"If you distribute modified code, or offer it as a networked service, you must make the source available under the same terms. This is not a restriction on sharing. It is a condition placed on sharing: if you share, you must share in kind." -- This is, on any plain reading, a restriction on sharing. "You can share only under these conditions" is plainly more restrictive than "sure do whatever you want". You can argue that it's a restriction that ultimately leads to more sharing overall. But it is a restriction on sharing in any given case of sharing nevertheless.

If the cost to copying code based on specifications, tests, etc is so close to zero as to be functionally zero cost, then any user can simply turn their AI on any library for which there is documentation and any ability to generate tests, have it reverse engineer it, and release their reverse engineered copy on GitHub for others to use as they like.

So I'm not sure it matters whether a giant company uses it because random users can get the same thing for ~ free anyway.

My night and weekend project the last month or so has been creating and implementing a package that provides a pure s-exp syntax for Julia that lowers to Julia's AST directly, and lately been churning through (mostly Opus is doing the actual churning) all the problems of creating an automatic transpiler for Julia to this other syntax.

Not ready to share just yet but nearly at the point that there are no Julia-syntax fallbacks in the entire base/stdlib and a femtolisp parser for the sexp syntax is able to build a complete Julia sysimage from the transpiled files. Already verified that I can transpile the .jl source of the Julia package for the syntax into the syntax, then use that transpiler to transpile again and load into the running sexp repl, then use that transpiler on the source again and get byte identical code, and along the way am testing to ensure that the entire Julia test suite passes in the sysimage being built.

So, with any luck here soon I'll have a sexp syntax for Julia that builds from raw transpiled sexp-syntax source and uses sexp syntax natively in the repl but can transpile & load any Julia code. Fingers crossed.

I'm aware of --lisp but it's not very good imo lol.

I really don't see how that is true.

For instance, once you develop atomically precise manufacturing ala Drexler and have a complete model of biology, etc., drive solar panel efficiency to very near the upper theoretical bound for infinitely many junction cells for a raw panel of ~68%, then there isn't really anywhere to go that matters for humans. Material production would be solved, anything you could desire would be manufacturable in minutes to hours, a km^2 of solar panels could power 10-20k people's post-scarcity lives.

You eventually reach the upper bounds on compute efficiency and human upload model efficiency -- unknown but given estimates on upper bound for like rod logic (~1e-34Js/op), reasonably bounds on op speed (100MHz), and low estimates for functional uploading (1e16 flops), you get something in the zone of 0.1nW/upload, or several trillion individuals on 1m^2 of solar panel in space. When you put a simulated Banks Orbital around every star in the Milky Way in a grand sim running on a system of solar panels in space where the entire simulated galaxy has a 15ms ping to any other point in the simulated galaxy, what exactly is this infinite stream of learning? You've pushed technology to the the limits of physical law subject to the constraint of being made of atoms.

Are you envisioning that we'd eventually be doing computation using the entirety of a neutron star or (if they can exist) a quark star? Even then, you eventually hit a wall where physics constrains you from making significant further gains.

There is an ultimate end to the s-curve of technology.

Most wouldn't because it's expensive. But at scale automated vehicles should be dramatically less expensive, in the range of 50-60¢/mi conservatively, and at that level it is going to be quite compelling to a lot of people since it's a private vehicle (no taxi driver) and it's reasonably affordable, a 1 seat ride, etc.

It's possible they'll be even cheaper but that range is the cost according to the IRS of operating a typical vehicle all in, and that seems like a reasonable guess of the cost of an autonomous electric vehicle with far lower probability of crash than a human (all the savings basically going to profit margin).

At ~60¢/mi, there'd be a lot of people who would save money on balance using autonomous taxis to get everywhere vs owning a private vehicle (10k mi/yr would cost only ~$6k/yr, a pretty low cost of ownership/use for a private vehicle).