[[{“value”:” Since its launch in 2018, Just Walk Out technology by Amazon has transformed the shopping experience by allowing customers to enter a store, pick up items, and leave without standing in line to pay. You can find this checkout-free technology in over 180 third-party… Read More »Enhancing Just Walk Out technology with multi-modal AI Tian Lan AWS Machine Learning Blog
[[{“value”:” Large language models (LLMs) have gained significant attention due to their potential to enhance various artificial intelligence applications, particularly in natural language processing. When integrated into frameworks like Retrieval-Augmented Generation (RAG), these models aim to refine AI systems’ output by drawing information from external… Read More »Trust-Align: An AI Framework for Improving the Trustworthiness of Retrieval-Augmented Generation in Large Language Models Nikhil Artificial Intelligence Category – MarkTechPost
Tomorrow, September 24, 2024, San Francisco will host one of the biggest global AI events of the year: the Chatbot Conference! Whether you’re passionate about artificial intelligence, curious about chatbots, or simply eager to connect with industry leaders, this conference is for you. Why You… Read More »Be Part of the AI Revolution at the Chatbot Conference Tomorrow! Cassandra C. Becoming Human: Artificial Intelligence Magazine – Medium
The future of AI is happening now, and we want you to be a part of it! Tomorrow, September 24, 2024, the global Chatbot Conference kicks off in San Francisco, gathering the brightest minds in AI, machine learning, and conversational interfaces. This is your… Read More »Join Us Tomorrow at the Global Chatbot Conference in San Francisco! Cassandra C. Chatbots Life – Medium
[[{“value”:” Evaluating your Retrieval Augmented Generation (RAG) system to make sure it fulfils your business requirements is paramount before deploying it to production environments. However, this requires acquiring a high-quality dataset of real-world question-answer pairs, which can be a daunting task, especially in the early… Read More »Generate synthetic data for evaluating RAG systems using Amazon Bedrock Lukas Wenzel AWS Machine Learning Blog
[[{“value”:” State and local agencies spend approximately $1.23 billion annually to operate and maintain signalized traffic intersections. On the other end, traffic congestion at intersections costs drivers about $22 billion annually. Implementing an artificial intelligence (AI)-powered detection-based solution can significantly mitigate congestion at intersections and… Read More »Making traffic lights more efficient with Amazon Rekognition Colin Chu AWS Machine Learning Blog
[[{“value”:” Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. Data scientists face numerous challenges throughout this process, such as selecting appropriate tools, needing step-by-step instructions with code samples, and troubleshooting errors and… Read More »Accelerate development of ML workflows with Amazon Q Developer in Amazon SageMaker Studio James Wu AWS Machine Learning Blog
[[{“value”:” With the rise of powerful foundation models (FMs) powered by services such as Amazon Bedrock and Amazon SageMaker JumpStart, enterprises want to exercise granular control over which users and groups can access and use these models. This is crucial for compliance, security, and governance.… Read More »Govern generative AI in the enterprise with Amazon SageMaker Canvas Saptarshi Banerjee AWS Machine Learning Blog
[[{“value”:” This post is co-written with Josh Zook and Alex Hamilton from Rocket Mortgage. Rocket Mortgage, America’s largest retail mortgage lender, revolutionizes homeownership with Rocket Logic – Synopsis, an AI tool built on AWS. This innovation has transformed client interactions and operational efficiency through the… Read More »Transforming home ownership with Amazon Transcribe Call Analytics, Amazon Comprehend, and Amazon Bedrock: Rocket Mortgage’s journey with AWS Josh Zook AWS Machine Learning Blog
[[{“value”:” Building massive neural network models that replicate the activity of the brain has long been a cornerstone of computational neuroscience’s efforts to understand the complexities of brain function. These models, which are frequently intricate, are essential for comprehending how neural networks give rise to… Read More »Spiking Network Optimization Using Population Statistics (SNOPS): A Machine Learning-Driven Framework that can Quickly and Accurately Customize Models that Reproduce Activity to Mimic What’s Observed in the Brain Tanya Malhotra Artificial Intelligence Category – MarkTechPost