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​[[{“value”:” Large language models (LLMs) have demonstrated promising capabilities in machine translation (MT) tasks. Depending on the use case, they are able to compete with neural translation models such as Amazon Translate. LLMs particularly stand out for their natural ability to learn from the context… Read More »Evaluate large language models for your machine translation tasks on AWS Narcisse Zekpa AWS Machine Learning Blog

​[[{“value”:” This blog post is co-written with Siokhan Kouassi and Martin Gregory at Parameta.  When financial industry professionals need reliable over-the-counter (OTC) data solutions and advanced analytics, they can turn to Parameta Solutions, the data powerhouse behind TP ICAP . With a focus on data-led… Read More »Parameta accelerates client email resolution with Amazon Bedrock Flows Siokhan Kouassi AWS Machine Learning Blog

​[[{“value”:” Dense embedding-based text retrieval has become the cornerstone for ranking text passages in response to queries. The systems use deep learning models for embedding text into vector spaces that enable semantic similarity measurements. This method has been adopted widely in applications such as search… Read More »This AI Paper from Tel Aviv University Introduces GASLITE: A Gradient-Based Method to Expose Vulnerabilities in Dense Embedding-Based Text Retrieval Systems Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In a time when global health faces persistent threats from emerging pandemics, the need for advanced biosurveillance and pathogen detection systems is increasingly evident. Traditional genomic analysis methods, while effective in isolated cases, often struggle to address the complexities of large-scale health monitoring. A… Read More »Researchers from USC and Prime Intellect Released METAGENE-1: A 7B Parameter Autoregressive Transformer Model Trained on Over 1.5T DNA and RNA Base Pairs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In this post, we walk you through the process to build an automated mechanism using Amazon SageMaker to process your log data, run training iterations over it to obtain the best-performing anomaly detection model, and register it with the Amazon SageMaker Model Registry for… Read More »Efficiently build and tune custom log anomaly detection models with Amazon SageMaker Nitesh Sehwani AWS Machine Learning Blog

​[[{“value”:” When it comes to AI tools, chatbots are often the first thing that comes to mind —conversation-based interfaces for users to write queries and receive responses. These dialogue interfaces are certainly useful, but they aren’t always the best fit for handling our everyday work.… Read More »Meet Height: An Autonomous Project Management Platform Leading the Next Wave of AI Tools Asif Razzaq Artificial Intelligence Category – MarkTechPost

Many linguistic and visual difficulties have been helped by self-supervised pretraining. In the language and vision domains, where a unified model may be easily tailored to multiple downstream tasks by pretraining representations without explicit labeling, self-supervised pretraining has been the subject of substantial research. However,… Read More »Microsoft Research Proposes SMART: A Generic Pretraining Framework For Multi-Task Sequential Decision Making Tanushree Shenwai Artificial Intelligence Category – MarkTechPost

The exponentially expanding scale of deep learning models is a major force in advancing the state-of-the-art and a source of growing worry over the energy consumption, speed, and, therefore, feasibility of massive-scale deep learning. Recently, researchers from Cornell talked about Transformer topologies, particularly how they… Read More »What Happens If You Run A Transformer Model With An Optical Neural Network? Aneesh Tickoo Artificial Intelligence Category – MarkTechPost