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📊 Master the TEXTSPLIT Function in Excel Still separating text manually? The TEXTSPLIT function lets you split text into multiple columns or rows instantly using a delimiter such as commas, spaces, hyphens, or other characters. Why TEXTSPLIT is Useful ✅ Clean messy datasets faster ✅ Separate names, emails, and... show more

Tips Excel

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18,005 次观看 • 2 个月前 •via X (Twitter)

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🚀 Stop Merging Data Manually in Excel! 📊 😫 Still copying and pasting data from multiple tables? There’s a smarter way. ⚡ Excel’s Consolidate feature lets you combine data from multiple ranges into a single summary in just a few clicks—saving time and reducing errors. ✅ Merge data faster ✅ Eliminate repetitive manual work ✅ Improve accuracy and productivity ✅ Perfect for reports, budgeting, and data analysis 💡 Small Excel tricks like this can save you hours over the course of a year. 📌 Save this post so you don’t forget it when working with spreadsheets! ❤️ Like • 🔄 Repost • 💬 Share with someone who still copies and pastes data manually.

🚀 Stop Merging Data Manually in Excel! 📊 😫 Still copying and pasting data from multiple tables? There’s a smarter way. ⚡ Excel’s Consolidate feature lets you combine data from multiple ranges into a single summary in just a few clicks—saving time and reducing errors. ✅ Merge data faster ✅ Eliminate repetitive manual work ✅ Improve accuracy and productivity ✅ Perfect for reports, budgeting, and data analysis 💡 Small Excel tricks like this can save you hours over the course of a year. 📌 Save this post so you don’t forget it when working with spreadsheets! ❤️ Like • 🔄 Repost • 💬 Share with someone who still copies and pastes data manually.

Tips Excel

558,039 次观看 • 2 个月前

🚀Napkin AI visuals just got better! We’ve launched Elastic Designs to help you get the right visual, faster. Now your visuals: ✅ Scale automatically with your content – during both generation and editing – so they always look polished without manual fixes ✅ Support more elements than ever, so none of your content gets dropped-off ✅ Instantly update with one-click Visual-Text sync when you change your text – no need to regenerate This is a big step toward making visual generation effortless – so you spend less time tweaking visuals and get to the right one faster. #NapkinAI #VisualAI #AITools #ElasticDesigns #NewFeatures

🚀Napkin AI visuals just got better! We’ve launched Elastic Designs to help you get the right visual, faster. Now your visuals: ✅ Scale automatically with your content – during both generation and editing – so they always look polished without manual fixes ✅ Support more elements than ever, so none of your content gets dropped-off ✅ Instantly update with one-click Visual-Text sync when you change your text – no need to regenerate This is a big step toward making visual generation effortless – so you spend less time tweaking visuals and get to the right one faster. #NapkinAI #VisualAI #AITools #ElasticDesigns #NewFeatures

Napkin AI

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💥Simple guide on Billions Network "First AI Agent Rewards" 🤔Only name indicates rewards ⚠️Not sure if there will be any rewards actually ⚠️As major CEX is involved, they may not allow rewards ⚠️Try as it is free, with no expectations ✅If u followed my previous guide for AI Agent, we did it on GitHub ⚠️So mostly our codespace would be terminated ✅So in this guide, we will set up from scratch, link new agent and install skill 🔗 ✅Download text file with all commands 🔗 ✅Login to GitHub ✅Open a blank codespace ✅Open downloaded text file ✅Just copy paste commands one by one ✅After 6th command u will get a link ✅Ctrl + click that link or copy paste link in browser ✅Login using same Billions Network login u used ✅Click verify ✅Now this new agent is linked to ur profile ✅Run 7th command ✅Type 'y' ✅Run 8th command ✅Type 'y' ✅Just click enter when some options r shown 💥Done 💙Like 🔁RT

