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
SenseNova-U1 just dropped — native multimodal gen/understanding in one model, no VAE, no diffusion
What’s new: Text rendering in images actually works. Diffusion models scramble text because they don’t have a language understanding pathway. U1 does — because it’s natively multimodal. Posters with long titles, slides with bullet points, comics with speech bubbles — all clean. Infographics & dense visual output — posters, annotated…
Adaptive Thinking: Large Language Models Know When to Think in Latent Space
Recent advances in large language models (LLMs) test-time computing have introduced the capability to perform intermediate chain-of-thought (CoT) reasoning (thinking) before generating answers. While increasing the thinking budget yields smooth performance improvements at inference time, the relationship between LLM capability, query complexity, and optimal budget allocation remains poorly understood for…
Extracting contract insights with PwC’s AI-driven annotation on AWS
This post was co-written with Yash Munsadwala, Adam Hood, Justin Guse, and Hector Hernandez from PwC. Contract analysis often consumes significant time for legal, compliance, and procurement teams, especially when important insights are buried in lengthy, unstructured agreements. As contract volumes grow, finding specific clauses and assessing extracted terms can…