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
AI chatbots can be as effective as humans at emotional support—sometimes better
New research led by The University of Manchester in collaboration with Durham University has found that AI chatbots such as ChatGPT can match—and in some situations outperform—humans as a source of everyday emotional support. However, the advantage depends on the emotional context, and a key ingredient for effective support—offering specific,…
The Current State of Agentic AI
In this article, you will learn how agentic AI architecture has evolved by mid-2026, including the shift away from orchestrated reasoning loops, the rise of…
Environment-free Synthetic Data Generation for API-Calling Agents
Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully implemented environments with executable APIs and realistic, pre-populated backend databases, creating a major bottleneck for scalability. To overcome this, we propose an environment-free synthetic data generation approach that…
Exploring self-distilled reasoning for supervised fine-tuning with Amazon Nova
When you fine-tune a model using Supervised Fine-Tuning (SFT), creating high-quality chain-of-thought (CoT) reasoning traces for your training data is often impractical and can be prohibitively expensive. As a result, you might choose to skip reasoning during SFT and train with only inputs and outputs. However, reasoning is a key…