​[[{“value”:” Seamless integration of customer experience, collaboration tools, and relevant data is the foundation for delivering knowledge-based productivity gains. In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where… Read More »Create a generative AI assistant with Slack and Amazon Bedrock Barry Conway AWS Machine Learning Blog

​[[{“value”:” Computer vision is revolutionizing due to the development of foundation models in object recognition, image segmentation, and monocular depth estimation, showing strong zero- and few-shot performance across various downstream tasks. Stereo matching, which helps perceive depth and create 3D views of scenes, is crucial… Read More »StereoAnything: A Highly Practical AI Solution for Robust Stereo Matching Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The development of AI agents as autonomous tools capable of handling complex tasks has led to a significant advancement in artificial intelligence. Foundry, a Y Combinator-backed startup, aims to be the “Operating System” for AI agents, making AI automation more accessible, manageable, and scalable.… Read More »Meet Foundry: An AI Startup that Builds, Evaluates, and Improves AI Agents Shobha Kakkar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Cell segmentation and classification are vital tasks in spatial omics data analysis, which provides unprecedented insights into cellular structures and tissue functions. Recent advancements in spatial omics technologies have enabled high-resolution analysis of intact tissues, supporting initiatives like the Human Tumor Atlas Network and… Read More »CelloType: A Transformer-Based AI Framework for Multitask Cell Segmentation and Classification in Spatial Omics Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In AI, a key challenge lies in improving the efficiency of systems that process unstructured datasets to extract valuable insights. This involves enhancing retrieval-augmented generation (RAG) tools, combining traditional search and AI-driven analysis to answer localized and overarching queries. These advancements address diverse questions,… Read More »Microsoft AI Introduces LazyGraphRAG: A New AI Approach to Graph-Enabled RAG that Needs No Prior Summarization of Source Data Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have transformed the development of agent-based systems for good. However, managing memory in these systems remains a complex challenge. Memory mechanisms enable agents to maintain context, recall important information, and interact more naturally over extended periods. While many frameworks assume… Read More »Exploring Memory Options for Agent-Based Systems: A Comprehensive Overview Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent years, there has been a growing demand for machine learning models capable of handling visual and language tasks effectively, without relying on large, cumbersome infrastructure. The challenge lies in balancing performance with resource requirements, particularly for devices like laptops, consumer GPUs, or… Read More »Hugging Face Releases SmolVLM: A 2B Parameter Vision-Language Model for On-Device Inference Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Thousands of companies worldwide use Salesforce to manage their sales, marketing, customer service, and other business operations. The Salesforce cloud-based platform centralizes customer information and interactions across the organization, providing sales reps, marketers, and support agents with a unified 360-degree view of each customer.… Read More »Unleash your Salesforce data using the Amazon Q Salesforce Online connector Mehdy Haghy AWS Machine Learning Blog

​[[{“value”:” Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. This can occur when the model’s training data lacks the necessary information or when the model attempts to generate coherent… Read More »Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents Shayan Ray AWS Machine Learning Blog

​[[{“value”:” With the rise of large language models (LLMs) like Meta Llama 3.1, there is an increasing need for scalable, reliable, and cost-effective solutions to deploy and serve these models. AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS),… Read More »Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM Maurits de Groot AWS Machine Learning Blog