bulldoa

> minimum standards to get called into interviews.

I am a bit curious on what is the minimum standard? It does feel to me (an outsider that took 1 class of ML in college) that you need at least Master in ML to get intuition on the probabilistic and linear algebra theory behind ML concepts.

curious, what are some cool application of SVD?

>Now I'm thinking of deploying k8s at home

Are we talking about k8 base on your own server rack at your house?

Do you have a recommended tutorial for engineer with backend background to setup a simple k8 infra in ec2, I am interested in understanding devops role better

Do you have a recommended tutorial for engineer with backend background to setup a simple k8 infra in ec2?

does brave route calls through their own server or is this also p2p?

what kind of mathematical models do you guys use (like convex optimizations?), I am very interested in this subject and would hope to learn more.

Whats your opinion on postgres vs nosql like cassandra and aerospike, fundamentally is there any reason that postgres can't scale as well as nosql? If I store key value in postgres and add read replica to scale read and partition to scale write will I not be able to keep up with other nosql solutions? If so what are the reasons?

Does min account history + min karma to comment enforcement helps?

Woah, I didn't know there is an entire ecosystem of contract job and auditors for big projects. How do companies usually hire contract jobs (outsourced HR, upwork, Accenture)? And how do they hire auditors?

is kotlin slow to compile

May I ask why do you think kotlin is best designed?

Do you guys accept contribution from junior devs (2-4 years out of college that have no compiler experience)?

might be a dumb question, but how do you render frontend server side? Is the content of the UI dynamically generated in the backend and serve as a static page to users?

Why would they do that tho? Doesn't that encourage fraud and damage their brand? I am just scratching my head trying to understand the benefit of doing that besides logistic cost?

I am confused, if a new model beats randomly selected randomised model 100% of time for each experiment why does it matter if randomised model beats other randomised models? Are they only comparing against the subset of worst randomised models?

Isn't sparse recommendation for videos kind of solved in netflix prize, where the winner uses SVD to extract signature characteristic and recommend videos base on that?

That sounds like a super cool job, may I ask how did you started?

> It's a problem with a thousand solutions. It's just a matter of getting costs down and production up

Can you source this? I heard of molten salt, gravity storage etc... but I have not read any paper stating we can scale those solution to 50% or even 20% of our current grid usage

ah, that make sense, I think another user point out that spawning n goroutine does not actually spawn n physical threads but rather queue n task to m thread in the pool, so if we exhaust m thread, n-m task will be blocked.

Thanks for the explanation

I wonder what is the point where each trade off make sense (ie. what is consider heavy computation vs light computation, it probably is related to OS thread allocation time)

hmm, why is that a bad thing, if your entire thread is synchronous shouldn't it technically be blocking? Or is OS thread the main thread?

> since hot loops can block a whole OS thread

Asking as a beginner, what does the above mean?

Not sure what does hot loop means, and why does it block Os thread

Not well verse in the subject, do people develop game engine in garbage collected languages? Intuitively I would think game engine requires absolute performance

Are there recommended resource for understanding and applying these type of problems? I am quite interested in optimization and its real life application, currently reading linear optimization by bertsekas

i am not questioning the intent, but I just wonder how would one support content creators besides donating money?

Can anyone recommend readings on what are the trade offs between graph database vs key value (whether its column base cassandra, or key value base aerospike...etc) and traditional acid compliant db (postgresql)

Out of curiosity, why is android struggling? What aspect of it needs improvement?

Can you recommend textbook on these topic?

What metric are we basing on here?

One of the key quality that hyperloglog relies on is that the action of hash distributes any input to any output with equal probability (eg. any input have 1/m chance to be in a particular point in output space where m is the cardinality of the output space)

I can't seem to prove this rigorously, am I understanding the paper correclty?