​[[{“value”:” Microsoft has unveiled an extensive AI learning journey designed to deal with the diverse needs of various personas within a business, ranging from business leaders to citizen developers. This initiative is structured into four stages: Understanding AI, Preparing for AI, Using AI, and Building… Read More »Microsoft’s Comprehensive Four-Stage AI Learning Journey: Empowering Businesses with Skills for Effective AI Integration and Innovation Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The research on vision-language models (VLMs) has gained significant momentum, driven by their potential to revolutionize various applications, including visual assistance for visually impaired individuals. However, current evaluations of these models often need to pay more attention to the complexities introduced by multi-object scenarios… Read More »Enhancing Vision-Language Models: Addressing Multi-Object Hallucination and Cultural Inclusivity for Improved Visual Assistance in Diverse Contexts Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graph comprehension and complex reasoning in artificial intelligence involve developing and evaluating the abilities of Large Language Models (LLMs) to understand and reason about graph-structured data. This field is critical for various applications, including social network analysis, drug discovery, recommendation systems, and spatiotemporal predictions.… Read More »GraCoRe: A New AI Benchmark for Unveiling Strengths and Weaknesses in LLM Graph Comprehension and Reasoning Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Accurately modeling magnetic hysteresis is a significant challenge in the field of AI, especially for optimizing the performance of magnetic devices such as electric machines and actuators. Traditional methods often struggle to generalize to novel magnetic fields, limiting their effectiveness in real-world applications. Addressing… Read More »This Paper Addresses the Generalization Challenge by Proposing Neural Operators for Modeling Constitutive Laws Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) with parametric memory of rules and knowledge have shown limitations in implicit reasoning. Research has shown that these models, even more complex ones like GPT-4, have trouble applying and integrating internalized facts reliably. For instance, even when they are aware… Read More »This AI Research from Ohio State University and CMU Discusses Implicit Reasoning in Transformers And Achieving Generalization Through Grokking Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Complex Human Activity Recognition (CHAR) in ubiquitous computing, particularly in smart environments, presents significant challenges due to the labor-intensive and error-prone process of labeling datasets with precise temporal information of atomic activities. This task becomes impractical in real-world scenarios where accurate and detailed labeling… Read More »VCHAR: A Novel Artificial Intelligence AI Framework that Treats the Outputs of Atomic Activities as a Distribution Over Specified Intervals Shreya Maji Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In a recent study by Innodata, various large language models (LLMs) such as Llama2, Mistral, Gemma, and GPT were benchmarked for their performance in factuality, toxicity, bias, and propensity for hallucinations. The research introduced fourteen novel datasets designed to evaluate the safety of these… Read More »Innodata’s Comprehensive Benchmarking of Llama2, Mistral, Gemma, and GPT for Factuality, Toxicity, Bias, and Hallucination Propensity Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have demonstrated remarkable performance across various tasks, with reasoning capabilities being a crucial aspect of their development. However, the key elements driving these improvements remain unclear. Currently, the primary approaches to enhance reasoning involve increasing model size and expanding context… Read More »This AI Research from Tenyx Explore the Reasoning Abilities of Large Language Models (LLMs) Through Their Geometrical Understanding Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” VLMs like LLaVA-Med have advanced significantly, offering multi-modal capabilities for biomedical image and data analysis, which could aid radiologists. However, these models face challenges, such as hallucinations and imprecision in responses, leading to potential misdiagnoses. With radiology departments experiencing increased workloads and radiologists facing… Read More »D-Rax: Enhancing Radiologic Precision through Expert-Integrated Vision-Language Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​ Dive into the world of prompt engineering and see how these powerful tools can complement your skills. Continue reading on Becoming Human: Artificial Intelligence Magazine »  Dive into the world of prompt engineering and see how these powerful tools can complement your skills.Continue reading… Read More »Mastering Prompt Engineering: Leveraging the Power of Generative AI Niño Ross Rodriguez Becoming Human: Artificial Intelligence Magazine – Medium