CryptoTelugu

44,385 次观看 • 3 个月前

💥Simple guide on Billions Network AI Agent & 2000 points 💰Funding -$30M 💯FREE 👇Steps 🔗 ✅Login ✅If already did sign up based on my previous guide, login with same email or wallet 📝U can earn 2000 power points if u create & link AI agent 👇Simple steps 🔗 ✅Download this text file with commands 🔗 ✅Login to GitHub ✅Open a blank codespace ✅Open downloaded text file ✅Just copy paste commands one by one ✅After last command u will get a link ✅Ctrl + click that link or copy paste link in browser ✅Login using same Billions Network login u used ✅Click verify 💥Done 🪙U can see 2000 points in your profile 😁Recently $BILL tokenomics was released 🪙Total supply - 10B 🪙TGE supply - 2.4B 🪙Community & Airdrop - 4B 📈 $BILL listing on Coinbase 🛡️ is also confirmed 🤷As it is free & nothing else to do, try this task 😉Let's hope for the best 💙Like 🔁RT

CryptoTelugu

132,992 次观看 • 4 个月前

Full article capture to Notion on iPhone! This is a super early look at Flylighter on iOS. My team got this initial test build of the app up and running in a single month. Absolutely incredible. Next steps: ✅ Speed upgrades ✅ More capture modes - text highlights, voice recordings ✅ Capture history (so you can send a highlight to a previously captured page) Soon, you’ll have a full set of tools for capturing any idea or resource you find to Notion, instantly. Less friction = more action 💪

Full article capture to Notion on iPhone! This is a super early look at Flylighter on iOS. My team got this initial test build of the app up and running in a single month. Absolutely incredible. Next steps: ✅ Speed upgrades ✅ More capture modes - text highlights, voice recordings ✅ Capture history (so you can send a highlight to a previously captured page) Soon, you’ll have a full set of tools for capturing any idea or resource you find to Notion, instantly. Less friction = more action 💪

Thomas Frank

20,760 次观看 • 2 年前

🚀 Meet KaneAI TestMu AI the next-generation AI-powered testing assistant for modern QA teams. KaneAI helps teams plan, author, and evolve end-to-end tests using natural language, turning requirements directly into executable code. Built for enterprise-scale complexity, it handles sophisticated workflows across all major programming languages and frameworks. QA teams often face hurdles like rapid development cycles, test case debt, and complex framework management. KaneAI addresses these challenges by: ✅ Generating structured test cases from text, JIRA, PDFs, images, audio, video, or spreadsheets ✅ Enabling complex testing workflows with natural language ✅ Supporting multi-language code exports and deep integrations with JIRA and GitHub ✅ Automating API and database testing, smart versioning, and auto bug detection ✅ Self-healing tests for UI changes and flexible manual interaction KaneAI augments QA teams, boosting productivity, reducing errors, and helping teams focus on outcomes rather than repetitive tasks. Learn more about KaneAI here: Connect with TestMu AI : LinkedIn: Twitter: #QA #TestAutomation #AI #GenAI #KaneAI #TestMu

🚀 Meet KaneAI TestMu AI the next-generation AI-powered testing assistant for modern QA teams. KaneAI helps teams plan, author, and evolve end-to-end tests using natural language, turning requirements directly into executable code. Built for enterprise-scale complexity, it handles sophisticated workflows across all major programming languages and frameworks. QA teams often face hurdles like rapid development cycles, test case debt, and complex framework management. KaneAI addresses these challenges by: ✅ Generating structured test cases from text, JIRA, PDFs, images, audio, video, or spreadsheets ✅ Enabling complex testing workflows with natural language ✅ Supporting multi-language code exports and deep integrations with JIRA and GitHub ✅ Automating API and database testing, smart versioning, and auto bug detection ✅ Self-healing tests for UI changes and flexible manual interaction KaneAI augments QA teams, boosting productivity, reducing errors, and helping teams focus on outcomes rather than repetitive tasks. Learn more about KaneAI here: Connect with TestMu AI : LinkedIn: Twitter: #QA #TestAutomation #AI #GenAI #KaneAI #TestMu

Mohini Shewale

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💥 A 450M model just beat bigger VLAs on real robot tasks, and it’s 100% open source [📍 bookmark for later] Came across SmolVLA, a new vision-language-action model for robotics that’s compact, fast, and trained entirely on open community datasets from LeRobot via Hugging Face. What stood out to me is how it matches or outperforms much larger models like ACT using noisy, real-world community data instead of giant private datasets. Why it’s worth a look ✅ 26% performance boost from pretraining on open-source data ✅ Runs on consumer hardware, even a MacBook ✅ 30% faster responses with async inference and smart architecture tweaks ✅ Strong results across Meta-World, LIBERO, SO100, and SO101 ✅ Fully open source: weights, code, training pipeline, eval stack They also introduced smart efficiency tricks like using fewer visual tokens, pulling outputs from mid-layer, and separating perception from action to make it all run fast. SmolVLA is a strong case for what can happen when the robotics community shares data and builds in the open. Definitely worth keeping an eye on.

