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AtomAgents: A Multi-Agent AI System to Autonomously Design Metallic Alloys Tanya Malhotra Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” The multi-scale difficulty of designing new alloys calls for a comprehensive strategy, as this procedure includes gathering pertinent information, using advanced computational methods, running experimental validations, and carefully examining the results. Because the tasks involved in this complex workflow are intricate, it has traditionally… Read More »AtomAgents: A Multi-Agent AI System to Autonomously Design Metallic Alloys Tanya Malhotra Artificial Intelligence Category – MarkTechPost

Saphira AI: An AI Platform that Revolutionizes Hardware Safety Compliance Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Hardware manufacturers must follow rules and regulations called “hardware safety compliance” to ensure their goods aren’t harmful to people or the environment. Typical areas covered by these rules include product design, production, testing, and labeling, though they differ by country and sector. The existing… Read More »Saphira AI: An AI Platform that Revolutionizes Hardware Safety Compliance Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

7 Machine Learning Projects That Can Add Value to Any Resume Abid Ali Awan MachineLearningMastery.com

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​[[{“value”:” Learning by doing is the best way to master essential skills for becoming a machine learning engineer. Instead of just focusing on simple classification and regression models. In this blog, we will focus on advanced machine learning projects that will impact your resume and… Read More »7 Machine Learning Projects That Can Add Value to Any Resume Abid Ali Awan MachineLearningMastery.com

ETH Zurich Researchers Introduce Data-Driven Linearization DDL: A Novel Algorithm in Systematic Linearization for Dynamical Systems Aswin Ak Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Accurately modeling nonlinear dynamical systems using observable data remains a significant challenge across various fields such as fluid dynamics, climate science, and mechanical engineering. Traditional linear approximation methods often fall short in capturing the complex behaviors exhibited by these systems, leading to inaccurate predictions… Read More »ETH Zurich Researchers Introduce Data-Driven Linearization DDL: A Novel Algorithm in Systematic Linearization for Dynamical Systems Aswin Ak Artificial Intelligence Category – MarkTechPost

ArabLegalEval: A Multitask AI Benchmark Dataset for Assessing the Arabic Legal Knowledge of LLMs Shoaib Nazir Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” The evaluation of legal knowledge in large language models (LLMs) has primarily focused on English-language contexts, with benchmarks like MMLU and LegalBench providing foundational methodologies. However, the assessment of Arabic legal knowledge remained a significant gap. Previous efforts involved translating English legal datasets and… Read More »ArabLegalEval: A Multitask AI Benchmark Dataset for Assessing the Arabic Legal Knowledge of LLMs Shoaib Nazir Artificial Intelligence Category – MarkTechPost

Google DeepMind Researchers Propose a Dynamic Visual Memory for Flexible Image Classification Shreya Maji Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” Deep learning models typically represent knowledge statically, making adapting to evolving data needs and concepts challenging. This rigidity necessitates frequent retraining or fine-tuning to incorporate new information, which could be more practical. The research paper “Towards Flexible Perception with Visual Memory” by Geirhos et… Read More »Google DeepMind Researchers Propose a Dynamic Visual Memory for Flexible Image Classification Shreya Maji Artificial Intelligence Category – MarkTechPost

Understanding the 27 Unique Challenges in Large Language Model Development: An Empirical Study of Over 29,000 Developer Forum Posts and 54% Unresolved Issues Asif Razzaq Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” LLMs have revolutionized artificial intelligence, particularly natural language processing and software engineering. Models useful for specific tasks such as generating, understanding, and translating text are being integrated into many applications. Because of their nature, LLMs, like OpenAI’s ChatGPT and GPT-4, have interacted extensively with… Read More »Understanding the 27 Unique Challenges in Large Language Model Development: An Empirical Study of Over 29,000 Developer Forum Posts and 54% Unresolved Issues Asif Razzaq Artificial Intelligence Category – MarkTechPost

The Challenges of Implementing Retrieval Augmented Generation (RAG) in Production Tanya Malhotra Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” In the field of Natural Language Processing (NLP), Retrieval Augmented Generation, or RAG, has attracted much attention lately. Breaking down documents into chunks, embedding those chunks, storing the embeddings, and then finding the closest match and adding it to the query context when receiving… Read More »The Challenges of Implementing Retrieval Augmented Generation (RAG) in Production Tanya Malhotra Artificial Intelligence Category – MarkTechPost

FlexEval: An Open-Source AI Tool for Chatbot Performance Evaluation and Dialogue Analysis Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

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​[[{“value”:” A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand and generate human-like text. It’s trained on vast amounts of data, enabling it to perform various natural language processing tasks, such as answering questions, summarizing content, and engaging in… Read More »FlexEval: An Open-Source AI Tool for Chatbot Performance Evaluation and Dialogue Analysis Mahmoud Ghorbel Artificial Intelligence Category – MarkTechPost

Can You Remove the Downstream Model for Speaker Recognition with Self-Supervised Speech Features? Apple Machine Learning Research

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​Self-supervised features are typically used in place of filter-bank features in speaker verification models. However, these models were originally designed to ingest filter-banks as inputs, and thus, training them on self-supervised features assumes that both feature types require the same amount of learning for the… Read More »Can You Remove the Downstream Model for Speaker Recognition with Self-Supervised Speech Features? Apple Machine Learning Research