teddyknox

I wonder if machine learning could be used to model the probability distributions at a greater capacity, and thus reduce backtracking.

One might also consider placing the algorithm in the context of a generative adversarial network (GAN) to adapt the tile probability modeling ML component towards a pattern that is less distinguishable from a real city.

How'd you learn that you have this condition?

Did vorinostat do anything for this? One of your comments on this 6 months ago got indexed by a search engine and I just found it.

Love the modesty implicit in the short post.

Death metal is my go-to work music for when the fight with entropy feels like a losing battle. Especially as the rest of our capitalist society tells you to be happy all the time, death metal offers you the intuitive sense that you're not alone in the pain, and some solace in the fact that some people are brave enough to lament their difficulty out loud.

I think catharsis is really important and people should teach themselves to seek it the way they seek their professional goals, food and companionship.

Why do BBC articles do so well here?

Ello.co stealing their metaphorical lunch

Sometimes I use a 26 word language and it sure seem capable of saying everything...

Conventional processors will eventually run into physical limits of heat dissipation that will impede moore's law. Reversible computers are a way of circumventing this physical limitation because they dissipate less energy as heat.

When I think exabyte scale queries on a columnar datastore I think aggregations, but then I have this question: Why do we need to do exabyte scale queries in the first place? Wouldn't statistical inference via random sampling be faster and accurate enough?

(Granted, often times aggregations are happening after some filtering, at which point the relation being aggregated might be considerably smaller than exabyte scale.)

fish