Multi-Modal AI Agents: Integrating Text, Image, and Speech Training Course
Course Outline
Introduction to Multi-Modal AI for Government
- Definition of multi-modal AI
- Key challenges and applications in the public sector
- Overview of leading multi-modal models for government use
Text Processing and Natural Language Understanding for Government
- Leveraging large language models (LLMs) for text-based AI agents in public sector operations
- Techniques for prompt engineering to enhance multi-modal tasks for government applications
- Fine-tuning text models for domain-specific needs within the government context
Image Recognition and Generation for Government
- Utilizing AI for image processing: classification, captioning, and object detection in public sector scenarios
- Generating images with advanced diffusion models (Stable Diffusion, DALLE) for government use cases
- Integrating image data with text-based models to enhance governmental operations
Speech and Audio Processing for Government
- Speech recognition using Whisper ASR for public sector applications
- Text-to-speech (TTS) synthesis techniques tailored for government communication
- Enhancing user interaction with voice-based AI in governmental services
Integrating Multi-Modal Inputs for Government
- Building AI pipelines to process multiple input types for efficient public sector operations
- Fusion techniques to combine text, image, and speech data for comprehensive analysis
- Real-world applications of multi-modal AI agents in government agencies
Deploying Multi-Modal AI Agents for Government
- Developing API-driven multi-modal AI solutions for government systems
- Optimizing models to ensure performance and scalability in public sector environments
- Best practices for deploying multi-modal AI in production within governmental frameworks
Ethical Considerations and Future Trends for Government
- Addressing bias and fairness in multi-modal AI applications for government
- Managing privacy concerns with multi-modal data in the public sector
- Anticipating future developments in multi-modal AI for governmental use
Summary and Next Steps for Government
Requirements
- An understanding of machine learning fundamentals for government applications
- Experience with Python programming
- Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch)
Audience
- AI developers for government projects
- Researchers in public sector institutions
- Multimedia engineers working on government initiatives
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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