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​[[{“value”:” A major challenge in the field of natural language processing (NLP) is addressing the limitations of decoder-only Transformers. These models, which form the backbone of large language models (LLMs), suffer from significant issues such as representational collapse and over-squashing. Representational collapse occurs when different… Read More »Decoding Decoder-Only Transformers: Insights from Google DeepMind’s Paper Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The remarkable performance in different reasoning tasks has been demonstrated by several Large Language Models (LLMs), such as GPT-4, PaLM, and LLaMA. To further increase the functionality and performance of LLMs, there are more effective prompting methods and increasing the model size, both of… Read More »Buffer of Thoughts (BoT): A Novel Thought-Augmented Reasoning AI Approach for Enhancing Accuracy, Efficiency, and Robustness of LLMs Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Dataset distillation is an innovative approach that addresses the challenges posed by the ever-growing size of datasets in machine learning. This technique focuses on creating a compact, synthetic dataset that encapsulates the essential information of a larger dataset, enabling efficient and effective model training.… Read More »What is Dataset Distillation Learning? A Comprehensive Overview Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In today’s age, learning AI is crucial as companies increasingly rely on it for efficiency, automation, and personalization, yet not everyone is an expert in the field. Salesforce offers short courses on Trailhead, covering essential AI skills to help you become the AI hero… Read More »Top Artificial Intelligence AI Courses from Salesforce Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Accurately predicting antibody structures is essential for developing monoclonal antibodies, pivotal in immune responses and therapeutic applications. Antibodies have two heavy and two light chains, with the variable regions featuring six CDR loops crucial for binding to antigens. The CDRH3 loop presents the greatest… Read More »ABodyBuilder3: A Scalable and Precise Model for Antibody Structure Prediction Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advancements in machine learning have been actively used to improve the domain of healthcare. Despite performing remarkably well on various tasks, these models are often unable to provide a clear understanding of how specific visual changes affect ML decisions. These AI models have… Read More »Google AI Proposes a Machine Learning Framework for Understanding AI Models in Medical Imaging Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This paper explores the domain of uncertainty quantification within large language models (LLMs) to identify scenarios where uncertainty in response to queries is significant. The study encompasses both epistemic and aleatoric uncertainties. Epistemic uncertainty arises from a lack of knowledge or data about the… Read More »Deciphering Doubt: Navigating Uncertainty in LLM Responses Shreya Maji Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advances in artificial intelligence, primarily driven by foundation models, have enabled impressive progress. However, achieving artificial general intelligence, which involves reaching human-level performance across various tasks, remains a significant challenge. A critical missing component is a formal description of what it would take… Read More »The Missing Piece: Combining Foundation Models and Open-Endedness for Artificial Superhuman Intelligence ASI Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Sampling from complex, high-dimensional target distributions, such as the Boltzmann distribution, is crucial in many scientific fields. For instance, predicting molecular configurations depends on this type of sampling. Combinatorial Optimization (CO) can be seen as a distribution learning problem where the samples correspond to… Read More »DiffUCO: A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Sajjad Ansari Artificial Intelligence Category – MarkTechPost