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tash9

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- How do they take a business problem and model it into code - How do they debug their own code - Is their code easy to read - Do they name their variables/fields/methods/classes in easy to understand and consistent ways or are the names confusing or inaccurate - How do they take constructive criticism - How collaborative are they - Do they think about the problem first or do they just start hacking away - When asked to add a feature to existing code, do they start hacking or do they write out a test describing the new functionality first - When confronted with vague requirements, how well do they ask questions to get the information they need - How much experience do they have with algorithms, database design, systems design, building things so they scale well

My hot take: this is actually really good (and would be fantastic if all the big tech followed suit).

Why? Imagine a world where big tech was cool with remote workers. They would be able to out-pay and acquire all the best talent, everywhere.

With this self-imposed restriction, this leaves a big pool of high end talent able to be recruited by smaller start-ups who ordinarily wouldn't be able to compete on comp, benefits, and stability.

If you're talking about small scale phenomena (less than 1km), then this wouldn't help other than to be able to signal when the conditions are such that these phenomena are more likely to happen.

One piece of context to note here is that models like ECMWF are used by forecasters as a tool to make predictions - they aren't taken as gospel, just another input.

The global models tend to consistently miss in places that have local weather "quirks" - which is why local forecasters tend to do better than, say, accuweather, where it just posts what the models say.

Local forecasters might have learned over time that, in early Autumn, the models tend to overpredict rain, and so when they give their forecasts, they'll tweak the predictions based on the model tendencies.

I would think heavy metals would be a much bigger issue wrt water contamination from a health point of view.

Not that the anaerobic sludge is great, but I would rather see a bigger push to recycle used electronics.

As far as methane, am in total agreement there. It's probably even better to incinerate paper products (if you are not in a subtropical region like LA).

But the volume of compostable material is small compared to the overall trash volume, right?

Aren't we talking about a negligible quantity relative to amount of effort and (potentially) negative sentiment amongst swing voters?

Maybe I'm missing something but I've never understood the point of composting.

- It's a hassle.

- You can buy good compost for very little at the hardware store that's produced at industrial scales

- Landfill space is not a precious resource in most parts of the world

- Your garbage will still turn into compost, just in a landfill

Where is the upside?

edit b/c I don't know how to format things

Giannis Antetokounmpo. He's been great for almost a decade and everybody still loves him. Growing up dirt poor for most of his life probably helps w/ being a great guy, though.

I think what he's trying to say is that a human has limited time to analyze variations, so they would typically analyze the "best" move for a given situation.

But if you make a suboptimal move, then you are going down a path that is less analyzed and thus you are likely to have an analytical advantage.

So while the board state is well known, what your opponent has researched is not known, or partially known (since players have favorites and predispositions).

It's not that much better than the normal network of AMS sensors. For one, it doesn't give you wind speeds at various levels (critical for predicting weather).

Second, it doesn't give you any additional readings over oceans, which is where the data is lacking in the current network of data.

It does give you more robust surface temperature readings in cloudy areas but that doesn't really help you predict the weather significantly better.

Source: degree in atmospheric sciences