Sadly I don’t know a single person who has used Wolfram’s software extensively. I haven’t used it myself extensively. Is that because it’s not what it’s cracked up to be, or because it’s a closed world?
Mathematica is used by a lot in academia, and you'll find it cited in Methods section often. I personally know a lot of incredibly talented and prolific physicists who swear by it, and have used it to get very good work done.
> It’s only recently that I’ve begun to properly internalize just how broad the implications of having a computational language really are—even though, ironically, I’ve spent much of my life engaged precisely in the consuming task of building the world’s only large-scale computational language.
I guess the rest of us will just need to muddle through with the (apparently) small-scale (non?)-computational languages that we use.
I think that might be a little unfair. Wolfram's certainly more articulate in his egotism, but nobody matches The Donald for sheer volume:
"I understand things, I comprehend very well. Ok? Better than, I think, almost anybody."
The only innovation I see here is an unusual attention to constructing visual representations and using them as identifiers in code. Which is cool! But insisting it's new demeans the work of thousands of engineers who do similar and prerequisite work, and who make an effort to situate their work in literature and indusrtry rather than insisting on some kind of exceptionalism.
Arrogance should be called out in every instance, because it's not actually a route to greatest impact.
The question I’d ask those physicists is whether Mathematica does the kinds of things Wolfram claims for it / does things other programming languages can’t do. I wouldn’t be surprised if the answer was “yes,” I’m just not sure.
This is coming from a pythonista btw. To each their own. Python is a better scripting language, but Mathematica is a better analysis language for a lot of things. Python is catching up in a lot of ways though with Numpy and Tensorflow. I'd say Python's Tensorflow is a lot more mature than Mathematica's neural nets, but Mathematica's symbolic math seems to be world class.
Mathematica/Wolfram Language is a perfectly fine programming language. It has an amazing standard library. It's definitely worth the money (if you're working in a field that benefits from it). But that's it. Don't call it a computational language. It isn't a new way of thinking. It isn't revolutionary, there is literally nothing in Mathematica that can't be done in another language just as easily (except the CAS engine is world leading). But somehow these mundane blog posts by Stephen Wolfram make it to the front page of HN every few months, so someone must be upvoting them.
So maybe his hype machine is working as intended- he is in charge of a successful company and I'm hiding anonymously behind a keyboard. So what if a few people don't like his attitude, he's more successful than most of us.
I used Mathcad a bit in undergrad and my wife (civil engineer) used it extensively for all engineering courses for 4 years. One of her main professors wrote an entire civil engineering textbook in Mathcad and that was why they pushed it. It was a decent and cheap math tool, but Mathematica is orders of magnitude more mature from a language, functionality, graphics...really it beats Mathcad in everything except cost. The gulf between the two is like Windows 95 and Windows 10. Mathematica has support for neural networks, time series data, blockchain, 3D printing, running on Arduino, transpiling to C, Natural language processing, insanely detailed graphics primitives, web crawling...etc etc.
Matlab and Maple have done a better job keeping up, but Mathematica beats those easily as well in my opinion although they are somewhat different products.
His writing does come across that way. He is self-confident, certainly. I have met him in person. He is actually a kind and generous person. He is also very likely to be the smartest person in the room most places he goes. I met him at a place where there were a lot of other math PhD's in the room (not me by any stretch) so maybe he felt he was among his people and was mixing more naturally. But in any case, my approach was to shut up and listen because I was more likely to learn something that way.
The notebooks are great, but I find Jupyter notebooks to be good enough even if they aren't as good in many ways if you aren't skilled in markup.
One of their senior scientists (Matt Trout) has some insane blog posts that show off the power of the language. He has one on using Laplace Transforms to hide an image of a goat. It is basically pages of Math. It would take two or three times the code in Python I bet.
Annoyingly, I wouldn't really use it in production as deployment looks painful and it limits the number of cores you can use. I usually use it as a super powerful prototyping tool.