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Sylvian (Sylvian) creates tool use environments and gathers expert tool use data (VSCode, Excel, etc.) for LLMs. They already have 4,500+ experts, from IMO Golds to MIT/Stanford PhDs, producing data at 1B tokens/wk.

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Y Combinator

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34,674 次观看 • 8 个月前 •via X (Twitter)

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Use this FREE tool to analyze data in 10 sec. This tool is used by more than 500,000 researchers. 1. Go to 2. Click on Data Analysis and upload your data file. 3. Write your prompt for data analysis. 4. For example, generate graphs from data. 5. AnswerThis will generate variety of graphs 6. It also generates an insightful data analysis report. You can download the graphs and the report. Try AnswerThis today. It’s FREE.
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Use this FREE tool to analyze data in 10 sec. This tool is used by more than 500,000 researchers. 1. Go to 2. Click on Data Analysis and upload your data file. 3. Write your prompt for data analysis. 4. For example, generate graphs from data. 5. AnswerThis will generate variety of graphs 6. It also generates an insightful data analysis report. You can download the graphs and the report. Try AnswerThis today. It’s FREE.

Faheem Ullah

26,459 次观看 • 6 个月前

Open-sourcing Introspect: MIT-licensed Deep-Research for your internal data! Works with spreadsheets, databases, PDFs, and web search. Has a remarkably simple architecture – Sonnet agent armed with recursive tool calling and 3 default tools. Best for use-cases where you want to combine insights from SQL with unstructured data + data from the web. Launching a bunch of products built on top of of this soon, but wanted to open-source our core engine to give back to the community! 2 min demo below, links in comments
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Open-sourcing Introspect: MIT-licensed Deep-Research for your internal data! Works with spreadsheets, databases, PDFs, and web search. Has a remarkably simple architecture – Sonnet agent armed with recursive tool calling and 3 default tools. Best for use-cases where you want to combine insights from SQL with unstructured data + data from the web. Launching a bunch of products built on top of of this soon, but wanted to open-source our core engine to give back to the community! 2 min demo below, links in comments

Rishabh Srivastava

71,512 次观看 • 1 年前

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

49,924 次观看 • 1 年前

Hon Farmer John,MP , my team and I have been working on “FeatheryCare” for poultry farmers. We’re currently beta testing and trying to achieve product market fit. I see you do a lot of manual data entry, happy to have you onboard to use our tool. Regards. Poultry Tech Bro.
0:23

Hon Farmer John,MP , my team and I have been working on “FeatheryCare” for poultry farmers. We’re currently beta testing and trying to achieve product market fit. I see you do a lot of manual data entry, happy to have you onboard to use our tool. Regards. Poultry Tech Bro.

Selikem Komla 🇬🇭

164,834 次观看 • 1 年前

Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.
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Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.

National Conservatism

26,004 次观看 • 10 个月前

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!
1:33

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 次观看 • 1 年前

As AI agents get better at computer and tool use, or writing code on the fly for a task, we're going to be able to solve much broader domains of knowledge work. Here's an example of Box AI with the new Claude Skills to generate a clean powerpoint file from existing data.
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As AI agents get better at computer and tool use, or writing code on the fly for a task, we're going to be able to solve much broader domains of knowledge work. Here's an example of Box AI with the new Claude Skills to generate a clean powerpoint file from existing data.

