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Researchers at the Hebrew University of Jerusalem recently discovered that in Retrieval Augmented Generation (RAG) systems, the number of documents processed significantly impacts language model performance, even when the total text length remains constant. The research team conducted experiments using 2,417 questions from the MuSiQue validation dataset, each linked to 20 Wikipedia paragraphs. Two to four paragraphs contained relevant answer information, with the remaining paragraphs serving as distractors. To study the impact of the number of documents, the team created multiple data partitions, progressively reducing the number of documents from 20 to...

Recently, Google announced the release of a brand new Vision-Language Model (VLM) called PaliGemma 2 Mix. This model combines image processing and natural language processing capabilities, allowing it to understand visual information and text input simultaneously, generating corresponding outputs as needed. This marks a significant breakthrough in artificial intelligence technology for multi-task processing. PaliGemma 2 Mix boasts powerful features, integrating image description and optical character recognition.

IBM has officially launched its next-generation open-source large language model, Granite3.1, aiming to secure a leading position in the enterprise AI sector. This series of models features an extended context length of 128K, embedding models, built-in hallucination detection capabilities, and significant performance improvements. IBM claims that the Granite8B Instruct model outperforms its open-source competitors of similar scale, including Meta's Llama3.1, Qwen2.5, and Google's Gemma2.

Google recently launched its next-generation artificial intelligence model, PaliGemma2, which can analyze images and generate captions while answering questions about the emotions and actions of people in the photos. Built on Google's Gemma open model series, PaliGemma2 offers more profound image descriptions than traditional object recognition, enabling it to identify emotions and generate contextually relevant detailed descriptions. However, despite this technology appearing to be a groundbreaking innovation, experts have raised serious warnings about its potential ethical and societal implications. Emotion recognition is not...

Google launched the Gemma22B model with 2 billion parameters, demonstrating exceptional performance across various hardware environments, particularly outperforming models like GPT-3.5-Turbo-0613 and Mixtral-8x7b in the chatbot arena. The model is optimized with the NVIDIA TensorRT-LLM library for efficient deployment in diverse scenarios, from edge devices to powerful cloud environments. To enhance safety, Google introduced the ShieldGemma safet....

Google has launched Gemma2, the latest version of its open-source lightweight language model, offering parameter sizes of 9 billion (9B) and 27 billion (27B). Compared to its predecessor, the Gemma model, this new version promises enhanced performance and faster inference speed.Product Access: https://top.aibase.com/tool/google-gemma-2 Gemma2 originates from Google's Gemini model and aims to make it easier for researchers and developers to access, significantly improving speed and efficiency. Un

Recently at the Google I/O Berlin conference, Google announced the open-sourcing of its latest language model Gemma2, which has made significant breakthroughs in performance and efficiency. Gemma2 offers two parameter sizes: 9B and 27B, with the 27B version's performance approaching that of the 70B Llama3 model, but with a model size that is only about 40% of the latter.