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Causes of Hallucination in Extensive Language Models (LLMs)

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 11, 202440Views0Likes0Comments
The introduction of large language models (LLMs) such as Llama, PaLM, and GPT-4 has transformed the world of natural language processing (NLP), elevating the capabilities for text generation and comprehension. However, a key issue with these models is their tendency to produce hallucinations - generating content that is factually incorrect or inconsistent with the input…

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AGENTGYM Evolves Agents towards General AI from Specific Tasks: Utilizing Various Environments and Independent Learning

AI Shorts, Applications, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 10, 202433Views0Likes0Comments
Artificial intelligence (AI) research aims to create adaptable and self-learning agents that can handle diverse tasks across different environments. Yet achieving this level of versatility and autonomy is a significant challenge, with current models often requiring extensive human supervision, limiting their scalability. Past research in this arena includes frameworks like AgentBench, AgentBoard, and AgentOhana, which are…

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Micro Agent: An AI Assistant that Composes and Rectifies Code on Your Behalf

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 10, 202441Views0Likes0Comments
Artificial intelligence (AI) has been aiding developers with code generation, yet the output often requires substantial debugging and refining, resulting in a time-consuming process. Traditional tools like Integrated Development Environments (IDEs) and automated testing frameworks partially alleviate these challenges, but still demand extensive manual effort for tweaking and perfecting the generated code. Micro Agent is a…

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Thought-Buffer (TB): A Unique AI Strategy to Boost Precision, Speed, and Resilience of Machine Learning Models by Integrating Advanced Reasoning Capabilities.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 10, 202430Views0Likes0Comments
Large Language Models (LLMs) like GPT-4, PaLM, and LLaMA have shown impressive performance in reasoning tasks through various effective prompting methods and increased model size. The performance enhancement techniques are generally categorized into two types: single-query systems and multi-query systems. However, both these systems come with limitations, the most notable being inefficiencies in the designing…

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Interpreting Transformers that are Decoder-Only: An In-depth Analysis of Google DeepMind’s Study

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 10, 202433Views0Likes0Comments
Natural Language Processing (NLP) faces major challenges in addressing the limitations of decoder-only Transformers, which are the backbone of large language models (LLMs). These models contend with issues like representational collapse and over-squashing, which severely hinder their functionality. Representational collapse happens when different sequences produce nearly the same results, while over-squashing occurs when the model…

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Interpreting Uncertainty: Guiding Through Ambiguity in LLM Responses

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202436Views0Likes0Comments
This paper delves into the realm of uncertainty quantification in large language models (LLMs), aiming to pinpoint scenarios where uncertainty in responses to queries is significant. The study delves into both epistemic and aleatoric uncertainties. Epistemic uncertainty arises from inadequate knowledge or data about reality, while aleatoric uncertainty originates from inherent randomness in prediction problems.…

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ABodyBuilder3: An Expandable and Accurate Framework for Predicting the Structure of Antibodies

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202433Views0Likes0Comments
Researchers from Exscientia and the University of Oxford have developed an advanced predictive model called ABodyBuilder3 for antibody structures. This new tool is key for creating monoclonal antibodies, which are integral in immune responses and therapeutic applications. The novel model improves upon the previous ABodyBuilder2 by enhancing the accuracy of predicting Complementarity Determining Region (CDR)…

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FusOn-pLM: Advancing Targeted Treatment for Oncoproteins Fusion via Improved Protein Language Modeling

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 9, 202434Views0Likes0Comments
Fusion oncoproteins, proteins formed by chromosome translocations, play a critical role in many cancers, especially those found in children. However, due to their large and disordered structures, they are difficult to target with traditional drug design methods. To tackle this challenge, researchers at Duke University have developed FusOn-pLM, a novel protein language model specifically tailored…

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A Complete Guide to Activities and Their Matching LLMs in the Current Artificial Intelligence AI Landscape.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 9, 202440Views0Likes0Comments
In the Artificial Intelligence (AI) world, the proper selection of Large Language Models (LLMs) is essential for maximizing efficiency and accuracy in various tasks. The following is a guide to choosing LLMs for several AI-related activities based on their specialized capabilities. For tasks demanding deep comprehension and interpretation of hard documents such as scientific papers,…

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Overcoming Linguistic Hurdles for Everyone: The Role of Minimal Gate-Based MoE Models in Closing the Divide in Neural Machine Translation

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 9, 202434Views0Likes0Comments
Machine translation, a critical aspect of natural language processing (NLP), is centered on the development of algorithms that translate text from one language to another. This technology is crucial for overcoming language barriers and fostering global communication. Neural machine translation (NMT) has in recent times gained advancements in improving translation accuracy and fluency, pushing the…

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Zyphra Launches Zyda Dataset: An Open Language Modeling Dataset with 1.3 Trillion Tokens

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 8, 202438Views0Likes0Comments
Zyphra, a company specialized in data science, recently unveiled Zyda, a major 1.3 trillion-token open dataset for language modeling. The company claims that Zyda is set to revolutionize the norms of language model training and research by offering an unrivaled blend of size, quality, and accessibility. Zyda is a combination of many superior open datasets…

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This AI study focuses on enhancing the efficiency of Large Language Models (LLMs) by removing matrix multiplication to achieve scalable performance.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 8, 202433Views0Likes0Comments
Matrix multiplication (MatMul) is a fundamental process in most neural network topologies. It is commonly used in vector-matrix multiplication (VMM) by dense layers in neural networks, and in matrix-matrix multiplication (MMM) by self-attention mechanisms. Significant reliance on MatMul can be attributed to GPU optimization for these tasks. Libraries like cuBLAS and the Compute Unified Device…

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