Aaron Levie

30,235 次观看 • 9 个月前

Collecting data is a PAAAAAAAIN❗ If only there were a solution out there... (𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 😱) Jannik Grothusen, researchers and founder in stealth mode 👀 from TU Munich, has created a new tool that helps collect data for robots to learn how to perform tasks. It’s inspired by a device from Stanford, but it’s even better! Here’s why: ✅ It can collect and process data in real-time, meaning no delays. ✅ It’s super easy to control, so collecting data is much faster and simpler. ✅ It can be used with different robot parts because of its smart, modular design. Best of all, this amazing tool is 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲, so anyone can use it or improve it! Github: The system is inspired by Cheng Chi; Universal Manipulation Interface (UMI). Credit: Jannik Grothusen
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Collecting data is a PAAAAAAAIN❗ If only there were a solution out there... (𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 😱) Jannik Grothusen, researchers and founder in stealth mode 👀 from TU Munich, has created a new tool that helps collect data for robots to learn how to perform tasks. It’s inspired by a device from Stanford, but it’s even better! Here’s why: ✅ It can collect and process data in real-time, meaning no delays. ✅ It’s super easy to control, so collecting data is much faster and simpler. ✅ It can be used with different robot parts because of its smart, modular design. Best of all, this amazing tool is 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲, so anyone can use it or improve it! Github: The system is inspired by Cheng Chi; Universal Manipulation Interface (UMI). Credit: Jannik Grothusen

Ilir Aliu

47,397 次观看 • 1 年前

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:
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"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:

Peter Yang

39,600 次观看 • 5 个月前

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

495,827 次观看 • 1 年前

DataTransfer iOS app wip. Ver 1.0.0 Perfect for Anyone that wants to quickly, easily, and reliably pull out all media data from device and can use to restore on another iOS device. Made for iOS only. Mainly started this project because there’s no app I can reliably use without it crashing or too much $ for a simple data backup, plus I need something like this for iOS data recovery situations when customers come in with iOS device for data transfer but FMI on and they cannot remember the login. So this way I can backup data FAST and have multiple ways to transfer the backup files, (Air drop wired or wireless, iCloud, etc) Also, main focus for this app will be elegant UI and high reliability and speed for backups.
1:06

DataTransfer iOS app wip. Ver 1.0.0 Perfect for Anyone that wants to quickly, easily, and reliably pull out all media data from device and can use to restore on another iOS device. Made for iOS only. Mainly started this project because there’s no app I can reliably use without it crashing or too much $ for a simple data backup, plus I need something like this for iOS data recovery situations when customers come in with iOS device for data transfer but FMI on and they cannot remember the login. So this way I can backup data FAST and have multiple ways to transfer the backup files, (Air drop wired or wireless, iCloud, etc) Also, main focus for this app will be elegant UI and high reliability and speed for backups.

Mr. Creator - EuphoriaTools.com

20,698 次观看 • 1 年前

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!
2:24

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

84,686 次观看 • 1 年前

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work
0:35

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work

Python Coding

107,470 次观看 • 9 个月前

Shuler: Are we now saying that this is what we’re getting to, that an athlete can’t use professional judgment without an AI system evaluating them at every turn and saying whether they made the right decision to make a pass to this player or that player? Collective bargaining is the tool that really undergirds this and gives workers a seat at the table to determine how that data is used.
0:51

Shuler: Are we now saying that this is what we’re getting to, that an athlete can’t use professional judgment without an AI system evaluating them at every turn and saying whether they made the right decision to make a pass to this player or that player? Collective bargaining is the tool that really undergirds this and gives workers a seat at the table to determine how that data is used.

Acyn

35,700 次观看 • 5 个月前

Everyone is building RAG applications, but nobody is talking about the data these systems use. You are delusional if you think clients will have their data sitting in a folder waiting for you to process it. Data is everywhere: in Google Drive, Dropbox, S3, Gmail, Slack, you name it. And, of course, no sane developer wants to build connections to every one of these systems. This would be suicide. I'm working with Ragie, and they released Ragie Connect to solve this problem. First, their RAG system is top-notch (they have published how they do on several RAG benchmarks), and with Connect, they made it very simple to integrate client data without having to write any code. (Well, in reality, you still have to write a few lines, but it's minimal.) Instead of developing one-off integrations for Drive, Dropbox, etc, you can use Connect to integrate with all of them and let Ragie handle authentication, authorization, and automatic data synchronization. This is a huge time saver!
3:47

Everyone is building RAG applications, but nobody is talking about the data these systems use. You are delusional if you think clients will have their data sitting in a folder waiting for you to process it. Data is everywhere: in Google Drive, Dropbox, S3, Gmail, Slack, you name it. And, of course, no sane developer wants to build connections to every one of these systems. This would be suicide. I'm working with Ragie, and they released Ragie Connect to solve this problem. First, their RAG system is top-notch (they have published how they do on several RAG benchmarks), and with Connect, they made it very simple to integrate client data without having to write any code. (Well, in reality, you still have to write a few lines, but it's minimal.) Instead of developing one-off integrations for Drive, Dropbox, etc, you can use Connect to integrate with all of them and let Ragie handle authentication, authorization, and automatic data synchronization. This is a huge time saver!

