GenAI

GenAI

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Agentless is a great example of how a more constrained agent is better than a general agent for specific tasks 💡 - it achieves much higher scores on SWE-Bench Lite for bug-fixing than other agent approaches 🛠️
Agentless is a great example of how a more constrained agent is better than a general agent for specific tasks 💡 - it achieves much higher scores on SWE-Bench Lite for bug-fixing than other agent approaches 🛠️
The whole point is to not let the agent do everything, but to do a… — Jerry Liu (@jerryjliu0)
·x.com·
Agentless is a great example of how a more constrained agent is better than a general agent for specific tasks 💡 - it achieves much higher scores on SWE-Bench Lite for bug-fixing than other agent approaches 🛠️
DAIR.AI
DAIR.AI
Learn important prompt engineering techniques to build use cases with LLMs.
·dair-ai.thinkific.com·
DAIR.AI
LLM-powered data classification for data entities at scale
LLM-powered data classification for data entities at scale
With the advent of the Large Language Model (LLM), new possibilities dawned for metadata generation and sensitive data identification at Grab. This prompted the inception of our project aimed to integrate LLM classification into our existing data management service. Read to find out how we transformed what used to be a tedious and painstaking process to a highly efficient system and how it has empowered the teams across the organisation.
·engineering.grab.com·
LLM-powered data classification for data entities at scale
LLM Resource Hub
LLM Resource Hub
A comprehensive collection of Large Language Model (LLM) resources, tools, and learning materials.
·llmresourceshub.vercel.app·
LLM Resource Hub
NODES 2024 - A Graph Entity Resolution Playbook
NODES 2024 - A Graph Entity Resolution Playbook
Entity resolution, the process of determining which digital descriptions correspond to the same real-world entities, is an important graph use case. It is also a crucial precursor to many graph data science projects. In this session, you will learn steps that the Neo4j professional services team has used in many entity resolution projects. The steps include designing a graph data model that highlights shared identifiers, standardizing the format of node properties, identifying outlier nodes that should be excluded from the matching process, using graph data science algorithms to identify duplicate entities, using string similarity to identify misspellings, and capturing the results of entity resolution in your graph. Get certified with GraphAcademy: https://dev.neo4j.com/learngraph Neo4j AuraDB https://dev.neo4j.com/auradb Knowledge Graph Builder https://dev.neo4j.com/KGBuilder Neo4j GenAI https://dev.neo4j.com/graphrag
·m.youtube.com·
NODES 2024 - A Graph Entity Resolution Playbook
Agent Protocol: Interoperability for LLM agents
Agent Protocol: Interoperability for LLM agents
LangGraph is a multi-agent framework. This means not only interacting with other LangGraph agents, but all other types of agents as well, regardless of how they are built. Today we are taking a few steps to to build towards this vision. We are announcing: * Agent Protocol: a common interface for
·blog.langchain.dev·
Agent Protocol: Interoperability for LLM agents
SynaLinks/HybridAGI: The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected
SynaLinks/HybridAGI: The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected
The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected - SynaLinks/HybridAGI
·github.com·
SynaLinks/HybridAGI: The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected
Is a LangGraph compiled graph thread-safe / advised for concurrent use? · langchain-ai/langgraph · Discussion #1211
Is a LangGraph compiled graph thread-safe / advised for concurrent use? · langchain-ai/langgraph · Discussion #1211
I just wanted to validate if it's ok to initialize/compile the graph once and then use it to serve multiple parallel requests in a web application. In other words is the shared state passed fro...
·github.com·
Is a LangGraph compiled graph thread-safe / advised for concurrent use? · langchain-ai/langgraph · Discussion #1211