Former Richard Stallman Colleague Now Argues for Open AI Models Too (fortune.com)
- Reference: 0184507088
- News link: https://news.slashdot.org/story/26/07/19/0631207/former-richard-stallman-colleague-now-argues-for-open-ai-models-too
- Source link: https://fortune.com/2026/07/03/open-source-ai-same-fight-as-software-fight-1980s-david-siegel-two-sigma/
> Recalling his initial resistance to free and open software, billionaire computer scientist [2]David Siegel argues vigorously in FORTUNE that [3]the stakes are too high to let AI become increasingly closed . "In the 1980s, I had the chance to spend several years arguing about free and open software, what we now call open source, with the founder of the movement, [4]Richard Stallman . My office at the MIT AI Lab was next door to his. Stallman's position was that the source code to software should be free for everyone to use, learn from, and improve. Software encapsulates knowledge, he argued, and no one should lock something so fundamental away. To hide software inside a company was to hide knowledge itself... What I missed was that software was not just a commercial asset; it was a body of knowledge, and bodies of knowledge grow stronger when they are shared. After about two years of on-and-off debate, Stallman convinced me I was wrong."
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> "Now the AI fight is the same — only bigger," advises Siegel. "AI is software, and AI is increasingly closed. The frontier models — the most advanced, cutting-edge AI systems — are closed completely and the trend is accelerating. Viable open alternatives are few and far between." So, what to do...? "Yes, frontier models keep getting bigger and more expensive — that arms race may well stay with the giants. But open source AI does not have to match their scale to be useful. Much of what the world needs probably does not require the absolute frontier. And where keeping a credible open option does demand serious compute, that is precisely the kind of public good worth paying for.
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> "What's missing is not a path but will. The government, the private sector, and nonprofits should invest heavily in free and open source AI — the way they once invested in open software: public compute grants for open research, corporate and philanthropic support for universities and nonprofits doing the work, and a simple rule that AI built with public money is open by default.
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> "We have run this experiment before. We know how it turns out. Let's not unlearn it."
[1] https://www.slashdot.org/~theodp
[2] https://en.wikipedia.org/wiki/David_Siegel_(computer_scientist)
[3] https://fortune.com/2026/07/03/open-source-ai-same-fight-as-software-fight-1980s-david-siegel-two-sigma/
[4] https://stallman.org/
Open training data matters too (Score:2)
Too many websites have got restrictions now because of irresponsible crawling, instead of setting up deals where legitimate ways of access are established through data dumps. The balance must be right.
Re: (Score:1)
Yep. Open weights is closer to having precompiled binaries only (though you can do a little bit more with open weights). All training data with labeling, plus a detailed build log including any special fine-tuning logs, is needed, especially to help show how the final weights were arrived at (since there can be randomness involved). Unless someone else can both replicate your final output plus make their own changes to it, it's not fully open source.
Problem (Score:2)
Much of an "AI model" is just the underlying statistical weights. The engine sitting atop that probability data might be either open or proprietary. But it's the weights themselves that define the generated results. And to date, the claim is that no one really understands how an LLM makes its decisions based on them. So, open/closed doesn't make that much difference.
Open source for the engine part might prevent someone from sneaking something "evil" into the process. But if the LLM was trained on faulty da
You have some hurdles (Score:2)
The software can be open and free but then it is useless unless trained which requires basically a datacenter of GPUs and Petabytes of data. This is where the private companies can wink and say it was all non-copyright data but you won't have that luxury. You also need constant on-going data collection and on-going training. This is nation-state stuff. The best bet is if the EU or Australia is willing to fund it to not be dependent on the USA or China.
a bunch of lies and ignorance (Score:2)
"Stallman's position was that the source code to software should be free for everyone to use, learn from, and improve."
That was RMS's public-facing claim. In reality, his position was that source code should be free for HIM to use. As a student, he got upset that he couldn't have source code to a driver he wanted. Regarding software projects he was involved in, RMS loved being a dictator, do it his way or get lost.
"Software encapsulates knowledge, he argued, and no one should lock something so fundamenta
A former Richard stallman colleague? (Score:2)
Can we also hear from his father's brother's nephew's cousin's former roommate?
We all know what AI is for (Score:2)
It's to replace us so the Epstein class aren't dependent on our labor anymore for their wealth and power.
People keep asking, if nobody has any jobs who is going to buy their products.
Try flipping that on its head.
Imagine you're a billionaire or a trillionaire. Every single day of your life your fortune is completely dependent on these pathetic worms buying your products. If at any time they stop buying them and they stop listening to you sure you still got money but you are no longer a trilliona
Public Good???? (Score:2)
Haven't you heard? We don't believe in public goods anymore. Freemarket Baby! Privatize everything. Abolish libraries. Ban unions. Shareholders, not voters. Wheeeeeeee!
Re: (Score:2)
"public good" is a handy catchphrase useful for justifying when billionaires steal. Wasn't DOGE for the "public good"?