🚨 NEWS: RAG con LangChain: Retrieval Augmented Generation pratico per sviluppatori
Ecco i punti chiave in breve:
💡 Hai un LLM che allucina risposte sui tuoi documenti interni? Oppure un chatbot aziendale che risponde solo fino alla data di training del modello? Il problema è sempre lo stesso: la conoscenza del mod...
#aIGenerativa #langChain #rAG #retrievalAugmentedGeneration #embeddingVettoriali
via #AIFoundry : A Developer’s Guide to Managing Models, Cost and Quality in Microsoft Foundry
https://ift.tt/D2CHiaf
#MicrosoftFoundry #Foundry #AIModels #ModelManagement #RAG #RetrievalAugmentedGeneration #AIPlatforms #ModelRouter #CostOptimization #Latency #QualityAssuranc…
Modern artificial intelligence systems are continually evolving. Large Language Models, or LLMs, have become the backbone of modern applications and help build conversational interfaces, like GPS, to more integrated content. However, LLMs lack memory and the capacity to retain content across interactions because they are stateless. And these limitations led to the building of AI agents. These AI agents build beyond simple prompt-response interactions into more autonomous, task-oriented workflows.
Souveräne Enterprise KI in Tagen statt Monaten mit Infinito.Nexus
Der gezeigte Post steht exemplarisch für eine Entwicklung, die aktuell in vielen Unternehmen zu beobachten ist. Es werden kurzfristig KI Entwicklerinnen und Entwickler gesucht, die ein breites Spektrum abdecken, von LLM Integration über RAG bis hin zu produktiven Pipelines und skalierbaren Cloud und Container Umgebungen. Der Bedarf ist hoch, die Anforderungen komplex und die Zeitfenster meist sehr eng. Dabei zeigt sich immer wieder, dass die eigentliche Herausforderung nicht nur im Finden einzelner Expertinnen und Experten liegt, sondern in der fehlenden technischen Grundlage, um solche Lösungen schnell, sicher und nachhaltig umzusetzen. […]
From the .NET blog...
In case you missed it earlier...
Generative AI for Beginners .NET: Version 2 on .NET 10
https://devblogs.microsoft.com/dotnet/generative-ai-for-beginners-dotnet-version-2-on-dotnet-10/ #dotnet #NETAspire #NETFundamentals #AI #csharp #Cloud #NET10 #agentframework #aicourse #generativeai #MicrosoftExtensionsAI #retrievalaugmentedgeneration
From the .NET blog...
Generative AI for Beginners .NET: Version 2 on .NET 10
https://devblogs.microsoft.com/dotnet/generative-ai-for-beginners-dotnet-version-2-on-dotnet-10/ #dotnet #NETAspire #NETFundamentals #AI #csharp #Cloud #NET10 #agentframework #aicourse #generativeai #MicrosoftExtensionsAI #retrievalaugmentedgeneration
To improve the relevance of responses produced by Dropbox Dash, engineers at #Dropbox started using #LLMs to augment human labeling - a crucial step in identifying which documents should be used to generate answers.
Their approach offers useful insights for anyone building systems with #RetrievalAugmentedGeneration (RAG).
Learn more: https://bit.ly/3P1nEyj
AG (Retrieval Augmented Generation) is the solution. Here's how to build your own RAG server from scratch using ollama, Open WebUI and Chroma DB!
✅ Document processing ✅ Vector embeddings ✅ Smart retrieval ✅ Production-ready API
#RetrievalAugmentedGeneration #RAG #AIEngineering #LLM #Python #TTMO #OpenSource #AI
Words and pictures in the history of user experience and the future of artificial intelligence
Modern artificial intelligence tools are largely rooted in text-based interactions. But the history of user experience, information and even humanity shows us that AI will have to go beyond text if it’s going to become relevant.
Meteora Web
Brandon H 
Foojay.io
Kevin Veen-Birkenbach
Barret
InfoQ
chribonn
Duncan Stephen