​[[{“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

​[[{“value”:” Large language models (LLMs) have advanced significantly in recent years. However, its real-world applications are restricted due to substantial processing power and memory requirements. The need to make LLMs more accessible on smaller and resource-limited devices drives the development of more efficient frameworks for… Read More »LightLLM: A Lightweight, Scalable, and High-Speed Python Framework for LLM Inference and Serving Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have made significant strides in various Natural Language Processing tasks, yet they still struggle with mathematics and complex logical reasoning. Chain-of-Thought (CoT) prompting has emerged as a promising approach to enhance reasoning capabilities by incorporating intermediate steps. However, LLMs often… Read More »Logic-of-Thought: Enhancing Logical Reasoning in Large Language Models through Propositional Logic Augmentation Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Instruction-tuned LMs have shown remarkable zero-shot generalization but often fail on tasks outside their training data. These LMs, built on large datasets and billions of parameters, excel in In-Context Learning (ICL), generating responses based on a few examples without re-training. However, the training dataset’s… Read More »Instructive Decoding (ID): A Novel AI Method that Enhances the Attention of Instruction-Tuned LLMs Towards Provided Instructions during the Generation Phase without Any Parameter Updates Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have gained significant attention due to their advanced capabilities in processing and generating text. However, the increasing demand for multimodal input processing has led to the development of vision language models. These models combine the strengths of LLMs with image… Read More »Self-Training on Image Comprehension (STIC): A Novel Self-Training Approach Designed to Enhance the Image Comprehension Capabilities of Large Vision Language Models (LVLMs) Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Over the last 18 months, AWS has announced more than twice as many machine learning (ML) and generative artificial intelligence (AI) features into general availability than the other major cloud providers combined. This accelerated innovation is enabling organizations of all sizes, from disruptive AI… Read More »AWS recognized as a first-time Leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms Susanne Seitinger AWS Machine Learning Blog