Non-commercial licenses aren't open source by the OSI open source definition https://opensource.org/osd-annotated (see points 5 and 6). I think it's important that we don't use the term "open source" for a license unless it fits that definition, and, ideally, is OSI approved.
There are a lot of issues with non-commercial license. There are some links here explaining why. https://en.wikipedia.org/wiki/Creative_Commons_NonCommercial_license#Commentary. Basically, the definition of what is considered "commercial" is much broader than what you would expect. Aaron Meurer On Thu, Apr 16, 2020 at 4:40 PM Jason Moore <[email protected]> wrote: > > The license they chose is open source, but it just isn't readily compatible > with OSI approved licenses. > > I was recently surprised to find out that CC-BY isn't even compatible: > https://opensource.stackexchange.com/questions/9242/why-does-creative-commons-recommend-not-using-cc-by-licenses-for-software/ > > Jason > moorepants.info > +01 530-601-9791 > > > On Thu, Apr 16, 2020 at 3:27 PM Aaron Meurer <[email protected]> wrote: >> >> FWIW the license they chose (CC-BY-NC) isn't actually open source. But >> at least the code is there if you want to run it. >> >> Aaron Meurer >> >> On Thu, Apr 16, 2020 at 3:50 AM S.Y. Lee <[email protected]> wrote: >> > >> > They have opened the source code and the dataset >> > https://github.com/facebookresearch/SymbolicMathematics >> > >> > On Saturday, January 11, 2020 at 2:25:40 AM UTC+9, Aaron Meurer wrote: >> >> >> >> For those who didn't see, the final paper was posted with many updates >> >> https://arxiv.org/abs/1912.01412. The newest version addresses some of >> >> the things that were discussed here, and makes more use of SymPy, >> >> including demonstrating some integrals that SymPy cannot solve, as >> >> well as making it clearer how SymPy was used to check the results of >> >> integration. >> >> >> >> Aaron Meurer >> >> >> >> On Tue, Oct 8, 2019 at 8:16 PM oldk1331 <[email protected]> wrote: >> >> > >> >> > (This mail is copied from my response at maxima mailing list.) >> >> > >> >> > My opinion on this paper: >> >> > >> >> > First, their dataset (section 4.1) can be greatly improved using >> >> > existing integration theory, Risch algorithm says that every elementary >> >> > function integration can be reduced to 3 cases: transcendental (only >> >> > contains rational functions and exp/log/tan, other trigonometric >> >> > functions can transform to 'tan'), algebraic (only contains rational >> >> > functions and nth-root ^), and mixed-case. >> >> > >> >> > So their method to prepare the dataset concentrates greatly on the >> >> > transcendental cases, extremely lacks algebraic cases. And they uses >> >> > only numbers from -5 to 5. I think it scales badly for wider ranges of >> >> > numbers. >> >> > >> >> > For transcendental cases, I think FriCAS has fully implemented this >> >> > branch of Risch algorithm, so it should always give correct result. For >> >> > algebraic cases, I highly doubt that this ML program can solve >> >> > integrate(x/sqrt(x^4 + 10*x^2 - 96*x - 71), x) = >> >> > log((x^6+15*x^4+(-80)*x^3+27*x^2+(-528)*x+781)*(x^4+10*x^2+(-96)*x+(-71))^(1/2)+(x^8+20*x^6+(-128)*x^5+54*x^4+(-1408)*x^3+3124*x^2+10001))/8 >> >> > >> >> > In fact, I doubt that this program can solve some rational function >> >> > integration that requires Lazard-Rioboo-Trager algorithm to get >> >> > simplified result. >> >> > >> >> > So I think this ML program has many flaws, but we can't inspect it. >> >> > >> >> > > I'm also curious (and sceptical) on just how well a neural network can >> >> > > "learn" symbolic mathematics and specifically an integration >> >> > > algorithm. Another interesting thing to do would be to try to train a >> >> > > network to integrate rational functions, to see if it can effectively >> >> > > recreate the algorithm (for those who don't know, there is a complete >> >> > > algorithm which can integrate any rational function). My guess is that >> >> > > this sort of thing is still beyond the capabilities of a neural >> >> > > network. >> >> > >> >> > I totally agree. >> >> > >> >> > - Qian >> >> > >> >> > -- >> >> > You received this message because you are subscribed to the Google >> >> > Groups "sympy" group. >> >> > To unsubscribe from this group and stop receiving emails from it, send >> >> > an email to [email protected]. >> >> > To view this discussion on the web visit >> >> > https://groups.google.com/d/msgid/sympy/ca99c7a0-b372-82cb-74e6-2ff978f40d54%40gmail.com. >> > >> > -- >> > You received this message because you are subscribed to the Google Groups >> > "sympy" group. >> > To unsubscribe from this group and stop receiving emails from it, send an >> > email to [email protected]. >> > To view this discussion on the web visit >> > https://groups.google.com/d/msgid/sympy/9d091321-07dd-4ade-9442-795282269627%40googlegroups.com. >> >> -- >> You received this message because you are subscribed to the Google Groups >> "sympy" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to [email protected]. >> To view this discussion on the web visit >> https://groups.google.com/d/msgid/sympy/CAKgW%3D6J2RkAM2zQrcSLfEH0X6D%3DH0-Jt1tTmwXQHz7aOO%2B4yDg%40mail.gmail.com. > > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/CAP7f1AgScnV30J297a%3DZ8yo8gmvDqXx%2BWgR9fhi5FrqSfVsisw%40mail.gmail.com. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CAKgW%3D6L3_c6oaxkHP%2BDFQupibA8qrC%2BSe2_w6SzuWUYhsupPmg%40mail.gmail.com.
