​[[{“value”:” Recent advances in autoregressive language models have brought about an amazing transformation in the field of Natural Language Processing (NLP). These models, such as GPT and others, have exhibited excellent performance in text creation tasks, including question-answering and summarization. However, their high inference latency… Read More »Researchers from KAIST and Google AI Introduce Blockwise Parallel Decoding (BCD): An AI Method for Rescoring Algorithms for Improved Efficiency and Fluency in Language Models Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Adrian Boeh, Senior Data Scientist – NAM AI, from Schneider Electric. Schneider Electric is a global leader in the digital transformation of energy management and… Read More »How Schneider Electric uses Amazon Bedrock to identify high-potential business opportunities Anthony Medeiros AWS Machine Learning Blog

​[[{“value”:” Species distribution modeling (SDM) has become an indispensable tool in ecological research, enabling scientists to predict species distribution patterns across geographic regions using environmental and observational data. These models help analyze the impact of environmental factors and human activities on species occurrence and abundance,… Read More »MALPOLON: A Cutting-Edge AI Framework Designed to Enhance Species Distribution Modeling Through the Integration of Geospatial Data and Deep Learning Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large enterprises are building strategies to harness the power of generative AI across their organizations. However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational… Read More »Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock Akarsha Sehwag AWS Machine Learning Blog

​[[{“value”:” Personalization can improve the user experience of shopping, entertainment, and news sites by using our past behavior to recommend the products and content that best match our interests. You can also apply personalization to conversational interactions with an AI-powered assistant. For example, an AI… Read More »Elevate workforce productivity through seamless personalization in Amazon Q Business James Jory AWS Machine Learning Blog

​[[{“value”:” Building intelligent agents that can accurately understand and respond to user queries is a complex undertaking that requires careful planning and execution across multiple stages. Whether you are developing a customer service chatbot or a virtual assistant, there are numerous considerations to keep in… Read More »Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1 Maira Ladeira Tanke AWS Machine Learning Blog

​[[{“value”:” CopilotKit has emerged as a leading open-source framework designed to streamline the integration of AI into modern applications. Widely appreciated within the open-source community, CopilotKit has garnered significant recognition, boasting over 10.5k+ GitHub stars. The platform enables developers to create custom AI copilots, in-app… Read More »CopilotKit’s CoAgents: The Missing Link that Makes It Easy to Connect LangGraph Agents to Humans in the Loop Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Biomedical vision models are increasingly used in clinical settings, but a significant challenge is their inability to generalize effectively due to dataset shifts—discrepancies between training data and real-world scenarios. These shifts arise from differences in image acquisition, changes in disease manifestations, and population variance.… Read More »Microsoft Researchers Unveil RadEdit: Stress-testing Biomedical Vision Models via Diffusion Image Editing to Eliminate Dataset Bias Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” LLMs, characterized by their massive parameter sizes, often lead to inefficiencies in deployment due to high memory and computational demands. One practical solution is semi-structured pruning, particularly the N: M sparsity pattern, which enhances efficiency by maintaining N non-zero values among M parameters. While… Read More »MaskLLM: A Learnable AI Method that Facilitates End-to End Training of LLM Sparsity on Large-Scale Datasets Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have garnered significant attention for their ability to understand and generate human-like text. These models possess the unique capability to encode factual knowledge effectively, thanks to the vast amount of data they are trained on. This ability is crucial in… Read More »This AI Paper from KAIST, UCL and KT Investigates the Acquisition and Retention of Factual Knowledge in Large Language Models Nikhil Artificial Intelligence Category – MarkTechPost