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Amazon Redshift RG, powered by AWS Graviton, deliver better performance - running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 at 30% lower cost per vCPU. Run SQL analytics across your data warehouse and data lake from a single engine — including...

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Amazon Web Services

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13,541 просмотров • 4 месяцев назад •via X (Twitter)

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The world around us is changing so fast. And to stay relevant, you need to constantly upskill yourself as well as accumulate capabilities. Data Analytics, Automation, and AI skill will continue to grow and evolve. On this channel, I will help you grow your knowledge of in these areas. From building your first machine learning model to deployment, building your first dashboard to becoming a pro, understanding business process automation using low code tools, data management, as well as learning from industry professionals through podcast. If you would like to learn about Microsoft Fabric, Power Platform, Data Management and Governance, Data Analytics, you are in the right place.
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The world around us is changing so fast. And to stay relevant, you need to constantly upskill yourself as well as accumulate capabilities. Data Analytics, Automation, and AI skill will continue to grow and evolve. On this channel, I will help you grow your knowledge of in these areas. From building your first machine learning model to deployment, building your first dashboard to becoming a pro, understanding business process automation using low code tools, data management, as well as learning from industry professionals through podcast. If you would like to learn about Microsoft Fabric, Power Platform, Data Management and Governance, Data Analytics, you are in the right place.

TheOyinbooke

15,539 просмотров • 2 лет назад

Incredible to see how Box is leveraging Salesforce to grow faster, stay closer to customers, and unlock the power of data. Excited for what’s next: Agentforce + Tableau Next = AI + CRM + real-time insights at scale. Aaron Levie is building the future of enterprise software. Welcome Tableau Next — the world’s first agentic analytics platform! You, your agent, and your app—united with Agentforce across all your data: Salesforce, Snowflake, Databricks, Amazon, Google & more. Built on an open, composable architecture powered by Data Cloud. Agents + humans, driving real insight + action. The future of the #DataFam is here. Watch the #TC25 keynote:
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Incredible to see how Box is leveraging Salesforce to grow faster, stay closer to customers, and unlock the power of data. Excited for what’s next: Agentforce + Tableau Next = AI + CRM + real-time insights at scale. Aaron Levie is building the future of enterprise software. Welcome Tableau Next — the world’s first agentic analytics platform! You, your agent, and your app—united with Agentforce across all your data: Salesforce, Snowflake, Databricks, Amazon, Google & more. Built on an open, composable architecture powered by Data Cloud. Agents + humans, driving real insight + action. The future of the #DataFam is here. Watch the #TC25 keynote:

Marc Benioff

70,016 просмотров • 1 год назад

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!
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Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,182 просмотров • 1 год назад

AI changes fast. Your database shouldn’t struggle to keep up. OceanBase is the unified distributed database for the AI era — built to power mission-critical transactions, real-time operational workloads, and AI on one data foundation. Always Ready for the Speed of Innovation
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AI changes fast. Your database shouldn’t struggle to keep up. OceanBase is the unified distributed database for the AI era — built to power mission-critical transactions, real-time operational workloads, and AI on one data foundation. Always Ready for the Speed of Innovation

OceanBase

2,145,443 просмотров • 1 месяц назад

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale
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AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

Small Cap Snipa

116,034 просмотров • 8 месяцев назад

Introducing the Future of AI-Powered Sports Data with $FXI.⚡️ We’re not just talking about innovation, we’re building it. 🚀 From #AI-driven data capture to on-chain validation and data monetization, the FX1 ecosystem is rewriting the rules of the sports and data economy. Our platform empowers leagues, teams, and creators to unlock the full potential of their data with cutting-edge AI solutions. 🧠 Why FX1? ➡️ AI-Powered Precision: Transform raw sports data into actionable insights. ➡️ Data Validation on Chain: Building trust in the data economy through blockchain. ➡️ AI-Powered Revenue Streams: Use sports data to drive predictive analytics, odds modeling, and other high-value solutions that unlock new ways to monetize. FX1 is leading the charge in AI innovation, creating a seamless bridge between sports, blockchain, and the data economy. This isn’t just evolution - it’s a revolution. 💡 The future of sports is here. And it’s powered by AI. 🤖 Watch the full video and see how we’re turning vision into reality. 👇
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Introducing the Future of AI-Powered Sports Data with $FXI.⚡️ We’re not just talking about innovation, we’re building it. 🚀 From #AI-driven data capture to on-chain validation and data monetization, the FX1 ecosystem is rewriting the rules of the sports and data economy. Our platform empowers leagues, teams, and creators to unlock the full potential of their data with cutting-edge AI solutions. 🧠 Why FX1? ➡️ AI-Powered Precision: Transform raw sports data into actionable insights. ➡️ Data Validation on Chain: Building trust in the data economy through blockchain. ➡️ AI-Powered Revenue Streams: Use sports data to drive predictive analytics, odds modeling, and other high-value solutions that unlock new ways to monetize. FX1 is leading the charge in AI innovation, creating a seamless bridge between sports, blockchain, and the data economy. This isn’t just evolution - it’s a revolution. 💡 The future of sports is here. And it’s powered by AI. 🤖 Watch the full video and see how we’re turning vision into reality. 👇

