Understanding generative AI models. Generative AI models are AI systems designed to create new content that resembles existing data. While traditional AI models specialize in classifying and analyzing ...

Large language models and small language models will play different roles in ensuring that we deliver valuable generative AI applications at cost-effective levels. Topics Spotlight: AI-ready data ...

Here are some common AI types: Traditional AI automates and optimizes specific tasks. Because it relies on ML models with predefined rules and algorithms, it’s most widely used in industries for ...

Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today.

Multimodal AI models are at the forefront of generative AI advancements. Unlike traditional models that process a single type of data, multimodal AI integrates text, images, and audio to provide a ...

Images, text, or videos are abundant, the researchers explain, and they can be used to train "traditional" generative AI algorithms. However, when it comes to 3D models, specific assets are not as ...

Generative AI models face data drift as patterns change, impacting accuracy. Continuous monitoring, retraining, and feature engineering keep models reliable.

Generative models provide a breakthrough solution. Figure 7 illustrates how MarS can simulate market impact: the top left shows how buy orders affect asset price trajectories, while the top right ...

Artificial intelligence startup and MIT spinoff Liquid AI Inc. today launched its first set of generative AI models, and they’re notably different from competing models because they’re built ...