peterthehacker

Depending on your personal situation you might want to seek professional help. But here are some ideas to get you started:

Practice making eye contact especially when someone is opening up about their feelings. Then say things that show you know how they feel. Human brains can mirror feelings, like pain, from another humans [0]. So, to empathize with someone you need to get on their level emotionally and really feel how they are feeling.

[0] https://www.ted.com/talks/vilayanur_ramachandran_the_neurons...

> Ronald Barrett and colleagues from the Department of Anthropology at Emory University in Atlanta have gone as far as to suggest that the emergence and re-emergence of disease threats owing to globalization and antibiotic resistance is a sign that we’re entering a “third epidemiologic transition” comparable to the rise of infection at the dawn of civilization and its fall in the last century and a half.

That is an ominous prediction. This coupled with climate change makes the future look pretty bleak. No wonder Bill Gates works so hard on these problems.

> Asian countries (where rice was available) where able to achieve and sustain far higher population density than areas fed by wheat

Do you have any sources/data for that point? I’m curious why rice would impact population density differently than wheat.

The Contact field can point to a landing page.

> A link or e-mail address for people to contact you about security issues. Remember to include "https://" for URLs, and "mailto:" for e-mails

Using a landing page should improve the signal/noise ratio. Google, for example, points to a landing page [0] and GitHub points to their HackerOne profile.

[0]https://g.co/vulnz

[1]https://hackerone.com/github

> Our review found that the commenting climate in Sports is better than elsewhere on the site. The conversations are more relevant to the stories, and there are fewer personal attacks. We’ll now be focusing all of our moderating resources on Sports, and our Community Guidelines will be strictly enforced.

I wonder if this is a common pattern. Perhaps sports stories naturally encourage healthier discussion.

Intuitively it makes sense. Talking sports with someone can be a great icebreaker if they come from a totally different background.

I think that this is an important question and I disagree that “YC has lost its way”. I think that we’re seeing more and more companies come out of YC that have a bottom up, Growth/Product focus instead of the traditional Sales/Tech focus B2B companies have historically had, which makes companies like this look like nothing special tech-wise, but look at their love on PH . They’re onto something.

Martin Casado, from a16z, has a great post/talk about this trend. https://a16z.com/2019/08/09/video-growth-sales-and-a-new-era...

It’s too early in the morning to yell. If you disagree with the OP, then calmly explain your disagreements with the post and cite sources if needed.

Edit: From the HN guidelines [0]

> In Comments: Be kind. Don't be snarky. Have curious conversation; don't cross-examine. Please don't fulminate. Please don't sneer, including at the rest of the community.

[0] https://news.ycombinator.com/newsguidelines.html

But if the company shuts down then they won’t be able to maintain the app anyways so as a user I wouldn’t want to use the app anymore and maybe have a copy of my data. The company could be required provide a download of the user’s data (encrypted) before shutting down.

From the end user’s perspective, what would the advantages of an app without centralized storage, like these, have vs. an app with E2E encryption and traditional centralized storage? If the end user’s data is encrypted on the service provider’s side and cannot be read without the user providing a key, doesn’t that achieve the same level of privacy from the user’s perspective?

Yes, you can use dask’s lower level APIs, like futures [0] or dask delayed, and it’ll just pickle the python objects. Dask provides a group of collections APIs, like dataframes [1] and arrays that use more efficient serialization methods.

[0]https://docs.dask.org/en/latest/futures.html

[1]https://docs.dask.org/en/latest/dataframe.html

Apache Pulsar is a streaming platform more comparable to Kafka. It doesn’t have built in parallel computation APIs like spark. You can hook spark streaming up with pulsar as a data source though.

https://pulsar.apache.org/docs/en/adaptors-spark/

I would be interested in seeing some spark v dask benchmarks too. Haven’t seen any yet though.

In my experience, Dask really shines when you implement custom numpy computations that could only be done in spark UDFs. We saw a decent performance difference there, but for common built-in computations I’d imagine that spark has better performance.

Edit: after some googling I found this paper with benchmarks.

https://arxiv.org/pdf/1907.13030.pdf

> Results show that despite slight differences between Spark and Dask, both engines perform comparably. However, Dask pipelines risk being limited by Python’s GIL depending on task type and cluster configuration. In all cases, the major limiting factor was data transfer.

I’ve had a lot of success with Dask lately. It’s comparable to spark in some ways [0]. Being written in python and built on top of pandas/numpy it allows much more flexibility. It’s also easier to get adoption from data scientists who are usually more comfortable with python than scala. It also has great tools built on top of kubernetes making deployment quick and easy [1].

