Wheatley became an Astronomy professor.
Readit Newsilovewhiskey commented on An exoplanet has been found in the ‘Neptunian Desert’ phys.org/news/2019-05-for... · Posted by u/lelf
ilovewhiskey commented on On FPGAs as PC Coprocessors (1996) fpgacpu.org/usenet/fpgas_... · Posted by u/zpiman
>So as long as FPGAs are attached on relatively glacially slow I/O buses
-- including 32-bit 33 MHz PCI
GPUs are on the PCI bus, aren't they? Has something changed in the last two decades to increase bandwidth?
PUT IT ON INFINITY FABRIC
ilovewhiskey commented on Linus Torvalds apologizes for his behavior, takes time off lore.kernel.org/lkml/CA+5... · Posted by u/fejkp
Post-scarcity is, at best, a distant fantasy.
Ergo, sufficient resources to forgive everyone, do not exist.
Ergo, it is best for any person to not expect forgiveness.
It's not a perspective; it logically follows from reality.
First, you are intentionally limiting the scope of my claim.
"Unforgiving" is just a synonym of "harsh", "challenging" or "adversarial", not about actual person forgiving someone.
Second, your logical proof is wrong. The existence of resource scarcity in the global scale does not mean the global resource scarcity, some places may have enough resources.
ilovewhiskey commented on Linus Torvalds apologizes for his behavior, takes time off lore.kernel.org/lkml/CA+5... · Posted by u/fejkp
>In your example - what's the point of thicker skin if people simply don't say mean things to each other?
You can never control other people's behavior, only your own. Learning to deal with mean comments is a valuable skill.
> You can never control other people's behavior
This is another way to say
> we believe the world is harsh and unforgiving
You seem to have internalized this perspective completely.
ilovewhiskey commented on Learning Plannable Representations with Causal InfoGAN [pdf] arxiv.org/abs/1807.09341... · Posted by u/stablemap
This approach is very similar to a AAAI18 paper [1] that also finds a binary representation ("plannable representation") using VAEs and performs planning algorithms, but the difference is that they included some experiments for continuous abstract states.
I personally prefer VAEs because GANs are hard to train.
[1] arxiv.org/abs/1705.00154