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Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But... show more

DeepLearning.AI

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40,810 次观看 • 9 个月前 •via X (Twitter)

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we've created a unified graph schema to allow BADDIE agents to do inference and execute search queries that cross between multiple data sources and entity categories eg. search by drugbank semantic info -> search chembl for similar bioactive compounds by explicit chemistry -> filter results with richer bioactivity data from cross-referencing uniprot or geneontology

we've created a unified graph schema to allow BADDIE agents to do inference and execute search queries that cross between multiple data sources and entity categories eg. search by drugbank semantic info -> search chembl for similar bioactive compounds by explicit chemistry -> filter results with richer bioactivity data from cross-referencing uniprot or geneontology

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Andrew Ng

63,773 次观看 • 6 个月前

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️

LangChain

13,518 次观看 • 6 个月前

Discover how AI agents are revolutionizing data utilization. In this clip, Anjali George from Theoriq showcases how multi-agent systems unlock untapped data reservoirs, enabling faster insights, smarter decisions, and innovative breakthroughs with Filecoin's ecosystem.

Discover how AI agents are revolutionizing data utilization. In this clip, Anjali George from Theoriq showcases how multi-agent systems unlock untapped data reservoirs, enabling faster insights, smarter decisions, and innovative breakthroughs with Filecoin's ecosystem.

Filecoin

19,579 次观看 • 1 年前

With the launch of GLM-5, introduces Agent Mode. - Agent Mode: Automatically breaks down tasks, orchestrates tools, drives execution, and delivers ready-to-use files. - Data Insights & Smart Writing: Upload data for instant visualizations. Go from outline to finished draft, all in one place. - AI Slides / Full-Stack upgraded: Now handles more complex instructions and multi-step workflows.

With the launch of GLM-5, introduces Agent Mode. - Agent Mode: Automatically breaks down tasks, orchestrates tools, drives execution, and delivers ready-to-use files. - Data Insights & Smart Writing: Upload data for instant visualizations. Go from outline to finished draft, all in one place. - AI Slides / Full-Stack upgraded: Now handles more complex instructions and multi-step workflows.

Z.ai

29,781 次观看 • 5 个月前

Learn about our research prototype LLM-powered personal health agent that analyzes various data modalities, including data from wearable devices, to offer evidence-based health insights and to provide a personalized coaching experience. Read more →

Learn about our research prototype LLM-powered personal health agent that analyzes various data modalities, including data from wearable devices, to offer evidence-based health insights and to provide a personalized coaching experience. Read more →

Google Research

25,348 次观看 • 9 个月前