💥 A 450M model just beat bigger VLAs on real robot tasks, and it’s 100% open source [📍 bookmark for later] Came across SmolVLA, a new vision-language-action model for robotics that’s compact, fast, and trained entirely on open community datasets from LeRobot via Hugging Face. What stood out to me is how it matches or outperforms much larger models like ACT using noisy, real-world community data instead of giant private datasets. Why it’s worth a look ✅ 26% performance boost from pretraining on open-source data ✅ Runs on consumer hardware, even a MacBook ✅ 30% faster responses with async inference and smart architecture tweaks ✅ Strong results across Meta-World, LIBERO, SO100, and SO101 ✅ Fully open source: weights, code, training pipeline, eval stack They also introduced smart efficiency tricks like using fewer visual tokens, pulling outputs from mid-layer, and separating perception from action to make it all run fast. SmolVLA is a strong case for what can happen when the robotics community shares data and builds in the open. Definitely worth keeping an eye on.

Ilir Aliu - eu/acc

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🚀Napkin AI just launched Custom Generation to give you more control over your visuals, so you can get the visual you want, faster. Now during generation, you can: ✅ Specify the visual type you need – flowcharts, mind maps, tables, or anything else ✅ Choose your preferred orientation that best suits your use case – vertical, horizontal, square, and more ✅ Control visual depth – detailed breakdowns when you need specifics or summary views for the big picture ✅ Keep your original wording intact with "Stay closer to my text" This is another step towards making visual generation effortless – so you spend less time fixing and more time creating what you want. #NapkinAI #VisualAI #AITools #CustomGeneration #NewFeatures

Napkin AI

27,427 次观看 • 1 年前

Typing just became… Typeless. Meet Typeless 1.0.2 for Mac — a tool that transforms your voice into clear, accurate writing across your Mac. Speak naturally and let Typeless handle the typing, corrections, and structure for you. With Typeless, you can dictate, translate, or ask for quick edits in any language or accent. It converts your speech into polished text up to 10× faster than traditional typing, while automatically fixing mistakes along the way. --- 1️⃣ Dictation Typeless acts as a powerful voice keyboard that works across all applications on your Mac. When you speak, it understands your intent, organizes your ideas, and converts your natural speech into well-structured writing. Whether you're drafting emails, notes, documents, or messages, Typeless helps you turn spoken thoughts into clean text instantly. Controls - Press Fn to start or stop dictation - Hold Fn for quick, short dictation --- 2️⃣ Translation Typeless makes writing in other languages effortless. You can speak in your native language and have Typeless translate your words instantly into the language you want. This allows you to communicate, write, and respond in foreign languages smoothly and naturally. Controls - Press Fn + Space to start translation - Press Fn to stop translation --- 3️⃣ Ask Anything Typeless Typeless also lets you interact with your text using voice commands. You can select any text and simply say how you want it changed. Typeless can edit, rewrite, answer questions, or perform quick actions based on your request, making editing and improving text much faster. Controls - Press Fn + Space to start Ask Anything - Press Fn to stop Ask Anything --- With Typeless, your voice becomes the fastest and easiest way to write, edit, and communicate on your Mac. Your voice is now your keyboard. Get Typeless → Available now on Mac, Windows, iOS, and Android. #Typeless

