November 7, 2025

Hi there

Good morning! In today’s issue, we’ll dig into the all of the latest moves and highlight what they mean for you right now. Along the way, you’ll find insights you can put to work immediately

— Ryan Rincon, Founder at The Wealth Wagon Inc.

If you think ChatGPT is impressive now, just wait until it can watch videos, interpret images, understand tone, and hold a conversation — all at once. That’s not the future. It’s happening right now, thanks to a breakthrough known as multimodal AI.

While traditional AI systems specialize in one type of data (like text or images), multimodal AI can process multiple forms of information simultaneously — words, visuals, sound, and even touch.

It’s the key to creating machines that can interact more naturally with humans — and it’s already transforming everything from healthcare and education to marketing and entertainment.

Let’s explore what multimodal AI is, how it works, and why it’s shaping the next generation of intelligent systems.

The word “multimodal” literally means “many modes.” In the AI world, that refers to different types of input data.

For example:

Multimodal AI combines these modes into a single system that can understand and generate responses across all of them.

Think of it like this:
If traditional AI is a one-trick pony (good at one thing), multimodal AI is a symphony conductor — coordinating multiple instruments of data to create harmony.

💡 Example: OpenAI’s GPT-4o (“o” for “omni”) can process text, images, and audio inputs in real time. That means you can show it a photo, ask it to describe what’s happening, and even hold a conversation about it — just like talking to a person.

At the core of multimodal AI are neural networks trained to connect different data types.

Here’s a simplified breakdown:

This type of learning mirrors how humans think: our brains don’t process information in silos. We use context — what we see, hear, and feel — all at once.

Multimodal AI isn’t just a cool tech demo — it’s already being used across industries.

AI can analyze medical scans, patient histories, and doctor notes together — improving diagnosis accuracy. For example, a system might combine MRI images with clinical data to detect early signs of diseases like Alzheimer’s or cancer.

Platforms like Khanmigo (powered by OpenAI) use multimodal AI to act as visual tutors — interpreting diagrams, explaining math problems step-by-step, and responding conversationally.

Imagine taking a photo of a product you love and instantly getting recommendations for similar items — that’s multimodal AI at work. It powers visual search tools like Google Lens and personalized shopping experiences.

For people with disabilities, multimodal AI can translate speech into text, describe visual environments aloud, or provide real-time sign language interpretation.

From text-to-video generators like Runway and Pika Labs to AI music composers, multimodal systems are fueling a new wave of digital art and storytelling.

Multimodal AI represents a major step toward human-like understanding. It’s no longer just about responding to commands — it’s about interpreting the context around those commands.

Here’s what that means:

In short, AI is becoming less of a tool and more of a collaborator.

As with all AI advancements, there are challenges to tackle:

That’s why transparency, regulation, and responsible training practices are critical as this technology expands.

The next evolution of multimodal systems is embodied AI — where intelligence lives inside physical robots that can perceive and act in the real world.

Picture a home assistant robot that recognizes faces, understands speech, and physically interacts with objects. Or industrial robots that “see” what needs fixing and do it automatically.

Companies like Tesla, Figure, and Agility Robotics are already developing humanoid robots powered by multimodal and generative AI models.

This is where AI begins to move — not just think.

Multimodal AI is making machines more human — not by giving them emotions, but by giving them understanding.

It’s the bridge between language, vision, and action — and it’s paving the way for a world where interacting with technology feels completely natural.

We’re heading into an era where AI won’t just answer your questions — it’ll see what you mean.

And that, more than anything, might be the moment artificial intelligence truly becomes intelligent.

I hope you enjoyed today’s issue of The Wealth Wagon. If you have any questions regarding today’s issue or future issues feel free to reply to this email and we will get back to you as soon as possible. Come back tomorrow for another great post. I hope to see you. 🤙

— Ryan Rincon, CEO and Founder at The Wealth Wagon Inc.

_^Disclaimer: This newsletter is for informational and educational purposes only and reflects the opinions of its editors and contributors. The content provided, including but not limited to real estate tips, stock market insights, business marketing strategies, and startup advice, is shared for general guidance and does not constitute financial, investment, real estate, legal, or business advice. We do not guarantee the accuracy, completeness, or reliability of any information provided. Past performance is not indicative of future results. All investment, real estate, and business decisions involve inherent risks, and readers are encouraged to perform their own due diligence and consult with qualified professionals before taking any action. This newsletter does not establish a fiduciary, advisory, or professional relationship between the publishers and readers.