6 ms·
Soul Player C64 – A real transformer running on a 1 MHz Commodore 64
- harel 6mo agoEliza called, and asked if we saw her grand kids...
- tclancy 6mo agoWhat makes you say that? This is about you, not me. (Came here to say an update to Eliza could really mess with the last person still talking to her.)
- bighead1 6mo agoi hate ai, and i love the c64, but i'll allow it.
- wk_end 6mo ago> 25K parameters is about 70 million times smaller than GPT-4. It will produce broken sentences. That's the point - the architecture works at this scale. Since it seems to just produce broken and nonsensical sentences (at least based on the one example given) I'm not sure if it does work at this scale. Anyway, as written this passage doesn't really make a whole lot of sense (the point is that it produces broken sentences?), and given that it was almost certainly written by an AI, it demonstrates that the architecture doesn't work especially well at any scale (I kid, I kid).
- forinti 6mo agoHow does it compare to a Markov chain generator I wonder.
- jll29 6mo agoThe Transformer is the more powerful model than Markov chain, but on such a weak machine as the C64, a MC could output text faster - but it surely would sound "psychedelic", as the memory limits a MC to a first-order or second-order model, so to predict one word, only the two words before would be taken into account as context (and no attention). On a plain vanilla C64, the Transformer cannot really show what it's capable of doing. An implementation using 2 bit per weight (vectorized) could be slightly better, perhaps.
- yorwba 6mo agoYou can build an unlimited-order Markov chain by, instead of pre-computing a table of counts for all possible contexts, using a substring-search index on the training data to count possible continuations on the fly: https://arxiv.org/abs/2401.17377 https://arxiv.org/abs/2401.17377 That paper uses suffix arrays, but more compact indices are possible: https://arxiv.org/abs/2506.12229 https://arxiv.org/abs/2506.12229
- anthk 6mo agoCould that be implemented in Hailo for Perl (it's two commands away from a base install:) - Install Cpanminus for Perl, some C compiler and sqlite3 just to be sure. cpanm -n local::lib cpanm -n Hailo ~/perl5/bin/hailo -t corpus.txt -b chatbot.brn ~/perl5/bin/hailo -b chatbot.brn
- yorwba 6mo agoYou would probably have to completely rewrite its internals.
- pizza234 6mo ago[dead]
- Lerc 6mo agoOk now we need 1541 flash attention. I'm not sure what the venn diagram of knowledge to understand what that sentence is suggesting looks like, it's probably more crowded in the intersection than one might think.
- dnnddidiej 6mo agoHow many 40+ AI pillers? Assume 10M devs in the world. 10% heard of flash attention, 1% heard of 1541 then 10,000
- Lerc 6mo agoAhh but you also have to know the significance of the 1541 that makes the Flash attention reference work
- gizmo64k 6mo agoBelieve me, using the 1541 as co-processor and extra storage was super tempting and on my mind all the time! So what do you think? Flash attention with K on the front side and V on the backside? :)
- gizmo64k 6mo ago..and we would keep the human in the loop:)
- classichasclass 6mo agoIf you're running this in VICE, run it under the SuperCPU with warp mode on.
- bartread 6mo agoThat's a good idea because, although I love this, 1 minute per token is absolutely savage. Whereas if you can juice the performance you're into semi-credible Jar Jar Binks simulator territory. It does also make me wonder what you could do with somewhat more powerful retro hardware. I'd love to see what a transformer running on a PSX or an N64 could do.
- giannicmptr1000 6mo agobut can you make mac keyboards feel like a c64c?
- anyfoo 6mo agoThis would have blown me away back in the late 80s/early 90s. (Or maybe not, if it doesn't perform better than random, I haven't actually tried it out yet. Some more examples would have been nice!) I wonder how far you could push this while still staying period correct, e.g. by adding a REU (RAM Expansion Unit), or even a GeoRAM (basically a REU on steroids). SuperCPU would also be an option, but for me it's always blurring the line of "what is a C64" a bit too much, and it likely just makes it faster anyway.
- LeFantome 6mo agoHow fast is the “new” Commodore 64? Have not heard much about it since launch. Although, now that I look, it seems they are just shipping now. https://www.commodore.net/product-page/commodore-64-ultimate-basic-beige-batch2 https://www.commodore.net/product-page/commodore-64-ultimate...
- steve_taylor 6mo agoRAM can be increased to 16 MB and CPU speed to 48 GHz.
- brcmthrowaway 6mo agoHow does this compare to ELIZA?
- jll29 6mo agoJopsph Weizenbaum's ELIZA was rule-based and ran on even slower (1960s) hardware, but because it relied on simple pattern matching instead of neural nets, it would easily have been more responsive (the Emacs editor/operating system has an implementation included, start it with: M-x doctor RETURN). ELIZA was not written in assembler, but (different versions) in COMIT, FORTRAN and LISP. https://dl.acm.org/doi/pdf/10.1145/365153.365168 https://dl.acm.org/doi/pdf/10.1145/365153.365168
- Geee 6mo agoELIZA is better, because this doesn't seem to generate anything coherent. You can try the original ELIZA with DOCTOR script here: https://anthay.github.io/eliza.html https://anthay.github.io/eliza.html
- daemonologist 6mo agoYou can chat with the model on the project page: https://indiepixel.de/meful/index.html https://indiepixel.de/meful/index.html It (v3) mostly only says hello and bye, but I guess for 25k parameters you can't complain. (I think the rather exuberant copy is probably the product of Claude et al.)
