https://github.com/timothywarner-org/multimodal-ai

Multimodal AI: How Machines Learn to See, Hear, and Understand Together
https://github.com/timothywarner-org/multimodal-ai

agentic-ai agentic-rag agentic-workflow copilot-agent copilot-coding-agent large-language-models m365 m365-copilot multimodal-large-language-models

Last synced: about 1 month ago
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Multimodal AI: How Machines Learn to See, Hear, and Understand Together

• Host: GitHub
• URL: https://github.com/timothywarner-org/multimodal-ai
• Owner: timothywarner-org
• License: mit
• Created: 2025-11-24T18:08:42.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2025-12-02T13:16:48.000Z (4 months ago)
• Last Synced: 2025-12-05T09:28:27.770Z (3 months ago)
• Topics: agentic-ai, agentic-rag, agentic-workflow, copilot-agent, copilot-coding-agent, large-language-models, m365, m365-copilot, multimodal-large-language-models
• Homepage: https://techtrainertim.com
• Size: 32.4 MB
• Stars: 4
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md
  • Governance: governance/agentic-ai-guardrails.md

Awesome Lists containing this project

README

          
# Multimodal AI: How Machines Learn to See, Hear, and Understand Together

[![YouTube](https://img.shields.io/badge/YouTube-Watch%20Video-red?style=for-the-badge&logo=youtube)](https://www.youtube.com/watch?v=3jZ_lzsgWTM)

[![Lychee Link Checker](https://github.com/timothywarner-org/multimodal-ai/actions/workflows/lychee-link-check.yml/badge.svg)](https://github.com/timothywarner-org/multimodal-ai/actions/workflows/lychee-link-check.yml)

[![Markdown Linter](https://github.com/timothywarner-org/multimodal-ai/actions/workflows/markdown-linter.yml/badge.svg)](https://github.com/timothywarner-org/multimodal-ai/actions/workflows/markdown-linter.yml)

## Tim's Contact Info

* 📧 [Email Tim](mailto:timothywarner316@gmail.com)

* 🌐 [Visit Tim's Website](https://techtrainertim.com)

* 💼 [Connect on LinkedIn](https://www.linkedin.com/in/timothywarner)

* 🎥 [Subscribe to Tim's YouTube Channel](https://www.youtube.com/channel/UCim7PFtynyPuzMHtbNyYOXA)

* 🐙 [Check Out Tim's GitHub Profile](https://github.com/timothywarner)

* 🏢 [Explore Tim's GitHub Organization](https://github.com/timothywarner-org)

## Session Overview

AI is no longer just about text. Today's systems can take in words, images, audio, and even live video,

making sense of them all at once. This session focuses on practical applications within the

Microsoft 365 Copilot ecosystem, where you can immediately apply these capabilities. We'll explore how

Copilot in Microsoft 365 uses multimodal understanding to enhance productivity, then examine comparable

examples from Google, Anthropic, and OpenAI to illustrate how different approaches solve similar

challenges. You'll gain a clear understanding of multimodal AI fundamentals, see real-world workflows,

and learn key governance and ethical considerations. Expect practical demos, industry examples, and

hands-on guidance you can use immediately. We'll close with an interactive Q&A session.

### Learning Objectives

By the end of this session, you will be able to:

* Understand what multimodal AI is and why it's essential for modern knowledge work.

* Leverage Microsoft 365 Copilot's multimodal capabilities to enhance productivity with text,

images, and data.

* Recognize how similar multimodal approaches work across Google, Anthropic, and OpenAI platforms

for broader perspective.

* Identify practical use cases and integration patterns within your Microsoft 365 environment.

* Apply governance, responsible AI, and ethical considerations when deploying multimodal AI solutions.

* Begin experimenting with multimodal capabilities in your organization's Microsoft 365 workflow.

## Structure

* 45 minutes presentation

* 10 minutes of Q&A