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This AI Paper Explores New Ways to Utilize and Optimize Multimodal RAG System for Industrial Applications
Unlocking AI Potential in Industry with Multimodal RAG Technology What is Multimodal RAG? Multimodal Retrieval Augmented Generation (RAG) technology enhances AI applications in manufacturing, engineering, and maintenance. It effectively combines text and images from complex documents like manuals and diagrams, improving task accuracy and efficiency. Challenges in Industrial AI AI systems often struggle to provide…
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Promptfoo: An AI Tool For Testing, Evaluating and Red-Teaming LLM apps
What is Promptfoo? Promptfoo is a command-line interface (CLI) and library that helps improve the evaluation and security of large language model (LLM) applications. It allows users to create effective prompts, configure models, and build retrieval-augmented generation (RAG) systems using specific benchmarks for different use cases. Key Features: Automated Security Testing: Supports red teaming and…
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Llama-3-Nanda-10B-Chat: A 10B-Parameter Open Generative Large Language Model for Hindi with Cutting-Edge NLP Capabilities and Optimized Tokenization
Understanding Natural Language Processing (NLP) NLP is about creating computer models that can understand and generate human language. Recent advancements in transformer-based models have led to powerful large language models (LLMs) that excel in English tasks, such as text summarization and sentiment analysis. However, there is a significant gap in NLP for Hindi, which is…
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AMD Open Sources AMD OLMo: A Fully Open-Source 1B Language Model Series that is Trained from Scratch by AMD on AMD Instinct™ MI250 GPUs
Introduction to Open-Source AI Solutions As artificial intelligence (AI) and machine learning rapidly evolve, the need for powerful and flexible solutions is growing. Developers and researchers often struggle with restricted access to advanced technology. Many existing models have limitations due to their proprietary nature, making it challenging for innovators to experiment and deploy these tools…
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All Hands AI Open Sources OpenHands CodeAct 2.1: A New Software Development Agent to Solve Over 50% of Real Github Issues in SWE-Bench
AI Agents in Software Development The use of AI agents in software development has rapidly increased, aiming to boost productivity and automate complex tasks. However, many AI agents struggle to effectively tackle real-world software development challenges, particularly when resolving GitHub issues. These agents often require significant oversight from developers, which undermines their intended purpose. To…
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WACK: Advancing Hallucination Detection by Identifying Knowledge-Based Errors in Language Models Through Model-Specific, High-Precision Datasets and Prompting Techniques
Understanding Large Language Models (LLMs) Large Language Models (LLMs) are powerful tools used for various language tasks, like answering questions and engaging in conversations. However, they often produce inaccurate responses known as “hallucinations.” This can be problematic in fields that need high accuracy, such as medicine and law. Identifying the Problem Researchers categorize hallucinations into…
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CHESTNUT: A QoS Dataset for Mobile Edge Environments
Understanding Quality of Service (QoS) Quality of Service (QoS) is crucial for assessing how well network services perform, especially in mobile environments where devices frequently connect to edge servers. Key aspects of QoS include: Bandwidth Latency Jitter Data Packet Loss Rate The Challenge with Current QoS Datasets Most existing QoS datasets, like the WS-Dream dataset,…
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AUTO-CEI: A Curriculum and Expert Iteration Approach to Elevate LLMs’ Response Precision and Control Refusal Rates Across Diverse Reasoning Domains
Understanding the Challenges of Large Language Models (LLMs) Large language models (LLMs) are increasingly used for complex reasoning tasks, such as logical reasoning, mathematics, and planning. They need to provide accurate answers in challenging situations. However, they face two main problems: Overconfidence: They sometimes give incorrect answers that seem plausible, known as “hallucinations.” Overcautiousness: They…
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This AI Paper Reveals the Inner Workings of Rotary Positional Embeddings in Transformers
Understanding Rotary Positional Embeddings (RoPE) Rotary Positional Embeddings (RoPE) is a cutting-edge method in artificial intelligence that improves how transformer models understand the order of data, particularly in language processing. Traditional transformer models often struggle with the sequence of tokens because they analyze each one separately. RoPE helps these models recognize the position of tokens…
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Top 30 Artificial Intelligence (AI) Tools for Data Analysts
Transform Your Data Analysis with AI Tools The rise of Artificial Intelligence (AI) tools has revolutionized how data is processed, analyzed, and visualized, enhancing the productivity of data analysts significantly. Choosing the right AI tools can lead to deeper insights and increased workflow efficiency. Here is a summary of the top 30 AI tools for…