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Five Stages of Artificial Intelligence According to OpenAI: A Guide to Reaching Human-Equivalent Problem-Solving Skills

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 14, 202436Views0Likes0Comments
OpenAI has launched a new five-level classification framework to track its progress toward achieving Artificial Intelligence (AI) that can surpass human performance, augmenting its already substantial commitment to AI safety and future improvements. At Level 1 - "Conversational AI", AI models like ChatGPT are capable of basic interaction with people. These chatbots can understand and respond…

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Ten years of Change: The Redefinition of Stereo Matching through Deep Learning in the 2020s

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 14, 202434Views0Likes0Comments
Stereo matching, a fundamental aspect of computer vision for nearly fifty years, involves the calculation of disparity maps from two corrected images. Its application is critical to multiple fields including autonomous driving, robotics and augmented reality. Existing surveys categorise end-to-end architectures into 2D and 3D based on cost-volume computation and optimisation methodologies. These surveys highlight…

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Unveiling Q-GaLore: A Resource-Efficient Method for Initial Training and Optimization of Machine Learning Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Fine Tuning, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 14, 202429Views0Likes0Comments
Large Language Models (LLMs) have become essential tools in various industries due to their superior ability to understand and generate human language. However, training LLMs is notably resource-intensive, demanding sizeable memory allocations to manage the multitude of parameters. For instance, the training of the LLaMA 7B model from scratch calls for approximately 58 GB of…

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Korvus: A Comprehensive Open-Source RAG (Retrieval-Augmented Generation) Framework Designed for Postgres

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, RAG, Staff, Tech News, Technology, UncategorizedJuly 14, 202435Views0Likes0Comments
The Retrieval-Augmented Generation (RAG) pipeline is a four-step process that includes generating embeddings for queries and documents, retrieving relevant documents, analyzing the retrieved data, and generating the final answer response. Utilizing machine learning libraries like HuggingFace for generating embeddings and search engines like Elasticsearch for document retrieval, this process could be potentially cumbersome, time-consuming, and…

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Korvus: A Comprehensive Open-Source RAG (Retrieval-Augmented Generation) Framework Designed for Postgres

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, RAG, Staff, Tech News, Technology, UncategorizedJuly 14, 202436Views0Likes0Comments
The Retrieval-Augmented Generation (RAG) pipeline is a complex process that involves generating embeddings for queries and documents, retrieving relevant documents, analyzing the retrieved data, and generating the final response. Each step in the pipeline requires its unique set of tools and queries, making the process intricate, time-consuming, and prone to errors. The development of the RAG…

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Improving LLM Dependability: The Retrospective Viewpoint Method for Detecting Hallucinations

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 14, 202436Views0Likes0Comments
Large Language Models (LLMs) such as GPT-4 are highly proficient in text generation tasks including summarization and question answering. However, a common problem is their tendency to generate “hallucinations,” which refers to the production of factually incorrect or contextually irrelevant content. This problem becomes critical when it occurs despite the LLMs being given correct facts,…

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Improving LLM Trustworthiness: The Retrospective Viewpoint Method for Identifying Hallucinations

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 14, 202430Views0Likes0Comments
Large language models (LLMs) such as GPT-4 have shown impressive capabilities in generating text for summarization and question answering tasks. But these models often “hallucinate,” or produce content that is either contextually irrelevant or factually incorrect. This is particularly concerning in applications where accuracy is crucial, such as document-based question answering and summarization, and where…

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Hyperion: An Innovative, Modular Framework for High-Performance Optimization Tailored for Both Discrete and Continuous-Time SLAM Applications

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Robotics, Staff, Tech News, Technology, UncategorizedJuly 14, 202437Views0Likes0Comments
The positioning and tracking of a sensor suite within its environment is a critical element in robotics. Traditional methods known as Simultaneous Localization and Mapping (SLAM) confront issues with unsynchronized sensor data and require demanding computations, which must estimate the position at distinct time intervals, complicating the handling of unequal data from multiple sensors. Despite…

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FBI-LLM (Fully BInarized Large Language Model): A structure for AI that uses successive distillation for the 1-bit weight binarization of LLMs, built from the ground up.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 14, 202437Views0Likes0Comments
Transformer-based Large Language Models (LLMs) like ChatGPT and LLaMA are highly effective in tasks requiring specialized knowledge and complex reasoning. However, their massive computational and storage requirements present significant challenges in wider applications. One solution to this problem is quantization, a method that converts 32-bit parameters into smaller bit sizes, which greatly improves storage efficiency…

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Stanford researchers present In-Context Vectors (ICV): An Effective and Scalable AI Method for Precision Enhancement of Extensive Language Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 14, 202438Views0Likes0Comments
Large language models (LLMs) are pivotal in advancing artificial intelligence and natural language processing. Despite their impressive capabilities in understanding and generating human language, LLMs still grapple with the issue of improving the effectiveness and control of in-context learning (ICL). Traditional ICL methods often suffer from uneven performance and significant computational overhead due to the…

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The IXC-2.5, also known as InternLM-XComposer-2.5, is a flexible wide-range language model that can handle extended contextual input and output.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 14, 202438Views0Likes0Comments
Large Language Models (LLMs) have seen substantial progress, leading researchers to focus on developing Large Vision Language Models (LVLMs), which aim to unify visual and textual data processing. However, open-source LVLMs face challenges in offering versatility comparable to proprietary models like GPT-4, Gemini Pro, and Claude 3, primarily due to limited diverse training data and…

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Interleave-LLaVA-NeXT: A Highly Adaptable Large Multimodal LMM Model Capable of Managing Configurations such as Multiple Images, Multiple Frames, and Multiple Views.

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 14, 202435Views0Likes0Comments
The power of Large Multimodal Models (LMMs) has shown great potential in furthering artificial general intelligence. These models are enhanced with visual abilities by harnessing vast amounts of vision-language data and aligning vision encoders. Despite this, most open-source LMMs are focused primarily on single-image scenarios, leaving complex multi-image scenarios mostly untouched. This oversight is significant…

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