dandan

The point of this demotivational poster is to ridicule the sort of person who thinks that this is pathetic.

It’s not actually saying that the guy is pathetic for having his hobby, it’s actually the opposite.

Yeah, something in the algorithm that prevents one magazine or one instance dominating would be the best approach.

Kebin

To get even more pedantic…

It’s defined on how far light will travel in a vacuum in the time it takes caesium-133 to do a certain number of transitions between hyperfine ground states.

It’s cool how almost all units of measure are defined on caesium

Looks good. What does steamed mean in this context?

Yeah, a flair or a robot is way quicker than a powered espresso machine.

I’ve been trying to optimise my workflow using a stopwatch and doing as much in parallel as possible. The key is to have water boiling and beans grinding simultaneously, and then milk heating and espresso extraction simultaneously.

I can make a flat white and be all cleaned up and packed away withing 4mins.

Process:

• add water to kettle and start boiling
• add beans to grinder and start grinding
• get robot off shelf and put into position with scale
• put milk into French press and in the microwave with time set to 1min (but not yet started)
• grinding has now finished. WDT and tamp.
• kettle has now boiled, press start on microwave
• water into portafilter and press (~30sec)
• empty and clean portafilter
• remove milk from microwave, froth, pour.
• put away robot, clean french press.
• ☕

I also have a robot and can’t vouch for it highly enough.

Came from aeropress like OP, and I’ve found it very similar to the aeropress in terms of flexibility.

The only downside for me is the effort required in temp management to do really light roasts. But I assume this would be the same with the original flair.

Is creamer used in countries that don’t regularly have milk in the fridge? I’ve never heard of anyone using it in Australia, but I’ve also never seen the need when everyone has milk and sugar readily on hand.

Ahh ok. I didn’t want to assume as I’m not familiar with the details.

It’s the defacto term for how we fit a statistical model to data, unrelated to any copyright concepts. I’m pretty sure we called it “training” back in 1997 when I was doing neural networks at uni, and it’s probably been used well before then too.

Neural nets are based on the concept of Hebbian learning (from the 1930s), because they are trying to mimic how a biological neural network learns.

This concept of training/learning has persisted because it’s a good analogy of what we are trying to do with these statistical models, even if they aren’t strictly neural networks.