Demonstrates cloud-based large language models (LLMs) generative AI, comparing OpenAI ChatGPT against Anthropic Claude.
Large Language Model Comparison
![](https://ride.ict.usc.edu/wp-content/uploads/2023/12/ExampleLLM-1200x675.png)
Demonstrates cloud-based large language models (LLMs) generative AI, comparing OpenAI ChatGPT against Anthropic Claude.
Demonstrates cloud-based text-to-image generative AI, comparing OpenAI DALL-E against Stability AI Stable Diffusion.
Collects available entity prefabs for inspection, modification and testing.
Shows how to leverage commodity audio-visual sensing AI services through REST calls, using RIDE’s common web services system.
Shows how to send GET, PUT, POST, and web requests through RIDE’s common web services system.
This example demonstrates how to use Google and Facebook OAuth authentication systems within RIDE.
Demonstrates the integration of cloud-based Natural Language Processing services for comparison within a Q & A format.
The RIDE ATLAS (Aerial Terrain Line of Sight Analysis System) integration represents an improved package of ATLAS rebuilt within RIDE.
This example demonstrates how to examine and run unit tests on various Machine Learning models residing within/outside RIDE backed with Unity Barracuda framework.
Demonstrates how to use Unity’s Timeline package with the RIDE API’s mechanics.