[0]https://docs.dask.org/en/latest/spark.html

[1]https://github.com/dask/dask-gateway

I’ve been feeling the same way about modern HTML/JS/CSS. The tooling has become too cumbersome and languages like TypeScript, SCSS and even Elm illustrate how the community needs a new frontend toolset. On top of that tools like React Native and Electron add even more complexity to the problem. I’ve recently started looking at Dart/Flutter - https://flutter.dev/ - which looks like it might have some potential to fix a lot of these problems. Has anyone here used Flutter and feel like it addresses these problems well?

> I had to set up Python projects for some machine learning classes in college and it was a complete mess.

Did you use conda (anaconda/miniconda) or pip?

Thanks tiangolo! Keep up the great work!!

I’ve used FastAPI at multiple companies now and really enjoy working with it. The tight integration with pydantic is wonderful. Also, it really is quite fast out of the box. Great for building ML prediction APIs.

Looks like I fell for a “conspiracy theory” here... I’m going to avoid any stock-market related comments on HN from here on out :p

The argument that Reddit/WSB users manipulated the market is a more difficult one to make vs. the argument that RH manipulated the market when they restricted their users to only sell GME. If they stopped both buying and selling then GME would not have dropped the way it did.

RH CEO’s denial said they made the move to protect the firm and their customers, but blocking buying and selling would’ve given them the protections without the risk of causing a change in the price. So it’s hard to believe that RH’s intent was anything but pushing the price of GME down to cover their customer’s short position.

Reading this article reminds me of an econ classes I took in college, developmental economics, where we studied what metrics are correlated with long-term economic growth. Of course we looked at things like education rates and technological advances, but surprisingly we looked at trust as well. Interestingly sociological measures of trust had a tighter correlation with long-term economic growth than anything else we looked at. If contracts are not trusted to be honored or enforced then business activity breaks down.

> We worked at a startup that leveraged autonomous blockchains to transfer money from naïve investors to slightly less naïve twenty-somethings.

What does it mean to “leverage autonomous blockchains”?

Whats SRR? I know SSR - server side rendering, but since that’s more-so a React/Vue thing I assume that you’re referring to something else.

Thanks for clarifying that. It makes sense. I figured that it was rarely the driver’s fault.

Since COVID I’ve used DoorDash more than ever. I got the dash pass with my cc and have been ordering a couple times a week. That is until I finally cancelled over some recurring bad experiences:

1. The food is wrong often. Whether it’s the dasher’s fault or the app’s or the restaurant’s who knows, but it happens too frequently. Granted DD gives an automatic refund in credits but our meal is ruined at that point and no one wants to wait another hour to roll the dice on a DD order.

2. All the good restaurants are leaving DoorDash. Maybe this is more so a trend in my town but at the beginning of COVID there were lots of great restaurants on it and now there’s just chains like Chipotle and McDonalds. Apparently it’s not just DD that loses money on these orders.

Now I will just call the restaurant directly and pick it up myself. Much better quality control, timing, cost and selection.

I agree that AI is very difficult and requires hard work by competent operators to be successful but I think there’s a deeper problem - most business data is irrelevant noise. It won’t matter how talented your DS team is if there is no signal in your data relevant to business operations for the ML model to identify.

Maybe this is just an issue with my phone, but I found the embedded demo video frustrating to view because it’s 1) low quality / hard to read and 2) in a loop that can’t be paused. I watched it 3 times trying to read through the code each time then gave up in frustration.

I’d guess jb775 saw a clip with a conservative lawmaker or pundit making this point. It’s been floating around the news lately. Take a look at the recent argument between Sen. Rand Paul and Dr. Fauci[0]. Essentially republicans are trying to push this idea that the number of infections and deaths from COVID-19 are inevitable and any government intervention can only impact the timing. In other words the area under the curve is constant.

They don’t want people thinking that if action was taken by the U.S. gov sooner (Feb instead of Apr) we would have dramatically fewer deaths and cases, which is probably a more scientifically accurate view but with all the data being so new this debate is ripe for political distortion.

[0] https://youtu.be/Yk2p2oyXxTc

Did you even read his book? Calling it “far-left” or “pessimistic” is pretty far off. If you have critiques then present them clearly with evidence.

It’s funny how on Twitter this currently has 3 retweets and 17 likes but on HN it has 110 points!

This is good to see but I’m curious how 2020 will turn out. I would guess that with with the pandemic driven shutdown median household income will drop pretty dramatically. Maybe more than this 6.8% gain.