FX1

23,913 просмотров • 1 год назад

Robots enter data centers! 💽 SeRo developed by NAVER LABS, is built for one of the most overlooked but critical tasks in a data center: managing servers in the IT warehouse. It can autonomously load and unload servers, identify their asset numbers, and log their lifecycle data. Physically, SeRo is designed tall to handle racks up to three meters high, maximizing storage density. SeRo also works as part of a larger system. It hands assets to GaRo, an autonomous transport robot, for seamless movement between warehouse and server room. More AI ops, more data centers, more data centers ops... Perfect market for robotics! 🦾
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Robots enter data centers! 💽 SeRo developed by NAVER LABS, is built for one of the most overlooked but critical tasks in a data center: managing servers in the IT warehouse. It can autonomously load and unload servers, identify their asset numbers, and log their lifecycle data. Physically, SeRo is designed tall to handle racks up to three meters high, maximizing storage density. SeRo also works as part of a larger system. It hands assets to GaRo, an autonomous transport robot, for seamless movement between warehouse and server room. More AI ops, more data centers, more data centers ops... Perfect market for robotics! 🦾

Lukas Ziegler

30,341 просмотров • 1 год назад

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
1:11

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 просмотров • 1 год назад

Beautiful new raster data layers are now available on Google Earth’s intuitive, no-code canvas. 🗺️👉 With the analytical power of Google Earth Engine directly integrated into Google Earth, geospatial analysis is as easy as point and click. Rolling out over the coming days, you will have access to ten new raster layers from Earth Engine's iconic data catalog, including: • Slope • Aspect • Land cover • and more It's never been easier to quickly combine raster data, vector data, imagery, and your own data to save time and make better decisions. Explore these new data layers, now.
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Beautiful new raster data layers are now available on Google Earth’s intuitive, no-code canvas. 🗺️👉 With the analytical power of Google Earth Engine directly integrated into Google Earth, geospatial analysis is as easy as point and click. Rolling out over the coming days, you will have access to ten new raster layers from Earth Engine's iconic data catalog, including: • Slope • Aspect • Land cover • and more It's never been easier to quickly combine raster data, vector data, imagery, and your own data to save time and make better decisions. Explore these new data layers, now.

Google Earth

15,693 просмотров • 5 месяцев назад

Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!
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Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!

DeepLearning.AI

20,833 просмотров • 2 лет назад

We hope you had as much fun watching these as we had creating them. On Irys, your data can: ✧ Be programmed to do (almost) anything, ultimately unlocking new ways to financialize data onchain. ✧ Be retrieved instantly. ✧ And while we highlighted permanence in our last video, you can store data both permanently and temporarily. ✧ All at a lower cost than traditional and web3 alternatives Only one datachain delivers all of this. Data belongs on Irys.
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We hope you had as much fun watching these as we had creating them. On Irys, your data can: ✧ Be programmed to do (almost) anything, ultimately unlocking new ways to financialize data onchain. ✧ Be retrieved instantly. ✧ And while we highlighted permanence in our last video, you can store data both permanently and temporarily. ✧ All at a lower cost than traditional and web3 alternatives Only one datachain delivers all of this. Data belongs on Irys.