Typing just became… Typeless. Meet Typeless 1.0.2 for Mac — a tool that transforms your voice into clear, accurate writing across your Mac. Speak naturally and let Typeless handle the typing, corrections, and structure for you. With Typeless, you can dictate, translate, or ask for quick edits in any language or accent. It converts your speech into polished text up to 10× faster than traditional typing, while automatically fixing mistakes along the way. --- 1️⃣ Dictation Typeless acts as a powerful voice keyboard that works across all applications on your Mac. When you speak, it understands your intent, organizes your ideas, and converts your natural speech into well-structured writing. Whether you're drafting emails, notes, documents, or messages, Typeless helps you turn spoken thoughts into clean text instantly. Controls - Press Fn to start or stop dictation - Hold Fn for quick, short dictation --- 2️⃣ Translation Typeless makes writing in other languages effortless. You can speak in your native language and have Typeless translate your words instantly into the language you want. This allows you to communicate, write, and respond in foreign languages smoothly and naturally. Controls - Press Fn + Space to start translation - Press Fn to stop translation --- 3️⃣ Ask Anything Typeless Typeless also lets you interact with your text using voice commands. You can select any text and simply say how you want it changed. Typeless can edit, rewrite, answer questions, or perform quick actions based on your request, making editing and improving text much faster. Controls - Press Fn + Space to start Ask Anything - Press Fn to stop Ask Anything --- With Typeless, your voice becomes the fastest and easiest way to write, edit, and communicate on your Mac. Your voice is now your keyboard. Get Typeless → Available now on Mac, Windows, iOS, and Android. #Typeless

Kuria Chronicles

43,623 次观看 • 4 个月前

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

Tencent Hy

412,880 次观看 • 10 个月前

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 次观看 • 1 年前

🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer

🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer

Qiusheng Wu

10,346 次观看 • 9 个月前

🚀 Introducing Queue: A Smarter Way to Build with Replit Agent Today, we’re excited to launch Queue, a powerful new capability designed to enhance your experience with Replit Agent. With Queue, you can submit multiple tasks while your Agent is still working—no more waiting around or breaking your flow. As each task completes, the Agent automatically moves to the next. You can: ✅ Add multiple tasks for the Agent to process in order. ✅ Edit, reorder, or reprioritize messages on the fly. ✅ Attach files and adjust settings—including toggling extended thinking or selecting a different model—per task.

🚀 Introducing Queue: A Smarter Way to Build with Replit Agent Today, we’re excited to launch Queue, a powerful new capability designed to enhance your experience with Replit Agent. With Queue, you can submit multiple tasks while your Agent is still working—no more waiting around or breaking your flow. As each task completes, the Agent automatically moves to the next. You can: ✅ Add multiple tasks for the Agent to process in order. ✅ Edit, reorder, or reprioritize messages on the fly. ✅ Attach files and adjust settings—including toggling extended thinking or selecting a different model—per task.

Replit ⠕

75,576 次观看 • 1 年前

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 次观看 • 11 个月前

Typing is overrated. Talking gets things done. I ditched typing emails and started speaking them instead. Writing used to eat up hours — drafting, rephrasing, fixing tiny mistakes. Even when you’re fast, it’s exhausting. Then I found Typeless (Typeless), and my workflow flipped. Now I can: ✅ Talk naturally → get polished, professional emails ✅ Say an idea → turn it into a tweet or LinkedIn post instantly ✅ Highlight any article → get a clean, usable summary It feels like a personal writer that understands my tone and sharpens every message — in real time. No typing. No rewrites. Just smooth flow from thought to text. If writing is part of your daily work, this is a serious upgrade. 👉 Try it free:

Typing is overrated. Talking gets things done. I ditched typing emails and started speaking them instead. Writing used to eat up hours — drafting, rephrasing, fixing tiny mistakes. Even when you’re fast, it’s exhausting. Then I found Typeless (Typeless), and my workflow flipped. Now I can: ✅ Talk naturally → get polished, professional emails ✅ Say an idea → turn it into a tweet or LinkedIn post instantly ✅ Highlight any article → get a clean, usable summary It feels like a personal writer that understands my tone and sharpens every message — in real time. No typing. No rewrites. Just smooth flow from thought to text. If writing is part of your daily work, this is a serious upgrade. 👉 Try it free:

