What Is Deep Learning?

Deep learning is behind the AI you've heard about—LLMs, image recognition, speech. But it's not always the right tool. Here's what it is and when you actually need it.

What is deep learning?

Deep learning is a type of machine learning that uses multi-layered neural networks to learn complex patterns from large amounts of data. The "deep" refers to the many layers, which let it capture rich, subtle patterns that simpler methods can't.

Why it powers modern AI

Deep learning's ability to learn from complex, unstructured data is what made modern AI possible:

Domain	Powered by deep learning
Language	LLMs, NLP
Vision	Computer vision
Speech	Voice AI

The transformer architecture—a deep learning breakthrough—is what powers today's LLMs.

Deep learning vs classic ML

	Classic ML	Deep learning
Data	Smaller, structured	Large, unstructured
Compute	Lower	High
Best for	Tabular predictions	Language, images, audio

Deep learning isn't always better—for smaller, structured problems (forecasting from spreadsheet data, for instance), classic ML is often faster, cheaper, and sufficient. Using deep learning where it's unnecessary wastes data and compute.

When to use it

Use deep learning when the problem involves large amounts of complex, unstructured data and simpler methods aren't accurate enough. For structured, smaller problems, start with classic ML—the use-the-right-tool principle.

The cost consideration

Deep learning's appetite for data and compute makes it more expensive to build and run—part of total cost of ownership. Right-sizing the approach to the problem controls cost.

Why FISTA

FISTA Solutions applies deep learning where it fits—and simpler methods where they win—matching the approach to your problem and data, through AI enablement, backed by 150+ projects across 12+ countries.

Not sure which approach fits? Talk to FISTA.