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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The realism that you wanted – Z Image Base (and Turbo) LoRA
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Document Clustering with LLM Embeddings in Scikit-learn
Imagine that you suddenly obtain a large collection of unclassified documents and are tasked with grouping them by topic.
Parallel Track Transformers: Enabling Fast GPU Inference with Reduced Synchronization
Efficient large-scale inference of transformer-based large language models (LLMs) remains a fundamental systems challenge, frequently requiring multi-GPU parallelism to meet stringent latency and throughput targets. Conventional tensor parallelism decomposes matrix operations across devices but introduces substantial inter-GPU synchronization, leading to communication bottlenecks and degraded scalability. We propose the Parallel Track…
How Amazon uses Amazon Nova models to automate operational readiness testing for new fulfillment centers
Amazon is a global ecommerce and technology company that operates a vast network of fulfillment centers to store, process, and ship products to customers worldwide. The Amazon Global Engineering Services (GES) team is responsible for facilitating operational readiness across the company’s rapidly expanding network of fulfillment centers. When launching new…