Tag: embeddings
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Simon Willison’s Weblog: Weeknotes: asynchronous LLMs, synchronous embeddings, and I kind of started a podcast
Source URL: https://simonwillison.net/2024/Nov/22/weeknotes/#atom-everything Source: Simon Willison’s Weblog Title: Weeknotes: asynchronous LLMs, synchronous embeddings, and I kind of started a podcast Feedly Summary: These past few weeks I’ve been bringing Datasette and LLM together and distracting myself with a new sort-of-podcast crossed with a live streaming experiment. Project: interviewing people about their projects Datasette Public Office…
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METR Blog – METR: Evaluating frontier AI R&D capabilities of language model agents against human experts
Source URL: https://metr.org/blog/2024-11-22-evaluating-r-d-capabilities-of-llms/ Source: METR Blog – METR Title: Evaluating frontier AI R&D capabilities of language model agents against human experts Feedly Summary: AI Summary and Description: Yes Summary: The text discusses the release of RE-Bench, a new benchmark aimed at evaluating the performance of AI agents against human experts in machine learning (ML) research…
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Simon Willison’s Weblog: llm-gguf 0.2, now with embeddings
Source URL: https://simonwillison.net/2024/Nov/21/llm-gguf-embeddings/#atom-everything Source: Simon Willison’s Weblog Title: llm-gguf 0.2, now with embeddings Feedly Summary: llm-gguf 0.2, now with embeddings This new release of my llm-gguf plugin – which adds support for locally hosted GGUF LLMs – adds a new feature: it now supports embedding models distributed as GGUFs as well. This means you can…
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Hacker News: You could have designed state of the art positional encoding
Source URL: https://fleetwood.dev/posts/you-could-have-designed-SOTA-positional-encoding Source: Hacker News Title: You could have designed state of the art positional encoding Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the evolution of positional encoding in transformer models, specifically focusing on Rotary Positional Encoding (RoPE) as utilized in modern language models like Llama 3.2. It explains…
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Hacker News: All-in-one embedding model for interleaved text, images, and screenshots
Source URL: https://blog.voyageai.com/2024/11/12/voyage-multimodal-3/ Source: Hacker News Title: All-in-one embedding model for interleaved text, images, and screenshots Feedly Summary: Comments AI Summary and Description: Yes Summary: The text announces the release of voyage-multimodal-3, a cutting-edge multimodal embedding model that enhances the capability of semantic search and retrieval tasks involving both text and images. Its ability to…
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Hacker News: Omnivision-968M: Vision Language Model with 9x Tokens Reduction for Edge Devices
Source URL: https://nexa.ai/blogs/[object Object] Source: Hacker News Title: Omnivision-968M: Vision Language Model with 9x Tokens Reduction for Edge Devices Feedly Summary: Comments AI Summary and Description: Yes **Summary:** OmniVision is an advanced multimodal model designed for effective processing of visual and textual inputs on edge devices. It improves upon the LLaVA architecture by reducing image…
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Simon Willison’s Weblog: Binary vector embeddings are so cool
Source URL: https://simonwillison.net/2024/Nov/11/binary-vector-embeddings/#atom-everything Source: Simon Willison’s Weblog Title: Binary vector embeddings are so cool Feedly Summary: Binary vector embeddings are so cool Evan Schwartz: Vector embeddings by themselves are pretty neat. Binary quantized vector embeddings are extra impressive. In short, they can retain 95+% retrieval accuracy with 32x compression and ~25x retrieval speedup. It’s so…
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Hacker News: Binary vector embeddings are so cool
Source URL: https://emschwartz.me/binary-vector-embeddings-are-so-cool/ Source: Hacker News Title: Binary vector embeddings are so cool Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses binary quantized vector embeddings, emphasizing their ability to retain high accuracy while dramatically reducing storage size for machine learning applications. This topic is particularly relevant for AI and infrastructure security…
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Cloud Blog: Getting started with NL2SQL (natural language to SQL) with Gemini and BigQuery
Source URL: https://cloud.google.com/blog/products/data-analytics/nl2sql-with-bigquery-and-gemini/ Source: Cloud Blog Title: Getting started with NL2SQL (natural language to SQL) with Gemini and BigQuery Feedly Summary: The rise of Natural Language Processing (NLP) combined with traditional Structured Query Language (SQL) has given rise to an exciting new technology known as Natural Language to SQL, or NL2SQL, which translates questions phrased…
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Cloud Blog: How to simplify building RAG pipelines in BigQuery with Document AI Layout Parser
Source URL: https://cloud.google.com/blog/products/data-analytics/bigquery-and-document-ai-layout-parser-for-document-preprocessing/ Source: Cloud Blog Title: How to simplify building RAG pipelines in BigQuery with Document AI Layout Parser Feedly Summary: Document preprocessing is a common hurdle when building retrieval-augmented generation (RAG) pipelines. It often requires Python skills and external libraries to parse documents like PDFs into manageable chunks that can be used to…