stephenhandley

TLDR: pressed record on cassette tape recorder and recorded onto cassette tape

Seeing more flies than cats

I cannot imagine anyone who works with audio regularly would realistically consider replacing Ableton/Logic/ProTools/Reaper/etc with whatever recording experience this provides (no screenshots doesn't help your pitch).

The versioning idea is interesting and something many musicians have to contend with as they work on songs. Personally, I wouldn't want the complexity of take-level versioning, but pinning audio and mix automation to a given mixdown could be useful for tracking the history of a song. It might be more effective to approach this as version tracking / collaboration layer around existing DAW formats rather than a full replacement.

/)_-)

https://www.amazon.com/s?k=headphones

This is the first I'm hearing an aeropress 30 second plunge time, what's that about?

"We’re currently experiencing issues" https://status.openai.com/

Hammer meet everything is a nail

Start your own company.

this is awesome. would suggest not randomizing the tempo on regenerate, and if it was already playing, when hitting regenerate, keep it playing. that would make it easy to quickly audition loops at a given tempo with a single click

I guess Ozempic face is what "anti-aging" looks like? Nothing to see there lol. The backlash on GLP-1s is gonna make thalidomide look like penicillin.

Effective TODOs capture a code-level design tradeoff and any associated debt which

- won't have sufficient positive impact on the bug/feature you are working on

- you don't have time to address at that point in time

- are significant enough to require pay down later

How to address them in terms of tooling and process is a way bigger question

This almost as great as how much I love that this gets posted like once every two weeks

Outlaw corporations from owning single family homes.

UI design gripes posted on site with icon that doesn't link through to homepage

I don't get the pick the muscles thing almost as much as I get the open source fitness thing.

Super fun! Would be cool to be able to challenge someone after going through a round. Also maybe clear CTA after round on way to sign up to save your score.

cool app. maybe its already possible but i'm missing how but would be awesome if dragging a new node between an existing connection it would automatically insert it between the nodes to avoid the steps to disconnect / reconnect

looks cool but wasn't able to get audio output from the stackblitz demo

It's basically just a wrapper around WebAudio, I've generally just used the builtin nodes, but I think you could do sample-level processing with this? https://developer.mozilla.org/en-US/docs/Web/API/AudioWorkle...

love the demo https://bungee.parabolaresearch.com/change-audio-speed-pitch

have you thought about wrapping it as an audio unit or vst via juce/clap/iplug so its usable in a daw?

https://juce.com/ https://cleveraudio.org/developers-getting-started/ https://github.com/iPlug2/iPlug2

You didn't even like this one!? https://idroppedmyphonethescreencracked.tumblr.com/post/9350...

That said, guessing a bunch of those are meant to be concise examples.

For what its worth my quick take on a lot of the text-based sound coding environments [1] is that they provide a relatively quick way to approach creating audio programmatically differently compared to a more traditional spatial / grid-based daw.

One nice thing about Cracked is that you can treat it as an audio input in Ableton, Logic, etc. and so you could use it to generate a sound to sample / process further in a daw arrangement. I had stumbled across it originally from the author's Wikipedia page which mentions that he uses it to create longer albums / pieces https://en.wikipedia.org/wiki/Bill_Orcutt

Interview with him about it https://www.thewire.co.uk/news/41540/bill-orcutt-releases-op...

[1] https://tidalcycles.org/ https://sonic-pi.net/ https://chuck.stanford.edu/ https://supercollider.github.io/

WebAudio-based library that provides quick way to set up a web audio graph.

Desktop wrapper: https://github.com/billorcutt/Cracked

Cat examples: https://idroppedmyphonethescreencracked.tumblr.com/

Honestly was not aware of that guideline. Insinuating that I was someone trolling for this discussion is a stretch.

If you're under the impression that all the content on here is 100% human, that's probably slightly optimistic, and the reason why I labeled it explicitly rather than regurgitating / rewording. That said, I'd rather read GPT output than skim the meta-discussion that ruins so many HN threads. Totally stoked that we're now contributing to that rather than talking about the actual content.

I believe they'd mainly need to be strategic about where and how deep they were radiating into the surface since there wouldn't be atmosphere that would trap heat.

Lol you mind giving me a quick heads up on what have you contributed other than this meta gripe? Any concrete response to the actual questions I'm asking or just a soapbox?

I'm wondering why this is being proposed to be in space rather than at the lunar poles? Is it a latency question? I'd assume if this is being used for LLM training purposes and it is a relatively long training run, latency is less a pressing concern than bandwidth constraints before / after training?

Wouldn't the moon would provide better environment for debris shielding and regolith could be used to passively dump heat?

I'm way out of my depth here, so of course I asked ChatGPT 4o to come up with a three paragraph concept sketch for an LLM training facility based at one of the lunar poles:

<gpt>

A lunar pole is an ideal location for large-scale LLM training due to its unique advantages in thermal management and power availability. Near-continuous sunlight at the “peaks of eternal light” allows for stable solar power generation, while nearby permanently shadowed craters provide ultra-cold regions that can act as natural heat sinks — solving one of the biggest challenges of orbital compute: radiative cooling. Compute clusters could be housed in regolith-insulated modules, with heat piped into crater floors or dissipated through passive radiators embedded in the lunar terrain.

The architecture would be modular: prefabricated training units delivered by landers (like Starship) could be arranged into scalable compute farms. Power would be provided by solar arrays on crater rims, with supercapacitors or RTGs as backup. Data transfer wouldn’t require low latency, just high throughput, so high-gain antennas or laser links could periodically sync model weights back to Earth. With no atmosphere, lunar surface conditions are harsh but predictable, and maintenance could be handled robotically.

Compared to the estimated $480 trillion needed for space-based radiators to support orbital training, a lunar facility could achieve similar scale at orders of magnitude lower cost, leveraging the Moon’s surface as both a structural anchor and a thermal reservoir. As launch costs drop and lunar infrastructure matures, this becomes a compelling direction for off-planet AI training.

</gpt>