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The Branch-and-Merge Technique: Improving Language Adaptification in AI Models by Reducing Devastating Memory Loss and Guaranteeing Preservation of Fundamental Language Skills during Acquisition of New Languages.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 15, 202467Views0Likes0Comments
The technique of language model adaptation is integral in artificial intelligence as it aids in modifying large pre-existing language models to function effectively across a range of languages. Notwithstanding their remarkable performance in English, these language learning models' (LLM) capabilities tend to diminish considerably when adapted to less familiar languages. This necessitates the implementation of…

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Samsung Scientists present LoRA-Guard: A method of adjusting guardrails effectively using parameters, based on information exchange between LLMs and Guardrail Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 15, 202474Views0Likes0Comments
Language models are advanced artificial intelligence systems that can generate human-like text, but when they're trained on large amounts of data, there's a risk they'll inadvertently learn to produce offensive or harmful content. To avoid this, researchers use two primary methods: first, safety tuning, which is aligning the model's responses to human values, but this…

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A novel computational method may simplify the process of engineering beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), McGovern Institute, MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedJuly 15, 202468Views0Likes0Comments
Scientists at the Massachusetts Institute of Technology (MIT) have developed a computational tool that can predict mutations to help create better proteins. The tool facilitates the creation of improved versions of proteins through strategic mutations and could offer significant advancements in neuroscience research and medical applications. One common procedure for producing improved proteins involves introducing…

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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, 202488Views0Likes0Comments
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, 202472Views0Likes0Comments
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, 202468Views0Likes0Comments
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, 202474Views0Likes0Comments
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, 202475Views0Likes0Comments
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, 202473Views0Likes0Comments
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, 202472Views0Likes0Comments
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, 202472Views0Likes0Comments
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, 202471Views0Likes0Comments
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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