AI Glossary of Terms
Conversational AI
Conversational AI refers to the development and use of artificial intelligence technologies that enable computers and machines to communicate with humans in a natural, conversational way. It involves creating intelligent chatbots and virtual assistants that can understand human language, respond to questions and commands, and engage in back-and-forth conversation with users.
Conversational AI technologies typically involve natural language processing (NLP), machine learning, and other advanced techniques that allow computers to understand and interpret human language. They can be used in a variety of applications, such as customer service, healthcare, education, and entertainment.
The goal of conversational AI is to create a more human-like interaction between humans and machines, making it easier for people to communicate with computers and get the information and assistance they need. As technology continues to advance, conversational AI is becoming more sophisticated and capable of handling complex interactions and tasks.
Example: ChatGPT-4
Google LaMDA
Googles Proprietary Language Model for Dialogue Applications - Used in the Google Bard chatbot
Example: Google Bard
Latent Diffusion Model
Latent Diffusion Model is a type of generative model used in machine learning to learn the underlying structure of a dataset. It is a type of probabilistic model that can be used for a variety of tasks, such as data generation, unsupervised learning, and anomaly detection.
In a Latent Diffusion Model, the data is assumed to be generated by a diffusion process through a high-dimensional latent space. The model is designed to capture the complex relationships between the observed data and the latent variables that generate them. This is achieved by using a series of diffusion steps, where the data is iteratively transformed through a sequence of conditional distributions that capture the dependencies between the latent variables.
Latent Diffusion Models have been applied in a range of domains, including image and text generation, video prediction, and anomaly detection. They have been shown to be effective at capturing complex patterns in high-dimensional data, and are an active area of research in machine learning.
Multimodal Chat
The feature to add pictures to a chat to ask for advice or analysis regarding the image.
Example: MiniGPT-4
StableLM
Open-source language model that can generate text and code with high performance in conversational and coding tasks. StableLM was developed by Stability AI.
Text to Video
An AI text-to-video generator often makes use of a machine learning technique called artificial neural networks that can receive input in the form of words, which it then processes to generate a video The entire process takes mere seconds, so you can see the results of your “work” immediately.
Text to Image
An AI text-to-image generator often makes use of a machine learning technique called artificial neural networks that can receive input in the form of words, which it then processes to generate an image. The entire process takes mere seconds, so you can see the results of your “work” immediately.
Image Segmentation
Identifying which image pixels belong to an object — is a core task in computer vision and is used in a broad array of applications, from analyzing scientific imagery to editing photos. But creating an accurate segmentation model for specific tasks typically requires highly specialized work by technical experts with access to AI training infrastructure and large volumes of carefully annotated in-domain data.
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