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As of Feb 2019, I think we are still not near peak Deep Learning. Peak hype? That was around 2016-2017. Peak applications & deployment? We have a long way to go. We're still expanding fast. The Keras userbase grew 35% last year, and will likely grow at least as much in 2019.
We are very fortunate that Deep Learning has been delivering enough practical value that repeated blitzs of overselling PR haven't killed it yet. I will note that the models & software that are delivering and those are being hyped up are remarkably non-overlapping...
What are the omens we should look for sign of “peak Deep Learning”?
videos of deep learning hand puppets popping up around the web ; )
Research is ~5% of usage. Data comes from many sources, but documentation MAUs is a relatively accurate indicator.
With TF2.0, the easy of developing models(of course more people are gonna use tf.keras) and deploying it on mobiles(tflite with new GPU backend), I bet ML/DL on mobile will see a surge. Though it depends on how seamless the whole process is.
Absolutely, I have high hopes for mobile-based, browser-based, and embedded applications in vision, sounds, NLP...
Compared to the big data hype we are at the map reduce stage. DL works well but is hard to implement for more difficult cases. There are so much more advanced DL frameworks to come.
What are some of the best places for someone with DL knowledge to meet & collaborate with someone with domain knowledge?
Starbucks
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