Experimental News Clipping Site

Tag: information retrieval

  • Cloud Blog: Reach beyond the IDE with tools for Gemini Code Assist

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/products/application-development/gemini-code-assist-launches-developer-early-access-for-tools/ Source: Cloud Blog Title: Reach beyond the IDE with tools for Gemini Code Assist Feedly Summary: One of the biggest areas of promise for generative AI is coding assistance — leveraging the power of large language models to help developers create or update application code with amazing speed and accuracy, dramatically boosting…

  • Simon Willison’s Weblog: Quoting Riley Goodside

    —

    by

    system automation
    in

    Source URL: https://simonwillison.net/2024/Dec/14/riley-goodside/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Riley Goodside Feedly Summary: An LLM knows every work of Shakespeare but can’t say which it read first. In this material sense a model hasn’t read at all. To read is to think. Only at inference is there space for serendipitous inspiration, which is why LLMs…

  • Cloud Blog: Tailor your search engine with AI-powered hybrid search in Spanner

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/hybrid-search-in-spanner-combine-full-text-and-vector-search/ Source: Cloud Blog Title: Tailor your search engine with AI-powered hybrid search in Spanner Feedly Summary: Search is at the heart of how we interact with the digital ecosystem, from online shopping to finding critical information. Enter generative AI, and user expectations are higher than ever. For applications to meet diverse user…

  • Hacker News: Roaming RAG – Make the Model Find the Answers

    —

    by

    system automation
    in

    Source URL: http://arcturus-labs.com/blog/2024/11/21/roaming-rag–make-_the-model_-find-the-answers/ Source: Hacker News Title: Roaming RAG – Make the Model Find the Answers Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text presents a novel approach called “Roaming RAG,” which simplifies the retrieval-augmented generation (RAG) model by allowing a large language model (LLM) to directly navigate well-structured documents without the…

  • Simon Willison’s Weblog: Roaming RAG – make the model find the answers

    —

    by

    system automation
    in

    Source URL: https://simonwillison.net/2024/Dec/6/roaming-rag/#atom-everything Source: Simon Willison’s Weblog Title: Roaming RAG – make the model find the answers Feedly Summary: Roaming RAG – make the model find the answers Neat new RAG technique (with a snappy name) from John Berryman: The big idea of Roaming RAG is to craft a simple LLM application so that the…

  • AWS News Blog: New Amazon Bedrock capabilities enhance data processing and retrieval

    —

    by

    system automation
    in

    Source URL: https://aws.amazon.com/blogs/aws/new-amazon-bedrock-capabilities-enhance-data-processing-and-retrieval/ Source: AWS News Blog Title: New Amazon Bedrock capabilities enhance data processing and retrieval Feedly Summary: Amazon Bedrock enhances generative AI data analysis with multimodal processing, graph modeling, and structured querying, accelerating AI application development. AI Summary and Description: Yes Summary: The text introduces several enhancements to Amazon Bedrock, particularly in the…

  • Cloud Blog: Build agentic RAG on Google Cloud databases with LlamaIndex

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/products/databases/llamaindex-integrates-with-alloydb-and-cloud-sql-for-postgresql/ Source: Cloud Blog Title: Build agentic RAG on Google Cloud databases with LlamaIndex Feedly Summary: AI agents are revolutionizing the landscape of gen AI application development. Retrieval augmented generation (RAG) has significantly enhanced the capabilities of large language models (LLMs), enabling them to access and leverage external data sources such as databases.…

  • Cloud Blog: Vertex AI grounding: More reliable models, fewer hallucinations

    —

    by

    system automation
    in

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/how-vertex-ai-grounding-helps-build-more-reliable-models/ Source: Cloud Blog Title: Vertex AI grounding: More reliable models, fewer hallucinations Feedly Summary: At the Gemini for Work event in September, we showcased how generative AI is transforming the way enterprises work. Across all the customer innovation we saw at the event, one thing was clear – if last year was…

  • Hacker News: AI Search Engineer at Activeloop (YC S18): Build Multi-Modal Enterprise Search

    —

    by

    system automation
    in

    Source URL: https://www.workatastartup.com/jobs/68254 Source: Hacker News Title: AI Search Engineer at Activeloop (YC S18): Build Multi-Modal Enterprise Search Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces Activeloop’s innovative API and platform that focuses on multi-modal AI dataset management, specifically designed for large-scale model training and retrieval optimization. This is particularly relevant…

  • Hacker News: WhisperNER: Unified Open Named Entity and Speech Recognition

    —

    by

    system automation
    in

    Source URL: https://arxiv.org/abs/2409.08107 Source: Hacker News Title: WhisperNER: Unified Open Named Entity and Speech Recognition Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces WhisperNER, a novel model that integrates named entity recognition (NER) with automatic speech recognition (ASR) to enhance transcription accuracy and informativeness. This integration is particularly relevant for AI…