Wow… incredibly expensive… at minimum another 26€ a month. Wolfram really enjoy milking their customers dry (and I’m a customer). I think this is highway robbery.
With a bit of creativity you can run something similar for free. It's worth noting Raspberry Pi comes with a free Wolfram license. The assistant part can come from something like Perplexity, which in my experience is decent at writing Mathematica code.
I also have a Mathematica license which I think is worth paying for. One of the few closed software that has no good equivalent in the libre world. Nonetheless, I wish Wolfram had come up with a different business model that made Mathematica more mainstream, as I feel it has not realized its potential in certain areas.
Totally agree that they have unrealized potential. It was amazing when I was in grad school. Then when I started running a corporate data science team, I struggled to find a use case to recommend it for purchase. There are so many other tools that are better at loading a messy dataset, cleaning it, doing EDA, building a model, and productionizing and monitoring the model, which is the process we spend a lot of time doing.
It’s only expensive if you’re getting less than 50$/month of value from it, at which point don’t subscribe. This isn’t something I’d pay for right now, but when I was doing this kind of work regularly it would have been an easy purchase.
Subscription models don’t mesh well with casual users. However, if it’s going to save you hours of work every month then it’s a perfectly reasonable price point.
For me, it's like days, weeks, or months of distraction trying to get the license renewed, through the multiple bureaucracies that are involved: IT, purchasing, and accounting, to name a few. And a second license for the lab, or a site license, or one for home use? That's crazy talk. And now that software is sold by subscription, it's an annual headache, per app.
I get it that "single user at single computer" is the majority of use cases, so I'm not asking for accommodation. But for me, free means free site license, and I do like to have my tools installed on every computer that I touch.
Sure, there are work-arounds, but it's hard to keep using the proprietary stuff when the free stuff is so easy to deal with.
Disclosure: Wolfram user from 1993 to 1997. Also, when colleagues want to use proprietary software tools, I always go to bat for them, to get the expense approved, because I believe that people should have a choice.
Yeah i totally do understand what you're saying. I miss having mathematica available on any machine for instance on a campus site license, which i used for years overlapping yours too!
That looks nice. For the user, however: If notebooks or anything connect to Wolfram servers, is your own IP mined to power the training? Has past IP been mined?
You could have a puzzle that's described in plain English. I think the current day tech is sufficient to translate the puzzle to a python constraint like in this gist.
The argument is that the SMT solvers are a better match for solving these problems than expensive matrix multiplication paid for by someone else.
Of course, SMT is not a solution for every situation that Wolfram language is used for today. But a lot of the reasoning benchmarks fall in this category.
This sounds like an argument for a custom DSL designed for the purpose of expressing constraints and for querying statiatical data.
Perhaps there are cases where DSL is the right answer. Not sure if this is one though.
I see some parallels to the arguments around using a ML derived language instead of adding types to python3 and giving it 90% of the capabilities.
There are other factors like: open vs closed development model, number of implementations (Wolfram language has exactly 1?) etc.
From my perspective, the problem to solve is that the python ecosystem isn't even trying. Would love to see stats about the adoption of the match statement introduced 3 yrs ago.
I loved mathematica during university. Gorgeous math notation written with quick hotkeys, so I never needed Latex. And it computed in that form, so I never needed to code in ASCII. I'd do most of my math/engineering/physics homeworks in it. I would have paid for this back then for sure. Sadly, I rarely need to open mathematica anymore, in the world of real life employment.
It's probably the fact that it costs money at all. Python libraries and Jupyter notebooks can technically do a lot of things for free, so even rich tech companies just default to the free option. Getting approval for paid software is a huge pain in the butt. Also, the fact that it doesn't use simple ASCII character code is probably frowned upon since you can't diff it in a version management system for code review.
I do have a personal copy and I definitely do open it up when I really want to solve a hard mathematical problem quickly. Then I translate it after the fact to whatever corporate language I was supposed to solve it with.
My feeling as a mathematician is that adding gen AI to study science takes the beauty away from scientific discovery. It is an overt signal to what was alreadly happening covertly: the transformation of science into a mechanized procedure for the sake of production instead of human good. I condemn technology like this especially.
