​[[{“value”:” Generative artificial intelligence (AI) models have become increasingly popular and powerful, enabling a wide range of applications such as text generation, summarization, question answering, and code generation. However, despite their impressive capabilities, these models often struggle with domain-specific tasks or use cases due to… Read More »Fine-tune Llama 3 for text generation on Amazon SageMaker JumpStart Ben Friebe AWS Machine Learning Blog

​[[{“value”:” Generative artificial intelligence (AI) applications powered by large language models (LLMs) are rapidly gaining traction for question answering use cases. From internal knowledge bases for customer support to external conversational AI assistants, these applications use LLMs to provide human-like responses to natural language queries.… Read More »Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval Samantha Stuart AWS Machine Learning Blog

​[[{“value”:” Integrating advanced predictive models into autonomous driving systems has become crucial for enhancing safety and efficiency. Camera-based video prediction emerges as a pivotal component, offering rich real-world data. Content generated by artificial intelligence is presently a leading area of study within the domains of… Read More »DriveGenVLM: Advancing Autonomous Driving with Generated Videos and Vision Language Models VLMs Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Document conversion, particularly from PDF to machine-processable formats, has long presented significant challenges due to PDF files’ diverse and often complex nature. These documents, widely used across various industries, frequently need more standardization, resulting in a loss of structural features when optimized for printing.… Read More »IBM Research Open-Sources Docling: An AI Tool for High-Precision PDF Document Conversion and Structural Integrity Maintenance Across Complex Layouts Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Machine learning models, especially those designed for code generation, heavily depend on high-quality data during pretraining. This field has seen rapid advancement, with large language models (LLMs) trained on extensive datasets containing code from various sources. The challenge for researchers is to ensure that… Read More »Snowflake AI Research Introduces Arctic-SnowCoder-1.3B: A New 1.3B Model that is SOTA Among Small Language Models for Code Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Sequential Propagation of Chaos (SPoC) is a recent technique for solving mean-field stochastic differential equations (SDEs) and their associated nonlinear Fokker-Planck equations. These equations describe the evolution of probability distributions influenced by random noise and are vital in fields like fluid dynamics and biology.… Read More »DeepSPoC: Integrating Sequential Propagation of Chaos with Deep Learning for Efficient Solutions of Mean-Field Stochastic Differential Equations Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Spiking Neural Networks (SNNs), a family of artificial neural networks that mimic the spiking behavior of biological neurons, have been in discussion in recent times. These networks provide a fresh method for working with temporal data, identifying the complex relationships and patterns seen in… Read More »Microsoft Research Suggests Energy-Efficient Time-Series Forecasting with Spiking Neural Networks Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” With the vast amount of online data, finding relevant information quickly can be a major challenge. Traditional search engines may not often provide precise and contextually accurate results, especially for complex queries or specific topics. Users frequently need help retrieving pertinent and useful information,… Read More »OpenPerPlex: A New Open-Source AI Search Engine that Leverages Cutting-Edge Technologies to Provide Search Capabilities over the Web Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Researchers from the University of Wisconsin-Madison addressed the critical challenge of performance variability in GPU-accelerated machine learning (ML) workloads within large-scale computing clusters. Performance variability in these environments arises due to several factors, including hardware heterogeneity, software optimizations, and the data-dependent nature of ML… Read More »PAL: A Novel Cluster Scheduler that Uses Application-Specific Variability Characterization to Intelligently Perform Variability-Aware GPU Allocation Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost