Eager

Open weights is one thing, but we don't even have that with OpenAI at least.

Even then, open weights is like me checking in a .exe and acting surprised if people look at me funny.

I'm definitely in the camp where all the artefacts are provided along with fully reproducible build and test environment for anyone who wants to retrace the steps.

Whatever 'open' means, I don't think it is eight shell companies, not even weights provided and closely guarded secrets around how RLHF, alignment and safety testing is carried out.

In fact, you would think that being 'open' about at least alignment and safety testing procedures would be the least one could expect.

I do understand that revealing these things may disclose zero day exploits for bad actors, but on the other hand, being open for inspection is how things get fixed, and I've never been a fan of security through obscurity.

I can't tell if you are joking.

It seems like you are implying the reason we do stuff is to make money, or at least the main motivating factor for you, or you believe it is for most people.

I started working in a factory when I was about 13 casually, and by 14 I was putting in enough hours for my technical apprenticeship.

During those years I did get paid, and I was thankful for it, but I definitely wasn't doing it for the money, and I was still going to school and then to college in parallel.

I'm sure things are different these days. It just makes me sad to think personal progress is somehow conflated with earning money.

With regard to the article. I think given what we know about social networks and young minds, it's already been shown to be a toxic mix. Getting kids on the capitalistic treadmill so young seems extremely cynical and it really does concern me.

A few months ago I made a neat little linux utility.

It was a drop in replacement shim for an arbitrary executable that would pretend to be the original when invoked, fork off the original and hook up to its stdout and stderr.

The error output was then fed to a custom GPT assistant that knew what program the errors came from. That assistant was tasked with turning the original errors into friendly human readable form. The output from the assistant was then sent out of the shim stderr.

It worked very well, but then I got really sick and wasn't able to work on it anymore.

I was using it for GCC / Clang errors because I had become tired of staring at heavily nested compiler dumps for concept/template issues, but you could use it for anything of course.

It would be a nice project for someone to build again, do it properly and generalize it since it doesn't look like I am going to be bouncing around again for a while.

This is rather excellent!

It would be great to have a VST or CLAP (preferably) plugin that hosts strudel and can be hosted in-DAW

It might also be nice to have a VSCode extension that let's you experiment in live mode like the guys at cmajor.dev have.

Finally, I could see this working really well with say cmajor in general or for embedded synthesizer development on say the Daisy Seed if there were a native version.

In any case, it's all great as it is. I will give it a try integrating with Bitwig this afternoon.

I don't know the pharmacology, but it is well known that Saffron makes you happy and a bit giggly.

The grocery store relies on the mystique of the thing. The people making those expensive jars probably also seed articles online about it being extremely expensive. Then when the average person goes to the store they look at it and aren't shocked by the ridiculous price because somewhere at the back of their mind they will have read it is worth more than gold. lol. Meanwhile, anyone in the know is buying it by the wheel for quite reasonable amounts, and likely better purity.

Grinding with sugar is definitely the way to go. I generally buy a big wheel of Iranian Saffron on eBay or a Persian shop, then grind it all up in a mortar and pestle with some sugar and store it in a spice jar in a dark cupboard. Then when you need it you don't need to be faffing about. If you want to be fancy, save a few whole strands that you can add to rice for decoration, but using whole stamens is really not necessary.

Oh that's a nice one. I think you are on to something that if you want to go beyond push button output you really need to think holistically about what you want to achieve.

My experiments taught me that it is an instrument that is easy to approach but hard to master right now at least.

It's kind of weird because you have to play it through writing text, which is super strange.

Everything I have done previously has been very in the moment with keyboards or guitars or whatever. With this I had to put a lot more thought in ahead of time, and try to put myself in the position of the generator and how it might take my prompts and convert them.

There is certainly quite some thinking that has to go on. How to describe the sound you are looking for is a little bit unusual.

I am finding it quite fascinating anyway, and I really believe it can be tasteful if done right and as the tools improve.

As far as covering specific artists, it isn't something I am attempting, it's more about the feel for me. I imagine people who do that have their own tricks and techniques.

As far as I know, Suno blocks any mention of specific artists. Probably you can jailbreak it, but I don't know about that.

I agree in especially the first one. It was quite a challenge from the original content as the bitrate is quite low still, and in that particular case it was quite severely compressed. I had to dig quite deep to get the headroom back.

The last one was my first attempt.

I think the middle one is okay considering. By the time I got to that I had figured out how to get Suno to create multiple takes with much more open mixes, which left me a lot more latitude in the studio.

I expect I will get better at it, and I don't doubt the compression artifacts and the rest will improve.

To me at least, it is quite impressive where we are at. A ways to go, but very promising.

You try your best, and if you provide enough examples, it will undoubtedly get figured out.

I have tried feeding some of the foundation models obfuscated code from some of the competitions.

People might think that the answers would be in the training data already, but I didn't find that to be the case. At least in my small experiments.

The model's did try to guess what the code does. They would say things like, "It seems to be trying to print some message to the console". I wasn't able to get full solutions.

It's definitely worth more research, not just as a curiosity, but these kinds of problems are good proxies for other tasks and also excellent benchmarks for LLMs particularly.

This is why round-tripping the code is important.

If you decompile the binary to source, then compile the source back to binary you should get the original binary.

You just need to do this enough times until the loss drops to some acceptable amount.

It's a great task for reinforcement learning, which is known to be unreasonably effective for these types of problems.