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
Update: Distilled v1.1 is live
We’ve pushed an LTX-2.3 update today. The Distilled model has been retrained (now v1.1) with improvements to audio quality and a slightly refined visual aesthetic. It’s available on HuggingFace alongside the previous Distilled version. Along with the new checkpoint, we’ve also retrained the distilled LoRA, updated all four ComfyUI example…
How to Implement Tool Calling with Gemma 4 and Python
The open-weights model ecosystem shifted recently with the release of the
Structured Outputs vs. Function Calling: Which Should Your Agent Use?
Language models (LMs), at their core, are text-in and text-out systems.
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models at ICLR 2026. Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on knowledge-intensive tasks. In this paper, we formalize fact memorization from…