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xiao_haozi

Steam link does it, and fast enough to play games with no noticeable latency.

Not sure what the magic is, though.

GPU cluster? You might need to tweak the pytorch code, but you can disperse across multiple GPUs very easily with pytorch.
While I see your point, I don't think this makes sense historically. Dictionaries never supported such behavior before so you'd be introducing a new core concept to a dictionary. But moreover, you'd be changing the type of the value only on duplicated keys, and what about if you were to add another value of 2 to a? Are you making this a set, and why? I think it would come with too many caveats and assumptions in the PEP.

I'm not saying you have a bad idea/logic here, just that I'm not sure it's the best thing for the dict.

Yes, absolutely. However, we know from leaks over the past decade that this is not always the case for this types of surveillance methods (the methods being made public).
Ah, okay. That makes sense.
I wonder why they would make public this information. Wouldn't it be advantageous for them to have those with criminal intent continue to utilize the platform and the police to have an established surveillance method? Or would it be unavoidable and become public information in criminal complaint filings and such?
Re:A Gentle Visual Intro to Data Analysis in Python Using Pandas on Thursday November 01, 2018 @09:04AM (#18353480)
Can you use groupby for your stratified sampling work?
I didn't see any, but you could stitch them together, e.g. https://vangoghmuseum-assetserver.appspot.com/tiles?id=56466...
You don't happen to have a writeup about your hardware selection and how you configured these do you? I've been thinking of going this way in a new house.
Re:End-to-end differentiable learning of protein structure on Sunday February 18, 2018 @08:25PM (#16410101)
Yes! And I'd also add that there are others that come into play...

* Elucidating function by identifying similarity to other known structures

* Finding novel signaling mechanisms (see work on PHinder)

* Modeling co-receptor/ligand dynamics

* Identifying function of orphan receptors

* Working with ancestral genes by identifying descendant structure

* Classifying and clustering proteins based on solved structure

* Learning new biochemical mechanisms through active vs inactive state structures

...

I find that the entirety of the author's blog is of similar quality. Even though a very specific context is provided as a point of conveyance, I find that the style of presentation is effective in allowing for generalization of the concepts for other use cases. There are also some really great gems in there - e.g. the fashion MNIST!