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Making Wolfram tech available as a foundation tool for LLM systems

writings.stephenwolfram.com

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Re: Making Wolfram tech available as a foundation tool for LLM systems

#101

Post by cwillu »

laserbeam wrote: post #98
Davidzheng wrote: post #40

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 macaul…

> against the spirit of science to keep them from the general public Within science, participants have always published descriptions of methodology and results for review and replication. Within the same science, participants have never made access to laboratories free for everyone. You get blueprints for how to build a lab and what to do in it, you don't get the building. Same for computation. I'm fairly sure almost…

Software is the blueprint, execution is the machine.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#102

Post by Almondsetat »

laserbeam wrote: post #98
Davidzheng wrote: post #40

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 macaul…

> against the spirit of science to keep them from the general public Within science, participants have always published descriptions of methodology and results for review and replication. Within the same science, participants have never made access to laboratories free for everyone. You get blueprints for how to build a lab and what to do in it, you don't get the building. Same for computation. I'm fairly sure almost…

Software is fundamentally different than lab equipment, just like PDFs are not paper journals that have to be printed, stored, and shipped. Most things in the digital domain have to be treated in a post-scarcity mindset, because they essentially are.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#103

Post by notyourwork »

laserbeam wrote: post #98
Davidzheng wrote: post #40

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 macaul…

> against the spirit of science to keep them from the general public Within science, participants have always published descriptions of methodology and results for review and replication. Within the same science, participants have never made access to laboratories free for everyone. You get blueprints for how to build a lab and what to do in it, you don't get the building. Same for computation. I'm fairly sure almost…

Generally I agree up until now where we appear to be treading on the threshold of AI being orders of magnitude more powerful. Given that, which has potential to displace large swaths of the labor force, I feel as though society deserves a larger return on investment.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#104

Post by verytrivial »

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!

Re: Making Wolfram tech available as a foundation tool for LLM systems

#106

Post by zozbot234 »

Davidzheng wrote: post #40

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 macaul…

Computer algebra of the Mathematica/Maple variety is not formally rigorous: it will get things wrong due to conflating function domains, choices of branch cuts for 'multi-valued functions' and other assumptions that are required for correct results but not exposed or verified. The work of providing "strong and fast algorithms" that are comprehensively described ought to be done as part of building proof systems for the underlying mathematics that will ensure correctness.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#107

Post by scotty79 »

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.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#108

Post by simianwords »

danpalmer wrote: post #95
simianwords wrote: post #87

Earlier quoted context omitted.

>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. False. It has nothing to do with tool use but just reasoning.

It's so easy to google this and find that they all do exactly this. Gemini: https://ai.google.dev/gemini-api/docs/code-execution ChatGPT: https://help.openai.com/en/articles/8437071-data-analysis-wi... Claude: https://claude.com/blog/analysis-tool Reasoning only gets you so far, even humans write code or use spreadsheets, calculators, etc, to get their answers to problems.

you have just linked the fact that they have code executions but not proved that it is needed for strawberry problem.

there are multiple ways to disprove this

1. GPT o1 was released and it never supported the tools and it easily solved the strawberry problem - it was named strawberry internally

2. you can run GPT 5.2-thinking in the API right now and deny access to any tools, it will still work

3. you can run deepseek locally without tools and run it, it will still work

Overall this idea that LLM's cant reason and need tools to do that is misleading and false and easily disproven.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#109

Post by tonyedgecombe »

scotty79 wrote: post #107

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.

>Imagine if 10 years ago Wolfram software was opensourced.

They would have lost ten years of profits and development would have slowed.

Re: Making Wolfram tech available as a foundation tool for LLM systems

#110

Post by bryanrasmussen »

golem14 wrote: post #69
bryanrasmussen wrote: post #57

Earlier quoted context omitted.

>We as a culture decided that science is worthwhile, and that it's worth funding it with public money, which I personally strongly support. what country are you in, and what percentage of the public purse goes to funding science? In the U.S about 11%, and with that number I often read articles, linked to from this site, about U.S Scientists quitting and going into private sector work or other non-scientific fields to…

Um, where did you get the 11% from? Looking at https://www.cbpp.org/research/federal-budget/where-do-our-fe... , federal tax revenue used for "science" seems to be Education is another 5% accroding to that site.

hmm, you're right, I made a mistake and was going on discretionary spending, of which it is a higher percentage than the whole budget.

I normally look at ncses, but in this mainly going off the last stuff I looked at from AAAS

https://www.aaas.org/sites/default/files/2021-02/AAAS%20R%26...

I think the CBPP maybe underplays research under different organizations, for example is DARPA under DOD or is it under science and education? If under DOD then can probably increase the percent by another .5 from DARPA, and so forth with other organizations.

However, I am certainly fine with taking your stats since that just underlines they point I made and evidently got downvoted for, that the U.S does not pay for scientific research at a level where one can blithely assert that it is something considered important by the government.

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