# Generative AI techniques

Published articles for Generative AI techniques.

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## Ep. 7: Enhancing AI with Message Chaining and Accuracy Scoring

DevFeed: [Ep. 7: Enhancing AI with Message Chaining and Accuracy Scoring](<https://devfeed.tech/articles/ep-7-enhancing-ai-with-message-chaining-and-accuracy-scoring-22257.md>)

Original publisher: [Read original article](<https://www.ardanlabs.com/blog/2024/09/enhancing-ai-with-message-chaining-and-accuracy-scoring-ep7.html>)

Published: 2024-09-19T00:00:00Z

Content type: tutorial

Language: en

Sources: [William Kennedy](<https://devfeed.tech/sources/william-kennedy.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [context](<https://devfeed.tech/topics/context.md>), [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [advanced-ai-workflows](<https://devfeed.tech/tags/advanced-ai-workflows.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-accuracy-scoring](<https://devfeed.tech/tags/ai-accuracy-scoring.md>), [ai-chatbot-continuity](<https://devfeed.tech/tags/ai-chatbot-continuity.md>), [ai-context-management](<https://devfeed.tech/tags/ai-context-management.md>), [ai-conversation-tracking](<https://devfeed.tech/tags/ai-conversation-tracking.md>), [ai-decision-making-validation](<https://devfeed.tech/tags/ai-decision-making-validation.md>), [ai-driven-system-accuracy](<https://devfeed.tech/tags/ai-driven-system-accuracy.md>), [ai-for-healthcare-accuracy](<https://devfeed.tech/tags/ai-for-healthcare-accuracy.md>), [ai-legal-and-finance-accuracy](<https://devfeed.tech/tags/ai-legal-and-finance-accuracy.md>), [ai-message-chaining](<https://devfeed.tech/tags/ai-message-chaining.md>), [ai-model-chaining](<https://devfeed.tech/tags/ai-model-chaining.md>), [building-smarter-ai-systems](<https://devfeed.tech/tags/building-smarter-ai-systems.md>), [chatbots](<https://devfeed.tech/tags/chatbots.md>), [complex-ai-tasks](<https://devfeed.tech/tags/complex-ai-tasks.md>), [context](<https://devfeed.tech/tags/context.md>), [context-aware-ai-systems](<https://devfeed.tech/tags/context-aware-ai-systems.md>), [enhancing-ai-conversations](<https://devfeed.tech/tags/enhancing-ai-conversations.md>), [factuality-scoring-in-ai](<https://devfeed.tech/tags/factuality-scoring-in-ai.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [generative-ai-techniques](<https://devfeed.tech/tags/generative-ai-techniques.md>), [intro-to-generative-ai-series](<https://devfeed.tech/tags/intro-to-generative-ai-series.md>), [models](<https://devfeed.tech/tags/models.md>), [multi-faceted-ai-automation](<https://devfeed.tech/tags/multi-faceted-ai-automation.md>), [multi-step-ai-processes](<https://devfeed.tech/tags/multi-step-ai-processes.md>), [processes](<https://devfeed.tech/tags/processes.md>), [reliable-ai-outputs](<https://devfeed.tech/tags/reliable-ai-outputs.md>), [workflows](<https://devfeed.tech/tags/workflows.md>)

### AI overview

This episode explains how message chaining preserves conversation context, how factuality scoring checks AI responses against verified sources, and how chaining multiple models enables complex, multi-step workflows.

### Source excerpt

Introduction: Welcome to the final episode of our Intro to Generative AI series! In this episode, Daniel Whitenack takes the concepts you've been learning and shows you how to apply advanced techniques like message chaining and factuality scoring to make your AI-driven systems smarter and more reliable. This session will help you understand how to create workflows that combine multiple models, ensuring your AI can provide accurate, context-aware responses and make decisions grounded in real data.

## Ep. 5: Key Techniques for Accurate AI-Driven Information Retrieval

DevFeed: [Ep. 5: Key Techniques for Accurate AI-Driven Information Retrieval](<https://devfeed.tech/articles/ep-5-key-techniques-for-accurate-ai-driven-information-retrieval-22253.md>)

Original publisher: [Read original article](<https://www.ardanlabs.com/blog/2024/07/key-techniques-for-accurate-ai-driven-information-retrieval-ep5.html>)

Published: 2024-08-22T00:00:00Z

Content type: tutorial

Language: en

Sources: [William Kennedy](<https://devfeed.tech/sources/william-kennedy.md>)

Topics: [information retrieval](<https://devfeed.tech/topics/information-retrieval.md>), [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [context](<https://devfeed.tech/topics/context.md>), [data](<https://devfeed.tech/topics/data.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [cohere](<https://devfeed.tech/topics/cohere.md>), [HTML](<https://devfeed.tech/topics/html.md>), [Website](<https://devfeed.tech/topics/website.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-and-web-page-content-extraction](<https://devfeed.tech/tags/ai-and-web-page-content-extraction.md>), [ai-driven-information-retrieval](<https://devfeed.tech/tags/ai-driven-information-retrieval.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [ai-models-and-text-data](<https://devfeed.tech/tags/ai-models-and-text-data.md>), [cohere](<https://devfeed.tech/tags/cohere.md>), [cohere-api-for-embeddings](<https://devfeed.tech/tags/cohere-api-for-embeddings.md>), [context](<https://devfeed.tech/tags/context.md>), [context-handling-in-ai](<https://devfeed.tech/tags/context-handling-in-ai.md>), [cosine-similarity-search](<https://devfeed.tech/tags/cosine-similarity-search.md>), [data](<https://devfeed.tech/tags/data.md>), [databases](<https://devfeed.tech/tags/databases.md>), [effective-ai-information-retrieval](<https://devfeed.tech/tags/effective-ai-information-retrieval.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [enhancing-ai-model-accuracy](<https://devfeed.tech/tags/enhancing-ai-model-accuracy.md>), [generative-ai-techniques](<https://devfeed.tech/tags/generative-ai-techniques.md>), [guide](<https://devfeed.tech/tags/guide.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [html](<https://devfeed.tech/tags/html.md>), [information-retrieval](<https://devfeed.tech/tags/information-retrieval.md>), [lancedb-vector-database](<https://devfeed.tech/tags/lancedb-vector-database.md>), [large-text-data-processing](<https://devfeed.tech/tags/large-text-data-processing.md>), [managing-large-scale-text-data-in-ai](<https://devfeed.tech/tags/managing-large-scale-text-data-in-ai.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [semantic-search-optimization](<https://devfeed.tech/tags/semantic-search-optimization.md>), [vector-embeddings-in-ai](<https://devfeed.tech/tags/vector-embeddings-in-ai.md>), [vectorization-techniques](<https://devfeed.tech/tags/vectorization-techniques.md>)

### AI overview

Episode 5 of an introductory Generative AI series explains techniques for retrieving relevant information from large text collections. It covers converting web content to Markdown, splitting text into overlapping chunks to preserve context, generating vector embeddings with Cohere's API, storing embeddings in vector databases such as LanceDB, and using cosine similarity for semantic search.

### Source excerpt

Introduction: Welcome to Episode 5 of our Intro to Generative AI series! In this episode, Daniel explores practical techniques for enhancing AI models' ability to handle large volumes of text data effectively. He addresses the challenges developers face when working with extensive content, such as entire web pages or internal documents, and provides actionable strategies to optimize the retrieval and processing of relevant information. Context Handling: Splitting large text into manageable chunks while preserving context. Vectorization Techniques: Converting text chunks into vector representations for semantic search. Semantic Search: Implementing cosine similarity to retrieve relevant information efficiently.