pythonwutang

Would this make them a “centi-corn”?

“Facebook data hacked by Google intern”

Bad: 1.0000 - Good: 0.0000

It really disliked this one, even though it probably would get attention on HN.

Chunking is the term I used because that's more relevant to the data science

If your intended audience are data scientists then why didn’t you mention Dask?

Doesn’t render well on mobile. The pictures smash the text to the right instead of moving it below.

Andrew Yang is the Trump of tech. And his brand of politics is more a dangerous threat to democracy than Trump’s is. His messaging and policies are just like Trump’s in that they’re dumbed down, optimized for social media likes and subtly enforce a world view where extreme income inequality is inevitable so let’s make the best of it. AI/tech isn’t going to kill the middle class by itself. This destruction will be assisted by technocracy propagandists like Yang.

By analyzing the blockchain and de-anonymizing bitcoin transactions, the agency was able to identify hundreds of predators around the world - even though those users thought that they could remain anonymous.

Who would’ve guessed the blockchain would help the government catch criminals!

How does this differ from Amazon Lambda?

Only read the landing page so far but it looks like Lambda with just Node support. Can someone correct me if I’m off?

Looks great! Thanks for the hard work Streamlit team. Our team started using Dash recently for an ML project and quickly got lost in callback hell and switched back to a notebook. This approach is so pythonic and elegant. Looks like it would handle our use case with much less code and callback related head aches. I’m excited to share it with our team!

I doubt 99% of the community is so humorously pessimistic. This functionality can be easily replicated in several databases (with triggers and the like). Generated columns l make a common pattern simpler and more explicit. Maybe it’s not a useful feature for everyone but it’s certainly not some instant tech debt like you’re implying.

This is just the beginning. Start microwaving some popcorn because this will be quite a glorious train wreck to watch! Hopefully the negative impacts are economically isolated.

Therefore, the best thing to do is to deploy your program without resource limits, observe how your program behaves during idle/ regular and peak loads, and set requested/ limit resources based on the observed values.

This is one of the author’s fatal assumption. The best practice I understand is to set cpu requests to be around 80% of peak and limits to 120% of peak before deploying to prod.

They set themselves up for disaster with this architecture where they have many idle pods polling for resource availability. This resource monitoring should have been delegated to a single pod.

Also it’s really unclear what specific strategy led to extra costs of 1000s of dollars...

“Why Haskell is important” according to a Haskell consulting company. So taking this article with a big grain of salt.

Haskell might be a great language but barely anyone (besides CS academics) uses it.

We use java and python in production because (among many other things) they’re very popular.

Popular languages have large archives of open source packages and easy to find communities that save enormous amounts of headaches and time. The opposite is true of Haskell, at least for now.

This is an attempt to push Lyft out of CA by raising the cost side of the equation but that cost will eventually have to be passed to riders, which will dramatically drop demand. If the minimum wage law passes and they subsidize rides long enough to edge out Lyft then they finally get the monopoly they’ve been promising investors for the last decade but they also lose a huge amount of their TAM. The laws of supply and demand will eventually come into play.

And of course once they get their monopoly they will raise prices further to get profits and at that point I’d guess they would only be slightly less expensive then Taxis were before all this gig economy craziness.

What an immature and rude way to criticize a young open source project. I’m disappointed that so many in our community appreciate this disrespectful writing style criticizing our k8s supporting peers.

Secondly, developing on Kubernetes “sucks” compared to what? Mesos? Docker Swarm?

Maybe this engineer is still frustrated with Tilt’s failure as a business (https://www.fastcompany.com/3069164/how-tilt-veered-off-cour...) and Airbnb imposing changes on his workflows like how they deploy their apps. If that’s true then I hope he finds more healthy and mature habits to manage his anger.

FastAPI is my new favorite python api framework. Pydantic and starlette are such powerful combo.

https://github.com/tiangolo/fastapi

At some point in the future, we will use programmable bacteria for treatment

Will bacteria be “programmable” in the same way that a computer is?

Hard to believe so maybe that’s not the right word for it.

If it will be then we will, in a way, be monkey patching natural selection’s code.

Testing would also be a pain!

There are a couple tests available that measure divergent thinking, which is a part of creativity, but I’m not aware of any others.

There certainly is an abundance of anecdotal evidence that marijuana boosts creativity from artists and musicians.

This focuses on IQ and memory but doesn’t it also impact creativity?

I’d be interested in seeing studies about marijuana’s impact on the brain’s creative abilities to contrast with this.

Because the devil’s advocate in me thinks “We have enough high IQ people in this world and not enough high creativity people.”

They cannot use anything except an algorithm to recommend videos

That’s assuming recommendations need to be personalized. They could recommend at a higher level to groups of people using attributes like age range or region.

I’m not a fan of their personalized recommendations. It’s algorithm overfits my views to recommend videos extremely similar to videos I’ve recently watched, which isn’t really aligned with my interests.

If they took a completely different approach (not personalized) it could really impact the UX in a positive way.

I’m curious where the term “Superior General Knowledge” in the headline came from. It’s not explicitly defined in the article and ironically is not an intellectually humble way to describe the article’s conclusions.

Are these apps available on the Apple App Store?

Try Django Rest Framework with React