Week 15 - Multimodal AI Engineering on AI Platform Engineering Handbook

Computer Vision & Image Models

Mon, 01 Jan 0001 00:00:00 +0000

Computer Vision & Image Models

The Big Picture First

Everything covered throughout most of this entire course has focused on text — language models reading and generating words. But a huge amount of the world’s useful information genuinely isn’t text at all — it’s photographs, scanned documents, charts, diagrams, medical scans, product images. Multimodal AI is the broad field specifically concerned with building AI systems that can actually work with these other kinds of information, not just text alone. This particular explanation focuses specifically on the visual side of that broader picture — how AI systems actually learn to see, understand, and even generate images. It’s worth understanding this as building on the exact same underlying foundations we’ve covered throughout this entire course (neural networks, embeddings, transformers), just applied to a genuinely different, visual kind of data.

Audio & Video AI

Mon, 01 Jan 0001 00:00:00 +0000

Audio & Video AI

The Big Picture First

The previous explanation covered how AI systems work with static images. This one extends that same multimodal idea into two more dimensions: sound and time. Audio adds a genuinely new kind of data — a continuous waveform rather than a fixed grid of pixels — and video combines both images and time together, essentially becoming a sequence of images changing over time, often paired with audio too. Together, these capabilities are what let AI systems actually listen, speak, watch, and understand the kind of rich, dynamic content that makes up so much of real human communication — phone calls, meetings, videos, podcasts — rather than being limited to text and still images alone.

Production Multimodal Systems

Mon, 01 Jan 0001 00:00:00 +0000

Production Multimodal Systems

The Big Picture First

The previous two explanations covered the individual building blocks of multimodal AI — vision models, audio models, video models, each one covered largely on its own. This final explanation is about what happens when you actually combine these pieces into real, working production systems that genuinely deliver value to real users. It’s worth understanding this as the multimodal equivalent of what we covered back in our earlier Week 15 AI product development and application-category explanations — the same underlying pattern of taking individual technical capabilities and assembling them thoughtfully into something a real business can actually deploy and rely on, just now specifically applied to systems that work across text, images, audio, and video together.