AI content generation is about feeding your AI models with semantic and contextual information. The result is a platform that can ‘understand’ what an item is, and how it should be used. AI creates content using semantic knowledge in any form of content including video, 3d, VR and more.
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Latest Artificial Intelligence Content News
Evaluating Sample Utility for Data Selection by Mimicking Model Weights
Foundation models are trained on large-scale web-crawled datasets, which often contain noise, biases, and irrelevant information. This motivates the use of data selection techniques, which can be divided into model-free variants — relying on heuristic rules and downstream datasets — and model-based, e.g., using influence functions. The former can be…
Generate synthetic counterparty (CR) risk data with generative AI using Amazon Bedrock LLMs and RAG
Data is the lifeblood of modern applications, driving everything from application testing to machine learning (ML) model training and evaluation. As data demands continue to surge, the emergence of generative AI models presents an innovative solution. These large language models (LLMs), trained on expansive data corpora, possess the remarkable capability…
An SRE’s guide to optimizing ML systems with MLOps pipelines
Picture this: you’re an Site Reliability Engineer (SRE) responsible for the systems that power your company’s machine learning (ML) services. What do you do to ensure you have a reliable ML service, how do you know you’re doing it well, and how can you build strong systems to support these…
It’s a Sign: AI Platform for Teaching American Sign Language Aims to Bridge Communication Gaps
American Sign Language is the third most prevalent language in the United States — but there are vastly fewer AI tools developed with ASL data than data representing the country’s most common languages, English and Spanish. NVIDIA, the American Society for Deaf Children and creative agency Hello Monday are helping…