Irys (✧ᴗ✧)

72,976 просмотров • 1 год назад

So excited to launch Autograph today. We raised $2.1M from elite operators, founders, and investors to build a platform that feels like God Mode for Operators. It's a single platform that integrates with existing systems — the alphabet soup of enterprise software, like your HRIS, ERP, FP&A, ATS, CRM, along with data warehouses and spreadsheets — to combine, clean, and make sense of your data. This data feeds a series of pre-built apps and agents that allow you to level up as an operator: run your complex, multi-functional workflows 10x better. We're solving the processes that takes forever and is really frustrating, but is essential to operating and scaling effectively: our first few apps are headcount planning, compensation reviews, and sales capacity. We're moving insanely fast. We're shipping a new app every couple of weeks. Soon, we'll have hiring pipelines, vendor analytics, resource allocation, unit economics, CX capacity, people analytics, and more. The best part? It's incredibly fast to set up thanks to our powerful agentic data engine, that processes any data source like magic. That means no long implementations, no multi-year contracts. We think it's the biggest leap forward for operators since the spreadsheet. Book an 20-minute onboarding to get started!
2:34

So excited to launch Autograph today. We raised $2.1M from elite operators, founders, and investors to build a platform that feels like God Mode for Operators. It's a single platform that integrates with existing systems — the alphabet soup of enterprise software, like your HRIS, ERP, FP&A, ATS, CRM, along with data warehouses and spreadsheets — to combine, clean, and make sense of your data. This data feeds a series of pre-built apps and agents that allow you to level up as an operator: run your complex, multi-functional workflows 10x better. We're solving the processes that takes forever and is really frustrating, but is essential to operating and scaling effectively: our first few apps are headcount planning, compensation reviews, and sales capacity. We're moving insanely fast. We're shipping a new app every couple of weeks. Soon, we'll have hiring pipelines, vendor analytics, resource allocation, unit economics, CX capacity, people analytics, and more. The best part? It's incredibly fast to set up thanks to our powerful agentic data engine, that processes any data source like magic. That means no long implementations, no multi-year contracts. We think it's the biggest leap forward for operators since the spreadsheet. Book an 20-minute onboarding to get started!

hari raghavan

83,565 просмотров • 10 месяцев назад

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇
1:03

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇

aigent.run

64,777 просмотров • 11 месяцев назад

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!
5:42

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

Alex Ratner

50,582 просмотров • 1 год назад

Today we announced the new Einstein Copilot Search and Salesforce Vector Database in Data Cloud to power semantic search and retrieval augmented generation. This will enhance Einstein Copilot's ability to understand, generate outputs, and automate actions across a wide variety of use cases, contexts, and data/content types. LLMs can't be relied on to recall specific data they were trained on, so the way to make them work in the enterprise, where accuracy is paramount, is to feed them with the right data using hybrid keyword and vector search-powered RAG. By bringing all this seamlessly into our apps and Einstein Copilot UX as well as Hyperforce cloud infrastructure, we can offer high performance, low latency, addressing data privacy, security, and residency requirements🌟
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Today we announced the new Einstein Copilot Search and Salesforce Vector Database in Data Cloud to power semantic search and retrieval augmented generation. This will enhance Einstein Copilot's ability to understand, generate outputs, and automate actions across a wide variety of use cases, contexts, and data/content types. LLMs can't be relied on to recall specific data they were trained on, so the way to make them work in the enterprise, where accuracy is paramount, is to feed them with the right data using hybrid keyword and vector search-powered RAG. By bringing all this seamlessly into our apps and Einstein Copilot UX as well as Hyperforce cloud infrastructure, we can offer high performance, low latency, addressing data privacy, security, and residency requirements🌟

Clara Shih

49,651 просмотров • 2 лет назад

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.
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The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.

OptimAI Network

50,485 просмотров • 1 год назад

Ryan believes we could get 3-6 years of AI progress at the current pace, but in a single year, once we automated AI R&D. So a jump as big as GPT 3.5 to Mythos in a single year. A big crux is whether you'd end up bottlenecked by data. It seems to that a big source of AI progress currently is human expert data, codified into RL environments and SFT data. Ryan doesn't think human expert data is a primary driver of AI progress, and this ended up being a fruitful debate during the conversation.
2:29

Ryan believes we could get 3-6 years of AI progress at the current pace, but in a single year, once we automated AI R&D. So a jump as big as GPT 3.5 to Mythos in a single year. A big crux is whether you'd end up bottlenecked by data. It seems to that a big source of AI progress currently is human expert data, codified into RL environments and SFT data. Ryan doesn't think human expert data is a primary driver of AI progress, and this ended up being a fruitful debate during the conversation.

Dwarkesh Patel

93,931 просмотров • 1 месяц назад

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!
9:28

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!

Akshay 🚀

65,672 просмотров • 10 месяцев назад