mschulkind

For context, I'm not transcribing to distribute sheet music or anything, although I'm sure you could. I write down just enough when transcribing so I don't forget what I just figured out. I do it to practice my ear and learn songs.

That said, it's the fastest way to get a track into some player, define loop points easily, and then write down what I need to along with the player. I can jot down chords, lyrics, tabs of riffs, etc. I've tried tons of solutions over the years like sooperlooper, ableton live, reaper, winamp, youtube. this is by far the easiest, with just the right set of tools. It also doesn't do any of it automatically, so there's not even a temptation to skip practicing my ear.

I don't have an answer, but wanted to say that I started using Soundslice about 9 months ago and I absolutely love it. It does exactly the part of transcribing that I want done for me and nothing more, which is basically none of it except the boring stuff.

But surely the difference is 16 vs 24 and nothing to do with the sample rate?

It really depends on the peering contract. Most are not for transit, but rather just destinations, and generally the side that sends more pays, so that means more traffic to HE if tunnels are in use.

I'm surprised someone named BobbyTables2 wouldn't go straight for the proper way to check email PGP signatures...

I've found what works best here is just switching to every 2 weeks or every 4 weeks. If you have little to talk about in a 1:1, feel free to end early, and then double the length of time until the next one.

I've never used it because I feel like it'd make me sound like a weirdo, but I've heard this concept explained as BLUF, Bottom Line Up Front.

I agree, but these are also the exact constraints that lead to an early leader getting overtaken by a longer term, yet better set of plans. Not saying that's the case here, but given how much success Waymo has had so far, over really everything Tesla has produced, says quite a bit about the likelihood of the approach, even if it's not yet there.

This is an interesting viewpoint, but isn't it also solveable?

Just because the human in the scenario only took vision as input, why does that matter to the training data and the model? The actions are the same.

To put it another way, what about all the cultural context the human had, or the sounds, smells, past experiences at the same intersection, etc? Even Tesla can't record this, but I'm not sure that matters.

But why can't you apply all that same logic and processing to LIDAR as well. Maybe we're not there yet, but about about in 5-10 years when we are?

While I agree with basically all of this, and find the FSD on my Tesla to be quite useful, a question pops into my mind.

Why can't Waymo ALSO develop the same smarts and just also solve the sensor fusion issue such that they can use the right set of sensors in the right environmental conditions, and then leapfrog Tesla's capabilities?

Whoosh...

I love the thoughtful response.

I feel you on every point, but I'd point out that they sell VERY reasonably priced replacement parts for basically everything on the A1 Mini that I have that is worth repairing.

If you turn on LAN mode, it acts exactly like every other printer. You can print directly to it from any slicer over your LAN, or dump gcode on the SD card directly.