Why Deep Learning Matters
Deep learning is a subset of machine learning that is especially strong on unstructured data such as text, images, audio, and video.
This is why deep learning sits behind many modern AI products: speech recognition, image understanding, language generation, and multimodal systems all rely heavily on it.

Which product problem is most likely to require deep learning rather than simple rules?

Deep learning is especially useful for text, speech, image, and video tasks.

Deep Learning Comes With Costs
Deep learning can unlock impressive capability, but it often increases:
<ul>
<li>compute costs</li>
<li>training and inference complexity</li>
<li>latency sensitivity</li>
<li>data needs</li>
<li>debugging difficulty</li>
</ul>
For PMs, the question is whether the value of the capability justifies those costs.

What is a likely PM concern for a real-time mobile vision feature powered by deep learning?

Deep learning is always the best choice whenever data exists.

The PM Takeaway
Use deep learning when the problem genuinely requires pattern recognition over complex data and the economics still make sense.
A strong PM compares deep learning against simpler alternatives before committing. The most advanced solution is not always the best product solution.

Which task is more likely to be better solved with simple deterministic logic than deep learning?

PMs should compare deep learning against simpler baselines before committing to it.