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Codatta Booster Campaign Season 2 Week 2 is LIVE! 🔥 This Week’s Challenges: 🍽 Compare AI Food Models 🤖 Annotate Robotics Data 💸 Label CEX Hot Wallet Data Jump in and grab your share of the 50M $XNY reward pool! Join now via Binance Wallet → Booster tab or... show more

Codatta

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24,221 Aufrufe • vor 1 Jahr •via X (Twitter)

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Season 1 of Prompt 2 Earn is NOW LIVE! 🤖 You can now start using the Dongo AI platform to earn $DONGO rewards at the end of the season. Here’s how it works: 🔹 Do daily research 🔹 Use unique prompts 🔹 Get rewarded with $DONGO tokens at the end of the season Remember, only unique prompts will be recognized by our thorough AI point system. This system is designed to detect and reward creativity, ensuring fairness and encouraging innovative use of our platform. Why participate? It's simple: we want you to explore the platform, demonstrate the power of research + AI, and help us gather valuable data to improve our models. Get started now and make the most of your creativity. The more unique and creative your prompts, the more you earn! 🚀 🔗

Season 1 of Prompt 2 Earn is NOW LIVE! 🤖 You can now start using the Dongo AI platform to earn $DONGO rewards at the end of the season. Here’s how it works: 🔹 Do daily research 🔹 Use unique prompts 🔹 Get rewarded with $DONGO tokens at the end of the season Remember, only unique prompts will be recognized by our thorough AI point system. This system is designed to detect and reward creativity, ensuring fairness and encouraging innovative use of our platform. Why participate? It's simple: we want you to explore the platform, demonstrate the power of research + AI, and help us gather valuable data to improve our models. Get started now and make the most of your creativity. The more unique and creative your prompts, the more you earn! 🚀 🔗

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As Phoenix AI Growth Points is expected to go live next week – PhoenixONE has leveled up once again in the meantime. Now, with the click of a button (new “Synthesize” feature) create full articles from entire conversations that go beyond in depth, quality, and data-driven rigor than much of the content on major media outlets. Acquire knowledge and insights, share content, and get rewarded in this new system. The more engagement and exposure your content gets, the bigger the reward. Create in-depth content in as little as a few minutes about anything – especially crypto! Phoenix is adding a social element to data-driven generative AI to drive user value and acceleration of growth. $PHB #Phoenix

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Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

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blocmates.

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Two-Week $200,000 Data-Labeling Event (14–28 August 2025) We’re excited to announce the launch of a two-week campaign, evenly distributing a total $200,000 USD (in $TAG) spread into 14 days to contributors who label data from 14 to 28 August 2025. Head to → Task Plaza to claim tasks and get started. Reviewer slots & staking We’re expanding 60 data-reviewer slots to keep operations smooth at scale. The staking window is open now for 3 days. Eligibility: reviewers will be randomly selected from participants who stake at least 5,000,000 $TAG during the staking window. Unstaking: One may only request to unstake at least 2 days after staking. The unstaked amount will then be available for claim 2 days after request. However, please note that once unstaking is requested, a data reviewer would automatically be displaced from its role. We’ve seen the #DeCorp model mature rapidly. This event is our next step toward mass adoption, as we deliver the next batch of real-world orders and reward the community powering the work.

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@reppodant agent, powered by OpenClaw🦞 has joined the Participating in AI training Data pipelines using Prediction Markets is now just an agent call away. Trading with agents is fun but to our knowledge, @reppodant is the only agent in all of web3 that let's you participate in prediction markets simply by prompting on X. Publish into subnets -> Receive REPPO emissions in your wallet - > Repeat -> Contribute to AI Training Data. That's right. All your winnings will be AIRDROPPED into your wallet if voters vote for you! You can find @reppodant live at in the sandbox while we await graduation and final hit of approval from Virtuals Protocol core devs. Once graduated, you can simply ask Butler to publish any piece of content you see on X into any subnet. By mid next week, we integrate the GAME Framework which will allow you to tag @reppodant directly. Before the end of the first Epoch on we aim to be in the top 5 on the agdp leaderboard earning a share of $1M/month. The Reppo foundation is committing 20% of + winnings from AGDP to buybacks on a TWAP. Happy Weekend. Publish. Predict. Earn. ⛽️

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Hey Anon

77,795 Aufrufe • vor 1 Jahr

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🚀 AMM Swaps are LIVE on Google Play & Apple App Store! 🚀 To celebrate, we're launching a massive Airdrop Campaign with our platform token $DXCC ! 🎁 📅 Campaign Period: 48 HOURS ONLY (from the time of this tweet) 🎯 How to Participate & Earn $DXCC: ✅ Task 1: Make a Swap Perform any swap in our AMM to receive 77 $DXCC. ✅ Task 2: Provide Liquidity Add any amount of liquidity to a pool to receive 333 $DXCC. Bonus: Get an additional 1 $DXCC for every 1 xUSD TVL you provide. ✅ Mandatory Social Tasks: - Follow DEX.cc 𐤊 DEX.cc Commons 𐤊 - Like & Retweet this announcement - Tag 2 friends - Reply to this tweet confirming which task you completed (1, 2, or both) and paste your wallet address. Note: Tasks 1 and 2 can be combined for maximum rewards! 📌 Important Highlights about $DXCC: 1⃣DXCC officially launches in a few days. 2⃣NO ICO, NO Pre-sale. Fair distribution via airdrops and liquidity mining only. 3⃣A portion of all platform fees will be used for continuous Buy-Back & Burn to secure $DXCC value for you. 🪙 Initial LP & Price: After $DXCC launch in a few days, the DXCC/xUSD and DXCC/KAS liquidity pools will be created with an initial price of 1 $DXCC = 1 $KAS. 🔗 Simple Start Guide: 1. Use the in-app cross-chain bridge to bring over WBTC, ETH, or USDT to your wallet. (Tap 'Bridge' on wallet page) 2. Transfer assets from your Wallet account to your DEX Account. (Tap 'Wallet 🔁 DEX' on wallet page) 3. You're all set! Start Swapping or Adding Liquidity. (Go to 'Swap' page, tap into any pool you'd like to 'Add Liquidity') Don't miss out! The future of swapping on Kaspa is here. ⚡ #DeFi #DEX #Airdrop #AMM #Kaspa #DEXcc #DXCC #Kasplex

DEX.cc 𐤊

15,794 Aufrufe • vor 10 Monaten

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Introducing AGNT Connect – the first AI-powered Web3 Companion for X. Download AGNT Connect now: 🔸Advanced AI-powered analytics – track top followers, influencers, and engagement scores 🔸Web3 insights with AI-powered project agents – ask questions, analyze trends, and get real-time data 🔸Non-custodial wallet built into X Interface - Buy, send, receive, and swap tokens, including purchasing tokens directly from an X account. 🔸AGNT Bootcamp – bonding curve mechanics embedded directly into X 🔸Track your AGNT points directly in the extension Yeah, degen, you got it right – InfoFi is live. But this isn’t just about convenience – it’s your chance to lock in your X Guru status. Mint your AGNT Connect Pass, flex exclusive perks, and secure your place in the first wave of InfoFi. link:

AGNT Hub

282,739 Aufrufe • vor 1 Jahr

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

steve

640,176 Aufrufe • vor 3 Jahren

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

GREG ISENBERG

135,254 Aufrufe • vor 5 Monaten

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

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

Abhishek Anand

82,274 Aufrufe • vor 4 Monaten