Numbers Station Labs has introduced Meadow, an open-source agentic framework designed for complete data workflows. Meadow is noted for its simplicity and effectiveness, achieving results within 3.6 points of the state-of-the-art on the Spider text-to-SQL benchmark and realizing lifts of up to 20 points. The framework aims to streamline the development and deployment of AI agents, which are increasingly used for autonomous task planning and execution. Meadow's release highlights the growing importance of AI agent infrastructure in accelerating generative AI application development.
🚀 Excited to see yet another major leap in AI: introducing Meadow by @NumbersStnAI ! Meadow harnesses the power of LLM agents to revolutionize data tasks. Here's why you should be excited: 🧵👇
Numbers Station Labs is extremely excited to release Meadow, the first and simplest agentic framework built for complete data workflows. Meadow is fully open source! 🪴💪🏼 Results against benchmarks below 🧵↓ https://t.co/zj9bjzn8x6
Numbers Station Labs is extremely excited to release Meadow, the first and simplest agentic framework built for complete data workflows. Meadow is fully open source! 💪🏼 Results against benchmark in thread 🧵↓ https://t.co/mxzcs02rbI
Numbers Station Labs is extremely excited to release Meadow, the first and simplest agentic framework built for complete data workflows. Meadow is fully open source! 💪🏼 Meadow is within 3.6 points of SOTA on the Spider text-to-SQL benchmark and realizes lifts of up to 20 points…
Numbers Station Labs is extremely excited to release Meadow, the first and simplest agentic framework built for complete data workflows. Meadow is fully open source! 🪴 🧵↓ https://t.co/mxzcs02rbI
Numbers Station Labs is extremely excited to release Meadow, the first and simplest agentic framework built for complete data workflows. Meadow is fully open source! 🪴 Early results show that Meadow is within 3.6 points of state-of-the-art on the Spider text-to-SQL benchmark…
#AI Agents – Build and Host LLM Apps At Scale by @abacusai @nandishtella Read more: https://t.co/unnTMrGrew #BigData #MachineLearning #ArtificialIntelligence #ML #MI cc: @ogrisel @iainljbrown @amuellerml https://t.co/25qJMqa8Op
Building AI Agent Infrastructure AI agents plan & do tasks on their own. They are becoming common for users & developers. Therefore, AI agent infrastructure is key for fast GenAI app development. New tools include agent-specific developer tools, agents as a service, browser… https://t.co/jBj7JABhP0
The Rise of AI Agent Infrastructure https://t.co/tmqohr6CQG
AI agent infrastructure from @MadronaVentures 'Today, many agents are almost entirely vertically integrated, without much managed infrastructure. That means: self-managed cloud hosts for the agents, databases for memory and state, connectors to ingest context from external… https://t.co/2UUFeMYbae