Haider Anis

111,583 次观看 • 7 个月前

Assumptions about the new "Can More" ChatGPT tool were right - ChatGPT is introducing own take on Claude Artifacts - code & document writing tools with persisted text documents, history revisions (restore previous version), edits and comments (probably used to apply suggested edits) New document symbol in the top navigation shows how many documents you have and allows you to open a resizable canvas to edit them in split view - your ChatGPT conversation on the left side and canvas on the right side, but the code/documents can also be accessed in fullscreen view The canvas is built using ProseMirror (open source WYSIWYM editor) and has an inline action to "Ask ChatGPT" (explain or make edits) for your document and code plus document formatting tools (like bold, italic, font style, etc.) But in addition to that, there are also special action shortcuts for documents and code, with an interesting decision to use sliders for the selection of the desired outcome For Documents - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.") - Add emojis ("Replace as many words as possible with emojis.") - Add final polish ("Add some final polish to the text. If relevant, add a large title or any section titles. Check grammar and mechanics, make sure everything is consistent and reads well. You can reply that you added some final polish and checked for grammar, but do not mention the prompt.") - Reading level (Graduate School - "Rewrite this text at the reading level of a doctoral writer in this subject. You may reply that you adjusted the text to reflect a graduate school reading level, but do not mention the prompt", College - "Rewrite this text at the reading level of a college student majoring in this subject", High School - "Rewrite this text at the reading level of a high school student who has taken a couple of classes in this subject.", Keep current reading level, Middle School - "Rewrite this text at the reading level of a middle schooler.", Kindergarten - "Rewrite this text at the reading level of a kindergartener.") - Adjust the length (Longest - "Make this text 75% longer.", Longer - "Make this text 50% longer.", Keep current length, Shorter - "Make this text 50% shorter.", Shortest - "Make this text 75% shorter.") For Code - Code review ("Search for bugs and opportunities to improve the code—for example, ways that performance or code structure could be improved. Leave as few comments as possible, but add more comments if the text is long. DO NOT leave more than 5 comments. You may reply that you reviewed the code and left suggestions to improve the coding quality, but do not mention the prompt.") - Add comments ("Add inline code comments to explain the code, especially parts that are more complex. Make sure to rewrite all the code. You may reply that you added inline comments, but do not mention the prompt.") - Add logs ("Insert logs/print statements in the code that will help debug its behavior. Do not make any other changes to the code.") - Fix bugs ("Find any bugs and rewrite all the code to fix the bugs. Do not leave comments. If there are no bugs, reply that you reviewed the code and found no bugs.") - Port to a language ("Port to a language. Create a new document that rewrites the code in ..." - PHP, C++, Python, Keep current code. No changes will be made, JavaScript, TypeScript, Java) - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.")

Assumptions about the new "Can More" ChatGPT tool were right - ChatGPT is introducing own take on Claude Artifacts - code & document writing tools with persisted text documents, history revisions (restore previous version), edits and comments (probably used to apply suggested edits) New document symbol in the top navigation shows how many documents you have and allows you to open a resizable canvas to edit them in split view - your ChatGPT conversation on the left side and canvas on the right side, but the code/documents can also be accessed in fullscreen view The canvas is built using ProseMirror (open source WYSIWYM editor) and has an inline action to "Ask ChatGPT" (explain or make edits) for your document and code plus document formatting tools (like bold, italic, font style, etc.) But in addition to that, there are also special action shortcuts for documents and code, with an interesting decision to use sliders for the selection of the desired outcome For Documents - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.") - Add emojis ("Replace as many words as possible with emojis.") - Add final polish ("Add some final polish to the text. If relevant, add a large title or any section titles. Check grammar and mechanics, make sure everything is consistent and reads well. You can reply that you added some final polish and checked for grammar, but do not mention the prompt.") - Reading level (Graduate School - "Rewrite this text at the reading level of a doctoral writer in this subject. You may reply that you adjusted the text to reflect a graduate school reading level, but do not mention the prompt", College - "Rewrite this text at the reading level of a college student majoring in this subject", High School - "Rewrite this text at the reading level of a high school student who has taken a couple of classes in this subject.", Keep current reading level, Middle School - "Rewrite this text at the reading level of a middle schooler.", Kindergarten - "Rewrite this text at the reading level of a kindergartener.") - Adjust the length (Longest - "Make this text 75% longer.", Longer - "Make this text 50% longer.", Keep current length, Shorter - "Make this text 50% shorter.", Shortest - "Make this text 75% shorter.") For Code - Code review ("Search for bugs and opportunities to improve the code—for example, ways that performance or code structure could be improved. Leave as few comments as possible, but add more comments if the text is long. DO NOT leave more than 5 comments. You may reply that you reviewed the code and left suggestions to improve the coding quality, but do not mention the prompt.") - Add comments ("Add inline code comments to explain the code, especially parts that are more complex. Make sure to rewrite all the code. You may reply that you added inline comments, but do not mention the prompt.") - Add logs ("Insert logs/print statements in the code that will help debug its behavior. Do not make any other changes to the code.") - Fix bugs ("Find any bugs and rewrite all the code to fix the bugs. Do not leave comments. If there are no bugs, reply that you reviewed the code and found no bugs.") - Port to a language ("Port to a language. Create a new document that rewrites the code in ..." - PHP, C++, Python, Keep current code. No changes will be made, JavaScript, TypeScript, Java) - Suggest edits ("How can I improve this. Leave as few comments as possible, but add a few more comments if the text is long. DO NOT leave more than 5 comments. You can reply that you added comments and suggestions to help improve the writing quality, but do not mention the prompt.")

