waleedka

Same here! I was going with the assumption that standard environments are going away since they haven't been updated for years.

I think you got it backwards. Which seems to be a fairly common mistake because, intuitively, we tend to associate the amount of work to the amount of value.

In Bitcoin, and other PoW blockchains, the protocol dynamically adjusts the difficulty of mining a new block such that it requires more work if there are more miners. Which also means that it requires less work if there are fewer miners, which is why it was easy to mine Bitcoin on a laptop in the early days but now it requires specialized hardware.

The causality path works like this: Price of the coin goes up -> it becomes more profitable to mine -> more miners jump in -> difficulty goes up -> cost of mining increases. This continues until there is an equilibrium.

One idea you might want to consider is to create a global function, let’s call it h() and pass all your human readable strings through it, like so h(“hello world”). This function, simply returns the same string. This is more explicit than relying on quote types. It also allows you to do interesting things such as logging everything to a text file and running a spell checker on it, or checking for wrongly encoded string, ...etc.

Actually I prefer standardizing on double quotes and I do that in my code on a regular basis. I know some people use a mix, sometimes single quotes and sometimes double quotes, which is fine, but I prefer consistency in this case.

You can now do it quicker with CTRL+Shift+V (Windows) and Option+Shift+Command+V (Mac). Both will paste without the formatting.

Does Swift have a large community beyond iOS apps? Last I used it was years ago, right after it was introduced by Apple. I'm curious if it has found growth in other areas.

> Construction of this data set consumed millions of compute hours

It's great to see such datasets shared publicly. I hope it achieves the intended purpose and spurs innovation in protein folding.

I’m very curious about the use of such cloud finder. But, to answer your question, the Mask RCNN model would be useful if you want to identify individual clouds. As in, find clouds surrounded by empty sky. Or, for example, you want to find clouds that look like a puppy or or a sheep. On the other hand, if you don’t care for identifying individual clouds and only want to find the pixels that belong to the ‘cloud’ class, then a semantic segmentation model would likely do better.

Also, while I don’t know much about your use case, using DenseNet seems like it might be an overkill since you only have two classes, cloud and sky. A lighter network might give you better results, especially if you don’t have a lot of training data.

I don't see this flag on my version of Chrome (64.0 on Mac). Are you on the beta branch?

Yes, totally agree. TF is solid and it’s still my goto tool, but the API has a very low elegance score, to put it nicely. Clearly the team has a lot of brillian engineers, but they’re missing the high level sense of design (yes, APIs do need good design as well) that puts everything together beautifully.

Not only the language, but have at least one line that says what this is. I can guess that it’s a hosted notebook service, but I can’t tell how it’s different from Jupyter Notebook. Is the difference in the language it uses, or are there other differences?

It gets worse, actually. People often, accidentally, click on the pen icon after highlight some text and end up highlighting that text permanently for all readers. And you, as the writer of the post, have no ability to remove that highlighting.