I'd also consider myself to be a direct communicator and always think twice when reviewing someone's PR / doing code review. My team is completely remote and things can get awkward at times. Often, it may come off as unnecessarily harsh or may make it seem like I'm telling them what to do. Like it or not, the tone of the review can greatly influence the morale of the team.
I found this[1] to be a good resource. Another thing that has helped me is adding a prefix to my review. Classifying it as: suggestion, nitpick, props, etc. More about this here[2].
The system is designed to favour wealth over income. Income tax vs capital gains tax is a good way to demonstrate that.
Another example of this is how homeowners are treated vs renters. Specifically, in terms of tax breaks for mortgage interest payments, expenses incurred during major home improvements, etc. Also you can withdraw a decent chunk of money from your IRA early without the hefty penalty if the withdrawal goes toward buying a home. On the other hand, renters are not eligible for any such benefits.
I'm in favour of keeping phones away from students during school hours - Yondr pouches or storing them in a locker makes sense. It's very unlikely that there will be an emergency that warrants the immediate attention of a school student as it is. Plus, in my high school parents could call in to the school landline to speak to their kids if need be.
Teachers have a difficult job as it is, not to mention that they are already mistreated - they have almost no authority over students since they never have backing from parents or school administrators.
I recently came across a post on Reddit[1] where a student pepper sprayed her teacher because he confiscated her phone during an exam. One of the commenters claimed that the same teacher was previously punched in the face by a different student for taking their phone away after catching them cheating on a test. It is disconcerting to say the least.
HN is really getting flooded with AI/GPT posts lately.
Anyway, this[1] is a really good introduction to Prompt Engineering and how one can tailor prompts for their use-case.
Interesting podcast episode that touches on this stuff - "In an age that favors the formulaic and generic to the ambiguous, complex, and unexpected, it's no wonder that computers can sound eerily lifelike. Leslie tells EconTalk host Russ Roberts that we should worry less about the lifelike nature of AI and worry more that human beings are being more robotic and predictable."[2]
I know you said wanted a no-code solution but in case you don't get a satisfactory answer try this out.
Earlier today there was a Show HN post[1] which showed how to visualize a Pandas dataframe (can come from CSV, JSON whatever). I tried it for basic tasks and it is pretty good. It's minimal code (<5 lines) - just reading the json and calling pygwalker in a Google Colab environment[2] or something. Something like this:
import pandas as pd
import pygwalker as pyg
df = pd.read_json('{filename}.json')
gwalker = pyg.walk(df)
> While working-class immigrant Asian parents are forcing their kids to take test prep and piano lessons thinking that it’ll help their kids get into a better college, the wealthy Asian elite have already cracked the code. Elites like Ahmed know that signaling that one has the “correct” beliefs is what is needed to gain entry to America’s most prestigious colleges.
I'm interested in this as well but don't know enough about how other entities do it. How do the World Bank, IMF, other governments, etc go about this?
As outlined in the article, common sense solutions do exist so the problem isn't technical per se. Is it just that not enough people are using these datasets for it to be an important enough problem to solve? Or is it more of a bureaucratic/political issue where its difficult to come to a consensus among these departments?
I just realized that Patrick McKenzie is the author of some of my favorite blog posts[1][2]. After his departure from Stripe, I hope he gets back to writing more frequently.
I also knew what you meant but it was more for those people who skip the article and comment based solely on the title.
Sidenote - if you can find the time, you should write more often. I just went through your articles and there is a lot of useful advice to be found. The projects are pretty interesting too. Cheers!
The author says silence but means isolation - ".....isolation without any signals or external validation until it’s complete"
I'd say this is just the first stage of creating something, an MVP of sorts. After that you do need to get some feedback, iterate and improve it step-by-step to get the finished product.
Blind[1] is a decent community to get a glimpse into what employees truly feel about employers, get referrals and overall tech career advice. It can get rather toxic and troll-ey at times, but you can filter that out to focus on the useful stuff.
Since OpenAI is a "capped-profit" company [1], the employees and investors only get up to 100X their initial investment. Anything beyond that would still go to the OpenAI non-profit. It seems like a reasonable compromise, however, the massive Microsoft investment does concern me.
"I know false-alarms like mine will be rare, and the potential life-saving benefit far outweighs the inconvenience of my particular situation. But there has to be a better way to distinguish genuine crashes from phone-smashing mishaps."
Just want to stress that training an ML model is going to be really difficult for this scenario, and false positives are to be expected. It isn't like this was unexpected either given that "the phone flew off its handlebar mount".
1B+ MAU along with the fact that people spend more time on TikTok than all streaming services combined. Its quite stunning how quickly TikTok is growing, and given the new ways in which they plan to monetize their user base, this ain't gonna stop any time soon.
Sidenote - Only a few years ago, I thought it'd be damn near impossible to compete with FB + IG in the social media space OR with Google + FB in the digital ads industry. On both counts though, I've had to rethink my position given the rise of TikTok, Amazon[1] and Apple[2].
3) I haven't used GCP except for Looker + BigQuery, and for the most part I have been a satisfied customer. Sharing data and dashboards across teams for non-(engineers + data scientists) is critical and Looker does a pretty good job for our use case.
4) I've also received discounts which helped us save on query and storage costs (20% off above a certain threshold).
As a hobbyist, I have used Google Colab which has been pretty good as well. (Don't know if it officially comes under GCP).
This is known but is worth repeating - GCP is under-pricing its products as a way to gain market share, and once they have a larger piece of the pie, they are likely to increase prices.
Makes me wonder about copyright when it comes to voice synthesis via AI. Like legally speaking, did they "need" JEJ to sign off on this as opposed to just using his voice as training data?
In the near future, I imagine it'd be easy enough to take a snippet of audio and transfer a celebrity's voice to it, similar to what we can already do to images using StyleGAN or something similar.
I found this[1] to be a good resource. Another thing that has helped me is adding a prefix to my review. Classifying it as: suggestion, nitpick, props, etc. More about this here[2].
[1] - https://stackoverflow.blog/2019/09/30/how-to-make-good-code-...
[2] - https://emmer.dev/blog/code-review-comment-prefixes/