MODULAR ARTIFICIAL INTELLIGENCE PLATFORM FOR MEDIA GENERATION AND METHODS FOR USE THEREWITH

Smart overview of the Invention

The modular artificial intelligence platform is designed for media generation by processing both text and image data. It employs various AI modules to encode and decode input data, transforming it into new media content. This platform integrates advanced neural networks and language processing to create outputs that are based on the input data, such as text and images, while also incorporating concept structure data through graph-based learning.

System Structure

The platform operates over a network, which can be the Internet or other types of networks, to receive media inputs from various sources. These inputs are processed through multiple AI layers, including text and image encoder modules, a concept identification module, and corresponding decoder modules. The system is capable of generating enhanced media outputs that may include new content or responses to queries.

Addressing AI Challenges

One of the key aspects of this platform is its modular design, which aims to address common issues associated with AI systems, such as bias and lack of transparency. By providing explainable components and reliable outputs, the platform enhances accountability in AI-generated media. This design helps mitigate the risks associated with blackbox neural networks by ensuring that the decision-making processes are more transparent.

Components and Tools

• Text Encoder Module: Encodes text data using language processing AI.
• Image Encoder Module: Encodes image data using neural networks and long short-term memory.
• Concept Identification Module: Utilizes graph-based learning AI to generate concept structure data.
• Text and Image Decoder Modules: Generate media output based on encoded data and concept structures.

Functionality

The platform supports the development of training datasets using dataset development tools and maintains versions in a control repository. It employs machine learning analysis tools to evaluate AI models for bias and moral insights. The system's operations include receiving media input via network interfaces, encoding this input, generating concept structures, decoding the processed data, and combining it into comprehensive media outputs.