This is just a strange thing to say. There are so many languages out there with very interesting features, I'm not sure why you insist python is the only obvious choice. In my experience, all of the advanced research for proprietary companies in this area is not being done on Python, at least not those who are willing to speak at conferences. There's a lot of GPU computing also available to Java, if you think that's the reason Python is the only option. Python is certainly more widely used as a teaching language, so I guess you might see more libraries that are widely known because of universities in the academic environment, but I'm not sure why you think that means that it's the only language that major institutions are using? Because the reality is that almost all the cutting edge stuff that I've read about is not being done in python at all.
Can you give an example where a cutting edge research is done using something other than Python or MatLab? The only exception is Facebook using Torch.
In fact, Python dominance in DL is not just my opinion. Even Java devs admit it while trying to justify using Java for DL [1]:
"We’re often asked why we chose to implement an open-source deep-learning project in Java, when so much of the deep-learning community is focused on Python."
[1] http://deeplearning4j.org/compare-dl4j-torch7-pylearn.html
From looking at their website Prismatic appears to be a start up building APIs to access ML tools and providing services for enterprise customers. I looked at their job postings and they don't seem to be very research oriented. What makes you think they are doing cutting edge research in DL?
No one can say for sure what Prismatic is doing behind the scenes since it is a commercial entity but I've seen them speak at a couple conferences, which led me to believe they are doing some pretty novel ML studies. I could be wrong. But, your initial point was to suggest that a company shouldn't use anything other than Python when starting new ML projects, and Prismatic is an example of a company doing just that: using Clojure in this case. The article you mentioned earlier gives some good reasons why Python is often not the best choice for ML: speed, security, portability are often the reasons for leveraging the JVM (where Clojure lives). This is not a knock against Python, just pointing out that there is major stuff happening in ML that has nothing to do with Python. NYU's machine learning lab prefers C++ over other languages, and major projects like Siri and Watson rely a lot on C++ and Prolog. The point is that it makes no sense to claim that Python is the only language anyone should consider for these tasks.