Tibor Blaho

136,084 次观看 • 1 年前

NEW GAS PUMP SCAM ALERT — They’re using a single screw to steal your money. Scammers wedge a small drywall screw into the nozzle holder at the pump. You pay, fill up, hang the nozzle… but it never fully resets. The next person (or the scammer) keeps pumping gas on YOUR card. Seen at multiple stations. Real. Simple. Effective. ✅ Always check the cradle before & after pumping ✅ Make sure the nozzle clicks fully in and screen resets to $0 ✅ Avoid “helpful” strangers offering to pump for you Share this. It takes 5 seconds to check and could save you a tank of gas. Has this screw-in-the-cradle gas pump scam been confirmed by law enforcement or multiple stations in your area?

NEW GAS PUMP SCAM ALERT — They’re using a single screw to steal your money. Scammers wedge a small drywall screw into the nozzle holder at the pump. You pay, fill up, hang the nozzle… but it never fully resets. The next person (or the scammer) keeps pumping gas on YOUR card. Seen at multiple stations. Real. Simple. Effective. ✅ Always check the cradle before & after pumping ✅ Make sure the nozzle clicks fully in and screen resets to $0 ✅ Avoid “helpful” strangers offering to pump for you Share this. It takes 5 seconds to check and could save you a tank of gas. Has this screw-in-the-cradle gas pump scam been confirmed by law enforcement or multiple stations in your area?

CeCe

6,729,592 次观看 • 3 个月前

🚀 We launched The Studio by Mirror Mirror AI. Generating fashion campaigns with AI should save you time and budget—without compromising your brand’s identity or aesthetic. That’s why we built The Studio. ✨ The Studio lets brands create campaign-quality imagery in minutes, not weeks: ✅ Drag & drop your products and models—no prompting needed ✅ Instantly generate on-brand visuals ✅ Transform any shot with Editorial Mode polish After a year refining this with high-end fashion teams, it’s finally here. Early Access is now open—reserve your spot: Thank you to everyone who helped us bring this to life.

Yusan Lin

27,810 次观看 • 1 年前

This is dope update for Gemini macOS app 🔥 You can now long press the Fn key and simply talk to Gemini from anywhere on your Mac. By default, it works as an intelligent dictation tool that: - Removes "ums" and "ahs" - Cleans up mid sentence corrections - Formats your text automatically - Pastes polished text directly where your cursor is Enable Gemini Reasoning, and it can do even more by understanding what's on your screen. For example, you can: - Summarize documents, PDFs, and images - Rewrite highlighted text in any tone - Turn notes into polished emails or executive summaries - Generate and edit images using voice commands Instead of switching between apps, you can just speak naturally and Gemini handles the rest. This update is rolling out globally in English for the Gemini app on macOS, with more languages coming soon. Video credit: Google Blog

This is dope update for Gemini macOS app 🔥 You can now long press the Fn key and simply talk to Gemini from anywhere on your Mac. By default, it works as an intelligent dictation tool that: - Removes "ums" and "ahs" - Cleans up mid sentence corrections - Formats your text automatically - Pastes polished text directly where your cursor is Enable Gemini Reasoning, and it can do even more by understanding what's on your screen. For example, you can: - Summarize documents, PDFs, and images - Rewrite highlighted text in any tone - Turn notes into polished emails or executive summaries - Generate and edit images using voice commands Instead of switching between apps, you can just speak naturally and Gemini handles the rest. This update is rolling out globally in English for the Gemini app on macOS, with more languages coming soon. Video credit: Google Blog

AshutoshShrivastava

14,630 次观看 • 14 天前