- rob74 6mo agoIt seems to like getting its own output fed back: YOU> HI! HOW ARE YOU DOING? C64> BELON YOU> WHAT DO YOU MEAN BY THAT? C64> YOU DES YOU> YOU TOO! C64> YOU DESER! THIS THE SHIN YOU> DESER? SHIN? THOSE AREN'T EVEN REAL WORDS, WHAT'S GOING ON HERE? C64> YOU> THIS THE SHIN C64> YOU MAKE ME HAPPY TOO YOU> YOU DESER C64> YOU MADE MY HEART! W YOU> DES, DESER, DESERST? C64> YOU DES YOU> BELON C64> I LIKE OURON ME! WONDERFUL!YOU! YOU> YOU BELON DES C64> YOU MAKE ME HAPPY
- mixmastamyk 6mo agoJust reminded me of the random sentence generator program on my Vic-20. I had changed most of the words to all the bad words a preteen could think up. So many laughs with the neighborhood kids.
- deleted 6mo ago[deleted]
- Vaslo 6mo agoLoad”*”,8,1 Brings back memories
- borsch_not_soup 6mo agoInteresting, I’ve always thought neural network progress was primarily bottlenecked by compute. If it turns out that LLM-like models can produce genuinely useful outputs on something as constrained as a Commodore 64—or even more convincingly, if someone manages to train a capable model within the limits of hardware from that era—it would suggest we may have left a lot of progress on the table. Not just in terms of efficiency, but in how we framed the problem space for decades.
- dpe82 6mo agoYOU> hey C64> HELLO! RE SOUNDS ME. MEFUL! 60s per token for that doesn't strike me as genuinely useful. Very, very cool project though!
- chillingeffect 6mo agonot useful in a disaster scenario: YOU> HELP I'M DROWNING C64> YOU' HERE! YOU> OH NO I'M ON FIRE C64> IGLAY! YOU> IM BEING SWALLOWED BE A SNAKE C64> YOU> BIRDS ARE NIPPING ON ME C64> YOU
- Razengan 6mo agoReminds me of Terry Davis' random word generator :') Maybe there is deeper wisdom in there that we have yet to unearth
- numpad0 6mo agoNext-word prediction features always existed for flip phones...
- djmips 6mo agoDissapointed - there was no 6502 code in the GitHub repo.
- Hackbraten 6mo agoI think there is, in a way: https://github.com/gizmo64k/soulplayer-c64/blob/main/src/asm_simple.py https://github.com/gizmo64k/soulplayer-c64/blob/main/src/asm...
- arketyp 6mo agoI love these counterfactual creations on old hardware. It highlights the magical freedom of creativity of software.
- rahen 6mo agoA little disappointed to see PyTorch + Claude here. I was hoping for some "demo-scene" hand-crafted 6502 assembly, and hopefully training on the C64.
- NooneAtAll3 6mo agoso... it is vibe-code? meh
- rahen 6mo agoYes. The author mentions Claude for testing, but it was obviously used for the README and code as well. This is a giveaway for AI generation, from the docstring to the terrible opcode dispatch (Claude sucks at assembly or low-level optimization): https://github.com/gizmo64k/soulplayer-c64/blob/main/src/cpu6502.py https://github.com/gizmo64k/soulplayer-c64/blob/main/src/cpu... A human would use a proper dispatch table and wouldn't make excuses for a sloppy implementation ("Python is fast enough"). Besides, the author has an art and design background, which doesn't seem to match the deep knowledge of Transformers or assembly required for such a project.
- gizmo64k 6mo agoI am the subject of your investigation. So, in your world meta-programming is a bad thing? Fine. In my world it isn't. The transition layers are how I kept four implementations bit-identical through the test suite. If you prefer to hand-roll this toward the goal, that's your decision, your life. And yeah, I use AI where it makes sense. Architecture decisions are still mine. For the record: I'm from Farbrausch, so you are technically correct! The demoscene did become a UNESCO intangible cultural heritage a few years back, I guess that makes me an artist, FINALLY! :)
- pjmlp 6mo agoSame, however I do conceed having the whole assembler toolchain written in Python was also kind of cool, even if it may have been AI generated. Even cooler would have been to have the 6502 directly generated from the LLM.
- vintermann 6mo agoMaybe impressive in one way, but I'm also pretty sure a simple n-gram Markov model (a la Niall on the Amiga) would have a lower loss on the test set. Transformers don't scale down very well, in my experience - I used to train local models all the time as new ones were released, as I recall transformers were the first ones I couldn't get better results out of with my limited training data and GPU.
- bluejay2387 6mo agoGreat work! Though I see some people criticizing the usefulness of this. Are they being sarcastic are just really not understanding what is being discussed here? I can't tell. Maybe as an interesting follow up you could train the transformer on something with a more limited vocabulary. Spoken language is complex but a transformer can work on less complex domains like music or PET-BASIC code.
- gizmo64k 6mo agoThanks! The training corpus and code are in the repo if you want to try... Training takes just a couple of minutes on an RTX 3090. Don't get your hopes up too high, though. I can imagine that code would be harder, not easier. Even modest sized transformer models struggle with proper GOTO targeting. It would look like BASIC, but essentially it would be friendly gibberish too.