Soak and rinse, but the soak water should be boiling when the dry beans go in.

Alkaline. Sodium Carbonate (baking soda) or calcium hydroxide (lime) work. Throw away the cooking water. This has to be done carefully, as too much of either can give the food a mineral taste and/or dissolve the beans entirely.

Fermentation also works. Lactic acid (like kimchee or pickles) helps a little. Koji (either added or grown on the beans themselves) helps a lot. Both will have a big impact on the flavor and what the beans will be good for in the end.

I don't know the details, but probably you would want to seek unpredictability in a higher level representation of the observed state. White noise is highly unpredictable per pixel, but will get a very predictable representation after a layer or two of featurization if the features are trained/designed for real world observations.

There is so much humans should be doing to make our brief existence a little more happy and fulfilling. Little of this has to do about contributing labor.

Americans have a deep reverence for their personal brand, but it's worth considering they don't install their government model on countries they conquer. Japan, Iraq, Germany, etc are all Parliamentary.

I wouldn't be too dismissive of the potential here.

The wine is also decent, and many bottles are quite affordable. They make a lot of Italian grape varietals that are a little hard to find elsewhere.

Plenty of people will have plenty of issues with a major corporation. But it's worth pointing out that McDonald's is one of the most prominent fast food chains which has no problem with animal abuse in terms of products from horribly treated livestock animals. They have trouble even making their french fries livestock-torture free .

Maybe this issue doesn't personally matter to you, but it does create a huge problem for a company that does something so shamelessly unethical.

This essay kind of describes this sort of store as one would describe a walk through the woods. But the purpose of a walk in the woods is so distinct from the purpose of shopping that no comparison can be made.

One big reason homes are priced so high in places like the USA is because home loans are already government subsidized. When people think of what they can afford, they look at their net monthly mortgage payment less the income tax break. And prices seem to rise to meet whatever monthly payment buyers can afford.

This is a very common feature of delirium in people. Chatting with an LLM seems a lot like what it would be to talk to a clever person with encyclopedic knowledge, who is just waking up from anaesthesia or is sleep talking.

I had a friend that was the victim of a local news "expose" on this. Just a harmless high school geek who thought it would be fun to combine the School blueprints with his CAD course to build a "fun" way of digitizing the blueprints.

The main lesson we learned from this exercise is that the Duke Nukem 3D pistol is totally OP when used in realistically proportioned hallways. Auto-aim and all.

The other lesson we learned is that local news investigative reporters care more about a compelling story than to represent the mundane truth.

The biggest defeating problem for pure AI teams is that they don't understand the domain well enough to know if their data sets are representative. Humans are great at salience assessments, and can ignore tons of the examples and features they witness when using their experience. This affects dataset curation. When a naive ML system trains on this data, it won't appreciate the often implicit curation decisions that were made, and will thus be miscalibrated for the real world.

A domain expert can offer a lot of benefits. They could know how to feature engineer in a way that is resilient to these saliency issues. They can immediately recognize when a system is making stupid decisions on out of sample data. And if the ML model allows for introspection, then the domain expert can assess whether the model's representations look sensible.

I'm scenarios where datasets actually do accurately resemble the "real world", it is possible for ML to transcend human experts. Linguistics is a pretty good example of this.

If we want to unscrew ourselves of the ticking time bomb we set, we need all the "clean" energy we can get, and then some. Nuclear is potentially an existential requirement to the mix.

We need more reliable and consistent base energy in overabundance fast. Nuclear can do this without creating a climate catastrophe. Even if you need energy dense chemical fuels, nuclear energy can be used to create these without net climate impact.

Hydrocarbon fossil fuels are the addiction that modern society needs to break from. Nuclear is an excellent "methadone" to ease the transition. But society seems to be split between denying there is a problem at all, or insisting we're all ready to go "cold turkey". Neither approach is reasonable to bet the continuance of human civilization on.