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.

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

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.

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[]'

```

Because it seems I can't and all the big words are about buying something new.

Why can't I just pay some price and get the entire bundle of Wolfram One Cloud + API calls + LLM Assistant + This new MCP access + Mathematica?

I need to buy 5 different things - and how does that look for me the user, I need 5 different binaries?

They really should sort that out, I know they are losing money because of this. I emailed their support once and ended up getting more confused.

Sure, as any other tech, Mathematica may have its edges (I used it deeply 10-15 years ago, before I migrated to Python/Jupyter Notebook ecosystem). But in the grand scheme of things, it is yet another tech, and one that is losing rather than gaining traction.

Certainly not "a new kind of science".

"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!

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.

[1] Introduction to Machine Learning:

https://www.wolfram.com/language/introduction-machine-learni...

A big disappointment as I’m a fan of his technical work.

Imagine if 10 years ago Wolfram software was opensourced. LLMs would be talking it since the day one.

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.

https://www.stephendiehl.com/posts/computer_algebra_mcp/

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.