I disagree. AI used thoughtfully as a tool can potentially allow a mathematician or scientist to progress further and see more beauty. I'm also a mathematician by training and I've realized that a large part of my love for math was/is the process of solving a problem by my own wits. AI does take that away somewhat, but that's not really the important part of maths for society as a whole.
I really appreciate the depth and detail of Wolfram's blog posts like these. Any other blog would have ended around 1/5th of the way. I kept expecting it to end, but it kept on giving and throwing in more examples. It's amazing and I can't help but compare that most people don't do that.
I like the idea of this quite a lot (at a minimum, it would cut out all of those "how do I do XYZ in Mathematica" web searches) but not enough to subscribe. I'd rather buy some bucket of credits because my use of MMA is very unevenly distributed over time.
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[ 4.8 ms ] story [ 91.7 ms ] threadI also have a Mathematica license which I think is worth paying for. One of the few closed software that has no good equivalent in the libre world. Nonetheless, I wish Wolfram had come up with a different business model that made Mathematica more mainstream, as I feel it has not realized its potential in certain areas.
And even in the symbolic math niche, I am afraid that Python and Julia will slowly erode its market-share.
Are they forcing you to use it?
Or do you expect them to run expensive GOUs for you for free?
Are you actually using wa? Because if it's helpful as an assistant and it only costs 26 Dollar, shouldn't you be happy about this?
Subscription models don’t mesh well with casual users. However, if it’s going to save you hours of work every month then it’s a perfectly reasonable price point.
Any alternative where you pay $10 for $15 value or you pay $100 for $150 value will beat this
Personally no, 50$/month of value covers not just 30$/month, but also the overhead of yet another subscription.
So paying 10 for 15 doesn’t make much sense IMO, but $100 for $150 does.
(Wolfram customer since 1988 too, so I think it’s helpful to change units, in this cost evaluation!)
I get it that "single user at single computer" is the majority of use cases, so I'm not asking for accommodation. But for me, free means free site license, and I do like to have my tools installed on every computer that I touch.
Sure, there are work-arounds, but it's hard to keep using the proprietary stuff when the free stuff is so easy to deal with.
Disclosure: Wolfram user from 1993 to 1997. Also, when colleagues want to use proprietary software tools, I always go to bat for them, to get the expense approved, because I believe that people should have a choice.
English -- (LLM) --> python
Human fine tunes python
Python -- (py2many) --> smt2 --> z3 --> result
Perhaps some steps can be eliminated in the future.
You could have a puzzle that's described in plain English. I think the current day tech is sufficient to translate the puzzle to a python constraint like in this gist.
The argument is that the SMT solvers are a better match for solving these problems than expensive matrix multiplication paid for by someone else.
Of course, SMT is not a solution for every situation that Wolfram language is used for today. But a lot of the reasoning benchmarks fall in this category.
https://blog.wolfram.com/2021/11/04/lessons-learned-migratin...
The linked tweet (https://x.com/WolframResearch/status/1325935891651698690?s=2...) is inaccessible. Does anyone have an archive?
I'd love to see pandas/df compared instead of the iterative style.
Now the view from someone who quit Mathematica walled garden to embrace the Python ecosystem (2018): https://paulromer.net/jupyter-mathematica-and-the-future-of-...
Perhaps there are cases where DSL is the right answer. Not sure if this is one though.
I see some parallels to the arguments around using a ML derived language instead of adding types to python3 and giving it 90% of the capabilities.
There are other factors like: open vs closed development model, number of implementations (Wolfram language has exactly 1?) etc.
From my perspective, the problem to solve is that the python ecosystem isn't even trying. Would love to see stats about the adoption of the match statement introduced 3 yrs ago.
I do have a personal copy and I definitely do open it up when I really want to solve a hard mathematical problem quickly. Then I translate it after the fact to whatever corporate language I was supposed to solve it with.
... for a significant slice of professional and hobbyist use cases, and there are no alternatives AFAICT!