Multimodal AI for Smart Assistants and Virtual Agents

• Basic understanding of AI and machine learning
• Experience with Python programming
• Familiarity with APIs and cloud-based AI services

Audience

• Product designers
• Software engineers
• Customer support professionals

Multimodal AI is transforming virtual assistants by integrating text, speech, and visual inputs for more natural and interactive user experiences. This course explores how AI-powered smart assistants like ChatGPT, Google Assistant, and Alexa utilize multimodal capabilities to improve engagement and responsiveness.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level product designers, software engineers, and customer support professionals who wish to enhance virtual assistants with multimodal AI.

By the end of this training, participants will be able to:

• Understand how multimodal AI enhances virtual assistants.
• Integrate speech, text, and image processing in AI-powered assistants.
• Build interactive conversational agents with voice and vision capabilities.
• Utilize APIs for speech recognition, NLP, and computer vision.
• Implement AI-driven automation for customer support and user interaction.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Multimodal AI for Smart Assistants

• What is multimodal AI?
• Applications of multimodal AI in virtual assistants
• Overview of AI-powered assistants (ChatGPT, Google Assistant, Alexa, etc.)

Understanding Speech Recognition and NLP

• Speech-to-text and text-to-speech conversion
• Natural Language Processing (NLP) for conversational AI
• Sentiment analysis and intent recognition

Integrating Computer Vision for Smart Assistants

• Image recognition and object detection
• Facial recognition and sentiment detection
• Use cases: Virtual agents with visual capabilities

Multimodal Fusion: Combining Voice, Text, and Vision

• How multimodal AI processes multiple inputs
• Designing seamless interactions across modalities
• Case studies: AI-powered virtual agents with multimodal interfaces

Building a Multimodal Virtual Assistant

• Setting up a conversational AI framework
• Connecting speech recognition, NLP, and vision APIs
• Developing a prototype smart assistant

Deploying AI-Powered Assistants in Real-World Applications

• Integrating virtual agents into websites and mobile apps
• AI-driven automation for customer support and user experience
• Monitoring and improving AI assistant performance

Challenges and Ethical Considerations

• Privacy and data security in AI-driven assistants
• Bias and fairness in AI interactions
• Regulatory compliance for AI-powered assistants

Future Trends in Multimodal AI for Smart Assistants

• Advancements in AI-driven conversation models
• Personalization and adaptive learning in virtual agents
• AI’s evolving role in human-computer interaction

Summary and Next Steps