dithered_djinn
cjsawk itself is also capable of building a C99 compiler. In turn this allows us to bootstrap from source all the way up to GCC.
Web demo: https://cosinusoidally.github.io/tcc_simple/experiments/cjsa...
Project github repo: https://github.com/cosinusoidally/tcc_simple/tree/master/exp...
Slides: https://online.accuconference.org/wp-content/uploads/2025/10...
cjsawk: A Self-Hosted Compiler for a Subset of C, JavaScript, and Awk
https://github.com/mamedev/mame/pull/13404/files#diff-f78737...
I agree 100%.
Regarding the licensing, I'll restate my point that the Affero license was created precisely in a moment where the existing licenses could no longer uphold the freedoms that the Free Software Foundation set out to defend. A change of license was the right solution at that particular point in time and, if it worked then, I think we can all agree that there is at least a precedent that such a course of action might work and should at the very least be considered as a possible solution for today's problems.
That said, my own personal view is more aligned with demanding the nation states to pressure big corporations so that currently closed-source software becomes at least open-source (either by law, or simply by stopping using it and invest their budget in free alternatives instead). Note I said open source and not free. I just would like to read their code and feed it to my LLM's :)
If we instead adopt the view of free software (https://www.gnu.org/philosophy/open-source-misses-the-point....), the fact that OpenAI and other large corporations train their large-language models behind closed doors - with no disclosure of their training corpus - effectively represents the biggest attack on GPL-licensed code to date.
No evidence suggests that OpenAI and others exclude GPL-licensed repositories from their training sets. And nothing prevents the incorporation of GPL-licensed code into proprietary codebases. Note that a few papers have documented the regurgitation of literal text snippets by large language models (one example: https://arxiv.org/pdf/2409.12367v2).
To me, this seems like the LLM-version of using coin-mixing to obscure the trail of Bitcoin transactions in the blockchain. The current situation also reminds me of how the generalization of the SaaS model led to the creation of the Affero GPL license (https://www.gnu.org/licenses/why-affero-gpl.html).
LLM's enable the circumvention of the spirit of free software licenses, as well as of the legal mechanisms to enforce them.
Adding the option to filter by monospaced typefaces would make it even more amazing, imho. I would totally use a version of it that had the ability to "pair" three fonts: heading font, body font, and coding font.
The cherry on top would be enabling support for locally-installed fonts.
Thanks for sharing!
Accelerate CPU Based LLM Inference with a Vector Index on the Output Embeddings
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Without writing any code, you could export an audio plugin that will run in another Digital Audio Workstation or run your RNBO patch on a Raspberry Pi. You can also export to C++ or Web Assembly code for your desktop, mobile, or web applications.
RNBO: Export Max-Like Patches to C++, WASM, VST, Max Externals & RPI
Binary pan-cancer distinct classes defined by YAP/TEAD activity
g++ -O2 -march=native -mtune=native -D__LINUX_PULSE__ -D__LINUX_ALSA__ -D__UNIX_JACK__ \
lcc_rtaudio.cpp RtAudio.cpp -o lcc -pthread -ljack -lasound -lpulse-simple -lpulse
The above will give you a binary with the Jack, ALSA and PulseAudio backends baked in.