Aside, I hate the fact that I read posts like these and just subconsciously start counting the em-dashes and the "it's not just [thing], it's [other thing]" phrasing. It makes me think it's just more AI.
I like Mathematica and use it regularly. But I did not see any benefits of using it over python as a tool that Claude Code can use. Every script it produced in wolfram was slower with worse answers than python. Wolfram people are really trying but so far the results are not very good.
There's a great discussion with Stephen Wolfram on the Sean Carroll podcast. Listening to it made me think very highly of Wolfram. He's a free thinking, eccentric, mathematician, scientist; who got started doing serious work at a very young age. He still has a youthful creative approach to thought and science. I hope LLMs do pair well with his tools.
>"But an approach that’s immediately and broadly applicable today—and for which we’re releasing several new products—is based on what we call
computation-augmented generation, or CAG.
The key idea of CAG is to inject in real time capabilities from our foundation tool into the stream of content that LLMs generate. In traditional retrieval-augmented generation, or RAG, one is injecting content that has been retrieved from existing documents.
CAG is like an infinite extension of RAG
, in which an infinite amount of content can be generated on the fly—using computation—to feed to an LLM."
We welcome CAG -- to the list of LLM-related technologies!
I tried using wolfram alpha as a tool for an llm research agent, and I couldn't find any tasks it could solve with it, that it couldn't solve with just Google and Python.
CAG sounds like fake solution for LLM's. Math problems are not custom data, they are limited in amount, and do not refresh like product manuals.
Hence math can always be part either generic llm or math fine tuned llm, without weird layer made for human ( entire wolfram) and dependencies.
Wolfram alpha was always an extra translation layer between machine and human. LLM's are a universal translation layer that can also solve problems, verify etc.
There's a lot of value in the implementation of many strong and fast algeorithms in computer algebra in proprietary tools such as Maple, Wolfram, Matlab. However, I (though of course believe that such work needs to be compensated) find it against the spirit of science to keep them from the general public. I think it would be good service to use AI tools to bring open source alternatives like sympy and sage and macaulay to par. There's really A LOT of cool algorithms missing (most familiar to me are some in computational algebraic geometry)
Additionally I think because of how esoteric some algorithms are, they are not always implemented in the most efficient way for today's computers. It would be really nice to have better software written by strong software engineers who also understands the maths for mathematicians. I hope to see an application of AI here to bring more SoTA tools to mathematicians--I think it is much more value than formalization brings to be completely honest.
Imagine Isaac Newton (and/or Gottfried Leibniz) saying, "Today we're announcing the availability of new mathematical tools -- contact our marketing specialists now!"
The linked article isn't about mathematics, technology or human knowledge. It's about marketing. It can only exist in a kind of late-stage capitalism where enshittification is either present or imminent.
And I have to say ... Stephen Wolfram's compulsion to name things after himself, then offer them for sale, reminds me of ... someone else. Someone even more shamelessly self-promoting.
Newton didn't call his baby "Newton-tech", he called it Fluxions. Leibniz called his creation Calculus. It didn't occur to either of them to name their work after themselves. That would have been embarrassing and unseemly. But ... those were different times.
Imagine Jonas Salk naming his creation Salk-tech, then offering it for sale, at a time when 50,000 people were stricken with Polio every year. What a missed opportunity! What a sucker! (Salk gave his vaccine away, refusing the very idea of a patent.)
Right now it's hard to tell, but there's more to life than grabbing a brass ring.
The blog post would have been more effective with a specific example of what it solves, a demo, or at least some anecdotes of what this has already solved via these integrations. As it stands, it comes off rather self-aggrandizing and a bit desperate, as though Wolfram tech perceives itself as threatened to remain relevant.
LLMs using code to answer questions is nothing new, it's why the "how many Rs in strawberry" question doesn't trip them up anymore, because they can write a few lines of Python to answer it, run that, and return the answer.
Mathematica / Wolfram Language as the basis for this isn't bad (it's arguably late), because it's a highly integrated system with, in theory, a lot of consistency. It should work well.
That said, has it been designed for sandboxing? A core requirement of this "CAG" is sandboxing requirements. Python isn't great for that, but it's possible due to the significant effort put in by many over years. Does Wolfram Language have that same level? As it's proprietary, it's at a disadvantage, as any sandboxing technology would have to be developed by Wolfram Research, not the community.
I can't help but think about Wolfram every time I go into my thinking-about-ai mode. Really not sure how to frame all this stuff, but jeez there's a nexus, right?
