are still hiring expensive marketing teams when AI can now handle 90% of the workload for less than the cost of one employee. I've been testing this for 6 months. The results are wild: ✅ Millions of impressions generated monthly ✅ Tens of thousands in revenue on autopilot ✅ Content creation at enterprise scale ✅ Zero manual research or writing These four agents handle content research, creation, paid advertising creative, and SEO content - work that typically requires a 5-7 person marketing team. The businesses adopting AI marketing agents like these will have an insurmountable advantage while everyone else is still hiring expensive teams and dealing with human limitations. Want the exact n8n templates for all four agents? 1. Like & RT this post 2. Follow me for more AI automation breakdowns 3. Comment "AGENTS" below I'll send you the complete system for free, plus access to my YouTube tutorials showing the step-by-step builds.

David Roberts

109,408 Aufrufe • vor 10 Monaten

I thought AEO (read: SEO for LLMs) was a hunk of bullsh*t. And then i spoke to KippBodnar.eth, CMO of HubSpot, who knocked the skepticism out of me. His first jab: In one year, they grew AI search traffic by 15x. It went from rounding error to real line item on the P&L. His second jab: AI search conversion rates are 5x higher than Google search. On some queries, 13x higher. His hook: 60% of AI citations don't come from the top 20 Google results. The companies dominating Google aren't automatically winning in AI search, which creates a huge advantage for early adopters. He then took me through his process for crushing AEO & seeing results in days, not months (like SEO): 1) Grade: your current AEO presence across ChatGPT, Perplexity, and Gemini with a tool like Hubspot's AEO grader. 2) Restructure: your content into chunked, answer-first pages with natural language headers. - one consolidated page, not 8-10 interlinked pages - lead with natural language questions like "What is X?" - 1-2 paragraph sections, not 1,000 word sections - table of contents on a single page 3) Separate: Mentions from citations and optimize differently for each - Mention = when AI references your brand or product in its answer but doesn't link to you - Citation = when an AI references you AND links to your page 4) Open up: your information — ungate content, build Reddit presence, make pricing public - Optimize for entity understanding: how well do AI models understand what your company does, based on every signal from Reddit to review sites, awards lists to help docs 5) Tool up: with AEO-specific software to track prompts and share of voice - Check out Xfunnel or Limey[.]ai 6) Rethink attribution: measure source of customers, not source of traffic. - Metrics that matter: share of voice, citation count, sentiment, mention frequency, source of customers not traffic

Alex Lieberman

98,635 Aufrufe • vor 6 Monaten

CORN SEASON is Here And it’s all about one thing: Growing $CORN 🌽 🟠 Bitcoin? Pumping. 🐸 Memecoins? Printing. 💰Your bags? Starving. Enter $CORN: a cross-ecosystem token built to fuel BTCFi and so much more. It’s planting roots across the industry, not just as another token, but as a movement: a meme-powered asset that moves with culture, lives across ecosystems, and sticks in people’s heads (and wallets). Growing $CORN means one thing: ubiquity. We’re not just increasing access ➡️ we’re cultivating presence everywhere users already are. The mission is simple: Get $CORN into as many hands as possible. Reduce friction at every step. Show up wherever users already are. That means: → More listings → More wallets → More integrations → Better UX → Global reach → Frictionless access Where can you get $CORN right now? ✅ Bybit – for the high-volume click traders ✅ Oku – for onchain purists with taste We’re planting $CORN where it’ll grow fast, and there’s a lot more soil to cover. Partnerships? Oh yeah. We’re seeding those too. Across chains. Across wallets. Across verticals. Each new integration adds surface area. Each new platform is a distribution node. Each new holder makes the brand stickier. This isn’t growth for growth’s sake, it’s ecosystem construction. What’s next? 🚜 More integrations 💧 More liquidity 💡 More ways to earn, trade, and hold 🌎 More people touching $CORN for the first time Corn Season isn’t just a meme, it’s a strategy, a movement, a purpose and a brand. Stay ready, stay corny, LETS GROW 🌽