Santiago

72,976 次观看 • 1 年前

Introducing Batch Bridge, powered by Relay A tool that allow users to bridge or swaps multiple tokens across Ethereum, Base and Arbitrum in a single batch transaction using EIP5792 and EIP7702 🔗 Tool Link : 🔗 Code : Batching very small value tokens may cause issues, so it is best to batch tokens worth at least $1. This rool uses EIP-5792 for batching when supported. Wallets that do not support wallet_sendCalls fall back to sequential transactions. For the true batch transaction experience, use ambire.eth wallet or OKX wallet, they fully support EIP-5792 batch calls, allowing all swaps and approvals to execute in a single transaction.
1:29

Introducing Batch Bridge, powered by Relay A tool that allow users to bridge or swaps multiple tokens across Ethereum, Base and Arbitrum in a single batch transaction using EIP5792 and EIP7702 🔗 Tool Link : 🔗 Code : Batching very small value tokens may cause issues, so it is best to batch tokens worth at least $1. This rool uses EIP-5792 for batching when supported. Wallets that do not support wallet_sendCalls fall back to sequential transactions. For the true batch transaction experience, use ambire.eth wallet or OKX wallet, they fully support EIP-5792 batch calls, allowing all swaps and approvals to execute in a single transaction.

Zun

60,118 次观看 • 6 个月前

Excited to present the LLM-Council skill. Initial idea by Karpathy. I just packaged it as a skill. You can easily spin up a council of LLMs or agents via Fireworks AI. Watch how the new GLM-5 model "deliberates" on other LLMs' thoughts on the big question, "Can LLMs reason?" Things worth paying attention to: New open models like GLM-5 have surprisingly improved on complex reasoning and long-running agentic tasks. The AskUserQuestion tool in Claude Code came in handy to select the council and chairperson. As Andrej Karpathy puts it, it's a really interesting way to get different perspectives from LLMs, which can lead to better decision-making on whatever task you are working on. You can use it for other agentic coding use cases, like evaluation, tool building, designing, and research.
0:35

Excited to present the LLM-Council skill. Initial idea by Karpathy. I just packaged it as a skill. You can easily spin up a council of LLMs or agents via Fireworks AI. Watch how the new GLM-5 model "deliberates" on other LLMs' thoughts on the big question, "Can LLMs reason?" Things worth paying attention to: New open models like GLM-5 have surprisingly improved on complex reasoning and long-running agentic tasks. The AskUserQuestion tool in Claude Code came in handy to select the council and chairperson. As Andrej Karpathy puts it, it's a really interesting way to get different perspectives from LLMs, which can lead to better decision-making on whatever task you are working on. You can use it for other agentic coding use cases, like evaluation, tool building, designing, and research.

elvis

39,452 次观看 • 5 个月前

❌ Do NOT use OpenAI for real-time web search - they index the web for fast yet inaccurate replies. 🚀 We’re releasing Browser Use Search API today. It crawls sites and fetches real-time data by interacting with any website. Built because you asked for it. We have already enterprises on board who use this API for web search. If you build general or vertical agents you can use this to enable browser interaction. See how it performs vs ChatGPT 🫣
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❌ Do NOT use OpenAI for real-time web search - they index the web for fast yet inaccurate replies. 🚀 We’re releasing Browser Use Search API today. It crawls sites and fetches real-time data by interacting with any website. Built because you asked for it. We have already enterprises on board who use this API for web search. If you build general or vertical agents you can use this to enable browser interaction. See how it performs vs ChatGPT 🫣

Browser Use

63,567 次观看 • 11 个月前