Every major technological invention nowadays quickly breeds open source clones that evolve to be on par with the commercial ones on some time scale. Why hasn't this happened to Wolfram Alpha/Mathematica? I know there's Sympy, but it's so far behind Mathematica that it's not even comparable. Is the heavily mathematical nature of the tool somehow an insurmountable obstacle to the open source community?
Lots of big words there, but can I now expose the local Mathematica (confusingly renamed Wolfram a while ago) that I'm paying for, through MCP to Claude Code?
Because it seems I can't and all the big words are about buying something new.
One thing me.Stephen never made available is for people to copy results of Wolfram Alpha… he persisted doing so even after ocr and LLms were omnipresent, so somehow I don’t trust him even though his reload theory seems very appealing and apparently the team there understands production grammars very well since 1996.
Something this "shape" has been coalescencing since the first tool calls were done. To draw another Star Trek parallel, this reformulation is what Brent Spiner is during the little stares and pauses made before answering a complicated but constrained problems on the show. Onward!
Lines up with the current YC advice to "make something agents want". Not sure it makes a lot of sense to try and build a VC-backed business like this, but if distribution is the moat these days, perhaps.
He's 10 years too late for that. That's how you lose by keeping your stuff proprietary. The world innovates without paying any attention to you and you get left behind.
Imagine if 10 years ago Wolfram software was opensourced. LLMs would be talking it since the day one.
37 comments
[ 3.6 ms ] story [ 48.4 ms ] threadAside, I hate the fact that I read posts like these and just subconsciously start counting the em-dashes and the "it's not just [thing], it's [other thing]" phrasing. It makes me think it's just more AI.
computation-augmented generation, or CAG.
The key idea of CAG is to inject in real time capabilities from our foundation tool into the stream of content that LLMs generate. In traditional retrieval-augmented generation, or RAG, one is injecting content that has been retrieved from existing documents.
CAG is like an infinite extension of RAG
, in which an infinite amount of content can be generated on the fly—using computation—to feed to an LLM."
We welcome CAG -- to the list of LLM-related technologies!
Hence math can always be part either generic llm or math fine tuned llm, without weird layer made for human ( entire wolfram) and dependencies.
Wolfram alpha was always an extra translation layer between machine and human. LLM's are a universal translation layer that can also solve problems, verify etc.
Even the documentation search is available:
```bash
/Applications/Wolfram.app/Contents/MacOS/WolframKernel -noprompt -run '
Needs["DocumentationSearch`"];
result = SearchDocumentation["query term"];
Print[Column[Take[result, UpTo[10]]]];
Exit[]'
```
Additionally I think because of how esoteric some algorithms are, they are not always implemented in the most efficient way for today's computers. It would be really nice to have better software written by strong software engineers who also understands the maths for mathematicians. I hope to see an application of AI here to bring more SoTA tools to mathematicians--I think it is much more value than formalization brings to be completely honest.
A big disappointment as I’m a fan of his technical work.
The linked article isn't about mathematics, technology or human knowledge. It's about marketing. It can only exist in a kind of late-stage capitalism where enshittification is either present or imminent.
And I have to say ... Stephen Wolfram's compulsion to name things after himself, then offer them for sale, reminds me of ... someone else. Someone even more shamelessly self-promoting.
Newton didn't call his baby "Newton-tech", he called it Fluxions. Leibniz called his creation Calculus. It didn't occur to either of them to name their work after themselves. That would have been embarrassing and unseemly. But ... those were different times.
Imagine Jonas Salk naming his creation Salk-tech, then offering it for sale, at a time when 50,000 people were stricken with Polio every year. What a missed opportunity! What a sucker! (Salk gave his vaccine away, refusing the very idea of a patent.)
Right now it's hard to tell, but there's more to life than grabbing a brass ring.
Mathematica / Wolfram Language as the basis for this isn't bad (it's arguably late), because it's a highly integrated system with, in theory, a lot of consistency. It should work well.
That said, has it been designed for sandboxing? A core requirement of this "CAG" is sandboxing requirements. Python isn't great for that, but it's possible due to the significant effort put in by many over years. Does Wolfram Language have that same level? As it's proprietary, it's at a disadvantage, as any sandboxing technology would have to be developed by Wolfram Research, not the community.
That’s why I’m working on an open source implementation of Mathematica (i.e. an Wolfram Language interpreter):
https://github.com/ad-si/Woxi
Because it seems I can't and all the big words are about buying something new.
Imagine if 10 years ago Wolfram software was opensourced. LLMs would be talking it since the day one.