CORN

15,123 Aufrufe • vor 1 Jahr

🚨Alpha Alert🚨$DEEPAI @DeepWhalesAI Your Crypto Trading War Chest (and Superpower!) Still sitting at less than 1.5 million dollars market cap, $DEEPAI has an awesome dev team, a great community, and some fabulous utilities. Check out why I am bullish on this gem 👇👇👇 🐋 Deep Whales AI is your battle-tested arsenal for CRYPTO DOMINATION. 💎 Your Crystal Ball for Crypto: 🐋 Deep Whales AI Bot: AI-powered trade alerts, seamless buying/selling, streamlined trading – ALL IN ONE. 🐋 Pulse Tracker: Spots dormant projects primed for EXPLOSIVE breakouts. 🐋 AI Trader Bot: Mimic top traders' strategies like a guru! 🐋 Blue Whale Alert Bot (NEW!): Early buy alerts – LIGHTYEARS ahead. Tiered system for flawless execution with the Deep Whales AI Bot. 🐋 SecureScan AI: AI guardian sniffing out malicious contract code. Sleep easy. 🐋 Portfolio Manager: Total control of your crypto empire. Track, analyze, OPTIMIZE. 🏆 Exclusive Access: Become a Crypto Whale! Limited edition Deep Whales AI NFTs (1-50) grant VIP access AND a 1.5x revenue share boost in our ecosystem. 🚀 Deep Whales AI VC Startup Fund: Fueling the Future Passionate about crypto innovation? Apply for a grant and turn your vision into reality. 💪 Deep Minke Whales Premium Service: Unleash Your Inner Jedi Hold 0.1% of our token? This power tool is YOURS, FREE. Not there yet? Monthly fee access, but why settle? Real-time alerts, trade execution, market domination – ALL FROM YOUR PHONE. The market waits for no one... except maybe for those with Deep Whales AI on their side. 😉 Check out the chart: Potential price target: 1B+ MCAP this bull run, as long as the team continues to build! #DeepWhalesAI #DEEPAI #AI #SmallCapGem #LadyTraderRa #TopPicks

🚨Alpha Alert🚨$DEEPAI @DeepWhalesAI Your Crypto Trading War Chest (and Superpower!) Still sitting at less than 1.5 million dollars market cap, $DEEPAI has an awesome dev team, a great community, and some fabulous utilities. Check out why I am bullish on this gem 👇👇👇 🐋 Deep Whales AI is your battle-tested arsenal for CRYPTO DOMINATION. 💎 Your Crystal Ball for Crypto: 🐋 Deep Whales AI Bot: AI-powered trade alerts, seamless buying/selling, streamlined trading – ALL IN ONE. 🐋 Pulse Tracker: Spots dormant projects primed for EXPLOSIVE breakouts. 🐋 AI Trader Bot: Mimic top traders' strategies like a guru! 🐋 Blue Whale Alert Bot (NEW!): Early buy alerts – LIGHTYEARS ahead. Tiered system for flawless execution with the Deep Whales AI Bot. 🐋 SecureScan AI: AI guardian sniffing out malicious contract code. Sleep easy. 🐋 Portfolio Manager: Total control of your crypto empire. Track, analyze, OPTIMIZE. 🏆 Exclusive Access: Become a Crypto Whale! Limited edition Deep Whales AI NFTs (1-50) grant VIP access AND a 1.5x revenue share boost in our ecosystem. 🚀 Deep Whales AI VC Startup Fund: Fueling the Future Passionate about crypto innovation? Apply for a grant and turn your vision into reality. 💪 Deep Minke Whales Premium Service: Unleash Your Inner Jedi Hold 0.1% of our token? This power tool is YOURS, FREE. Not there yet? Monthly fee access, but why settle? Real-time alerts, trade execution, market domination – ALL FROM YOUR PHONE. The market waits for no one... except maybe for those with Deep Whales AI on their side. 😉 Check out the chart: Potential price target: 1B+ MCAP this bull run, as long as the team continues to build! #DeepWhalesAI #DEEPAI #AI #SmallCapGem #LadyTraderRa #TopPicks

