I once heard someone say “What obstacles can I remove from your path?”. I think the whole philosophy is encapsulated in that one question.

Yeah, the Coaching Habit has "and what else?" as it's primary focus.

My suggestion would be to experiment with languages until you find one that you like more than the others and replicate the functionality of someone else’s software. Free yourself of the need to come up with a good idea.

If you choose a language that’s not widely used or no one is hiring for, don’t worry about it. You’ll find that the concepts you learn in any language are portable to all languages. Once you learn those, it will be easy to pick up new languages when you need to.

Bonus advice: when you find a language you’re good at, stick with it and get really good at it.

It's interesting that the Death Metal was the hardest to reproduce. I conclude that it's the most fundamentally human of all genres.

Well... they hardly tried all genres :)

It sounds like it can't handle lyrics or semantics that well so I suspect any genre where the lyricism is important would also be quite mushy and recognizably AI

The Beatles seemed to be the hardest music for JukeBox to emulate.

The sound sample seemed to fit the 'vibe', but lacked any discernible definition. Could it be that it's too sonically dense to easily reproduce? Perhaps this could be improved with a more tailored training set.

I think it was just the genre that was the least represented in the training data

dadabots here: haven't gotten good death metal with it. problem is there's not really much in the dataset.

(context: i make ai death metal & also i worked on stable audio). 100% it was a dataset problem. Diffusion models still work well when you train them on death metal: https://www.youtube.com/watch?v=rlsRMQzD_6Q

It sounds more like break core haha

I made a robot that cheers every time the Green Bay Packers score (American football).

https://imgur.com/a/JeiDCYR

The chassis is 3D printed and a Raspberry Pi is hiding, with a couple of speakers, in the base. The Pi connects via WiFi to the local network and checks ESPN’s publicly available JSON for that day’s game to determine if the score has changed.

I gifted it to a friend that owns a bar and wanted him to be able to move to new networks and reconfigure without using a computer. So, I wrote some python scripts that interface with the GPIO pins on the Pi to reset the device and broadcast a WiFi network and web interface that can be used to connect to other networks.

That last bit now has over 500 stars on GitHub!

https://github.com/jasbur/RaspiWiFi

Oh wow I built something just like RaspWiFi ten years ago. Silly of me not to open source it back then!

They’re in a de facto monopoly position with Reader, they don’t have to worry about users leaving for a faster product.

Probably, all of their best programmers are working on revenue generators, not performance.

I think what resonious is saying is that your particular job is unlikely to make you significantly wealthier than any others in your field.

Don't make huge sacrifices unless you have a realistic expectation of abnormally huge returns.

Google will give a relative measure of how busy the space currently is but doesn't give an exact number or a sense of how full a location is relative to any temporary capacity limits that might be in place.

This is a simple web site that I put together for small businesses that want to keep crowds small and avoid lines at their businesses while running at a limited capacity. It includes a simple app to keep tally which is then visible to people searching for you.

It's totally free for all to use and any feedback is appreciated!