by hebejebelus
4 subcomments
- Man, I miss Wolfram Language. Once you've twisted your brain a little to grok its usage, it's such an incredibly high-value tool, especially for exploration and prototyping. I saw it more as a do-anything software tool for researchers rather than as a language aimed at programmers, so I put on a researcher hat and tried to forget everything I knew as a professional programmer, and had a few memorable seasons with it around 2016-2020. I remember calculating precisely which days of the year would cause the sunlight to pass through a window and some glass blocks in an internal wall, creating a beautiful light show indoors. It only took a couple of minutes to get a nice animated visualisation and a calendar.
Nowadays I'd probably just ask Claude to figure it out for me, but pre LLMs, WL was the highest value tool for thought in my toolbox.
(Edit: and they actually offer perpetual licenses!)
- The tech world needs more Stephan Wolframs.
Yes this is all a bit quirky and nuanced but when you get into it these things are really good. It’s refreshing to see some really smart folks just focused on doing great things without blinding from VCs and MBAs pushing another hacky quick way to make a buck and cash out.
- Maybe with the power of a supercomputer, Mathematica can finally launch in less than 30s. I have no idea how a software that still does essentially the same thing as it did in 1988 can be that sluggish.
by robot-wrangler
1 subcomments
- So "use our proprietary service to scale our proprietary language" is a great pitch for people who are already all in. Increasing spend among existing customers won't help you get new ones though. And it kind of feels like a prelude to nerfing non-cloud based usage.
Typical example of a extraction/exploitation mentality where innovation would be better. Wolfram is in an amazingly good spot to spin up better "simulation as a service" if they would look at fine-tuning LLMs for compiling natural language (or academic papers) into mathematica semi-autonomously and very reliably. Mathworld is potentially a huge asset for that sort of thing too.
- I love this, too many people keep themselves busy discussing bits and bytes, or Stephen Wolfram's personality.
The reality is that by now we should already be at a level where common programming would be like Wolfram everywhere.
Maybe agents and LLM driven code generation is how we eventually get into the next abstraction level, sadly won't be without casualties with smaller team sizes, when so much can be automated away.
- I really like this way of introducing a new feature/service. Straight to the point, explains what it does, which problem it solves, gives practical examples and walks the reader through them. So many times when I read about a new feature/service I am left with more questions than I had started with, but this was great!
- Huh. So Stephen finally discovered cloud computing (yes, I know about the hosted notebooks).
I played around with RemoteKernel some time ago (https://taoofmac.com/space/blog/2016/08/10/0830) but this is “better”, although I wish they’d make it hostable in your own cloud provider like materials simulation software and other things we see running in HPC clusters.
(I also ran Mathematica in a 512GB/128core VM once for kicks, but it’s just not cost-effective).
- I've been using Mathematica since 1992 or so and at least for the last 20 years I've been wondering why they didn't provide cloud computing services, so that I can simply evaluate stuff remotely on a larger computer. So, I guess I should say "FINALLY!" :-)
- With all the integrated standard functions Mathematica is such an incredible tool. We really need an open source version of it. Even if we implement only 10% of the features it would be already incredible useful.
I started working on an implementation in Rust called Woxi (https://github.com/ad-si/Woxi) and I hope to find some contributors, as it is such a gargantuan task!
by d_burfoot
1 subcomments
- Do quant traders use Mathematica? I would guess this would be a great use case for a tool that lots of people love. Pretty language, huge boatload of built-in tools, high powered mathematics, great visualization capabilities. Quant firms should be able to live with the price tag. I assume they have a compiler that can produce fast executables for HFT.
- Instead of offloading batch computations to a proprietary cloud, it’s better to actually optimize the incredibly slow and unstable computational kernel.
In any case that’s not the happy path, Mathematica gets stuck in symbolic computations for ages. My FFT-based research in Mathematica slowed to a crawl, tens of minutes of waiting, even with 90% of the code compiled to binary. MATLAB finishes this task in milliseconds.
- the beauty of pure functions :)
by adamwong246
1 subcomments
- I'm slightly terrified of the combination of Wolfram and a LLM.
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