LadyTraderRa

172,214 Aufrufe • vor 2 Jahren

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Alex Ratner

495,851 Aufrufe • vor 1 Jahr

Microsoft canceling its internal Claude Code licenses this week likely has almost nothing to do with AI costs becoming untenable. Microsoft's own statement says Claude models remain accessible through Copilot CLI and Anthropic's Claude still runs inside Microsoft 365. The real story is that Microsoft's own product (GitHub Copilot) was being embarrassed by a competitor internally this is a platform strategy play, not a cost crisis call. And the post assumes token prices are rising and unsustainable but the actual data goes the other way. As Sam Altman said, a hard reasoning problem that cost X on the OpenAI API 18 months ago now costs 1,000x less. 1,000x in 18 months is just that doesn't happen very often. His stated mission is to relentlessly drive the cost of intelligence down as close to zero as possible and make it a low-cost asset available to the world. A16z separately documented a 10x cost decline per year for equivalent model performance and Nvidia's Blackwell platform delivered 4x to 10x inference cost reductions in production deployments in early 2026. Yes, Uber burned through its 2026 AI budget in four months. But look at why, 95% of engineers were using AI tools monthly, ~70% of committed code was AI-generated, and 11% of real-time backend updates were made autonomously by agents with zero human intervention. That's not an AI cost problem. That's a CFO who budgeted for a pilot and got a revolution. Also, this post ignores the Jevons Paradox, when a resource gets cheaper, total consumption rises, not falls. Tokens inferenced on platforms like OpenRouter grew 25-fold since December 2024, OpenAI’s revenue grew at roughly a 250% annual rate to around a $20B run rate, while Anthropic’s surged from roughly $9B to over $30B in just a few months. Those aren't the numbers of companies whose economics are imploding. Even Gartner projects inference on a 1-trillion parameter model will cost 90%+ less by 2030. The actual Gartner warning is that agentic AI costs more per task because agents run longer chains, that's a design and scoping problem, not a structural industry collapse.

Microsoft canceling its internal Claude Code licenses this week likely has almost nothing to do with AI costs becoming untenable. Microsoft's own statement says Claude models remain accessible through Copilot CLI and Anthropic's Claude still runs inside Microsoft 365. The real story is that Microsoft's own product (GitHub Copilot) was being embarrassed by a competitor internally this is a platform strategy play, not a cost crisis call. And the post assumes token prices are rising and unsustainable but the actual data goes the other way. As Sam Altman said, a hard reasoning problem that cost X on the OpenAI API 18 months ago now costs 1,000x less. 1,000x in 18 months is just that doesn't happen very often. His stated mission is to relentlessly drive the cost of intelligence down as close to zero as possible and make it a low-cost asset available to the world. A16z separately documented a 10x cost decline per year for equivalent model performance and Nvidia's Blackwell platform delivered 4x to 10x inference cost reductions in production deployments in early 2026. Yes, Uber burned through its 2026 AI budget in four months. But look at why, 95% of engineers were using AI tools monthly, ~70% of committed code was AI-generated, and 11% of real-time backend updates were made autonomously by agents with zero human intervention. That's not an AI cost problem. That's a CFO who budgeted for a pilot and got a revolution. Also, this post ignores the Jevons Paradox, when a resource gets cheaper, total consumption rises, not falls. Tokens inferenced on platforms like OpenRouter grew 25-fold since December 2024, OpenAI’s revenue grew at roughly a 250% annual rate to around a $20B run rate, while Anthropic’s surged from roughly $9B to over $30B in just a few months. Those aren't the numbers of companies whose economics are imploding. Even Gartner projects inference on a 1-trillion parameter model will cost 90%+ less by 2030. The actual Gartner warning is that agentic AI costs more per task because agents run longer chains, that's a design and scoping problem, not a structural industry collapse.

Milk Road AI

251,150 Aufrufe • vor 2 Monaten