We are grateful to our partners @lablabai
, @langchain
, and @weaviate_io for their support, mentorship, and workshops, which helped make this event successful. Thank you all for participating in our Enterprise AI Hackathon! We are thrilled to welcome innovators who utilized RAG
AGENTS
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Enterprise AI Hackathon Success with RAG Technology Partners
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RAGenda: AI-Powered Meeting Companion Using Cohere Connectors
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Second place: @KibernumChile
's RAGenda – Your AI-Powered Meeting Companion RAGgenda is an AI-powered meeting companion that utilizes Cohere's connectors ecosystem to streamline and improve meeting management. It integrates with a multitude of company resources for comprehensive -
Zephyr AI Agent Detects Apache Airflow Failures Automatically
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Winner: @astronomerio
’s Zephyr – an AI Agent for Apache Airflow Zephyr is a solution that automatically detects failures in Apache Airflow instances, consisting of an API, an AI agent, and a UI. With an extensive machine learning (ML) model, it stores and retrieves relevant -
Enterprise AI Hackathon Drives Innovation and Collaboration
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We just wrapped up our Enterprise AI Hackathon, in partnership with @NYSE. 🎉
— Cohere (@cohere) 26 février 2024
Our builders fostered an environment where collaboration and innovation thrived, developing powerful tools that keep their organizations competitive in this ever-changing world.
Learn more about the… pic.twitter.com/BwqYUjxHZKWe just wrapped up our Enterprise AI Hackathon, in partnership with @NYSE
. Our builders fostered an environment where collaboration and innovation thrived, developing powerful tools that keep their organizations competitive in this ever-changing world. Learn more about the -
Mistral Releases le Chat Frontend Demonstration Platform
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As a small surprise, we’re also releasing le Chat Mistral, a front-end demonstration of what Mistral models can do. Learn more on
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Building Agent-Forward Applications with LangChain and LangGraph
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LangGraph and OpenGPTs: Building Agent-Forward Applications with LangChain A new great video from @AIMakerspace on building agentic applications with some of our newer tech YouTube: https://
youtube.com/watch?v=NdF609
kO8FY
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Language Agents with Verbal Reinforcement Learning Explained
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Reflexion: Language Agents with Verbal Reinforcement Learning Shinn et al.: https://
arxiv.org/abs/2303.11366 #Artificialintelligence #DeepLearning #MachineLearning -
Improving Agent Accuracy Through Reflection and Critique
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Reflection Agents Agents are unreliable. One of the best ways to improve their accuracy is to run some step to check or critique their previous response. We've added three examples of this (based on recent papers): Reflexion Paper: https://
arxiv.org/abs/2303.11366 Language Agent Tree -
Agent-Based Modeling and GIS: Practical Primer for Geospatial Analytics
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"Agent-Based Modelling and Geographical Information Systems: A Practical Primer (#GeoSpatial Analytics and #GIS)" http://
amzn.to/3b26CK9
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#BigData #DataScience #AI #ComputationalScience #SocialScience #AgentBasedModeling #NetworkScience #SpatialAnalysis -
HyperWrite Agent Studio Launch: AI Learns Tasks from Single Example
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It's time to make AI Agents useful.
— Matt Shumer (@mattshumer_) 23 février 2024
I'm thrilled to announce that the @HyperWriteAI Agent Studio is now live!
Just show it a task once by doing it yourself, and the AI can repeat it. pic.twitter.com/XRHHRZgaIfIt's time to make AI Agents useful. I'm thrilled to announce that the @HyperWriteAI Agent Studio is now live! Just show it a task once by doing it yourself, and the AI can repeat it.
→ View original post on X — @hyperwriteai, 2024-02-23 19:57 UTC