Hey everyone! Ali and Chris here. We’ve been living away from our families and supporting them remotely for over 16 years.

We are really excited to be launching Jhappi.Day (http://Jhappi.Day) - a subscription service for NRIs, overseas Pakistanis, and Bangladeshis to take care of their family back home.

We started Jhappi.Day because:

- It’s hard to support your parents while you’re far away: If they get sick, it’s hard to arrange the right appointments - and even harder to know the full outcome. If we were there, we’d help with running errands, but we can’t do that from abroad.

- It's hard to make sure that your family is not getting ripped off: Are they getting the best services for their money? Are they using the best discounts and deals available online?

- It's hard to transparently track if all relatives are contributing fairly to family finances: It becomes hard to have a single source of truth and nudge relatives or siblings when financial responsibility is not being equally shared.

The solution is a long distance family management service that gives you:

- Complete health tracking: A monthly visit from a Medical Doctor with detailed reports shared directly with you.

- 24/7 reliable errand support & tracking with best deals: Round-the-clock on-call support to help your family with any errands, including weekly grocery shopping and much more.

- Coordination of financial contributions: A simple dashboard to track all contributions and get a clear breakdown of all family expenses.

We are offering:

- Everybody who signs up today gets 1 month completely free.

- The first 250 people to book a call will be entered into a prize draw for a free return flight to a South Asian city of their choice.

We also launched today on Product Hunt: https://www.producthunt.com/posts/jhappi-day-long-distance-s...

Would love to hear any thoughts and feedback on the product.

I suspect there must be some confounder here - like the positioning used for the CXRs correlating with race, based on the methodology used in a particular region / hospital.

Seems the most likely explanation for it still working even when pixellated as 8x8?

That was exactly my thinking. I wouldn't publish anything until the pixellated versions were better understood.

Well, isn’t the point of publishing to get help figuring it out from other researchers in the field? I agree it’s very likely that there’s some kind of explainable trick the AI is using, but there’s no guarantee it’s an easy trick that the authors could have figured out.

I'd warm up to that concept if the article was: "We don't know what in the hell is going on here. Here's our source code and data set of x-rays and race. What do you think?"

It could be that in the realm of machine learning, most of what is going on is people turning random knobs on a big machine and getting mysterious results. It's the birth of science without understanding.

That's precisely what the researchers are saying. In the underlying paper, they conclude that "this capability is extremely difficult to isolate or mitigate", call for "further investigation and research into the human-hidden but model-decipherable information", and suggest medical imaging people should "consider the use of deep learning models with extreme caution" until future research produces a better understanding of what's happening.

They always call for 'further investigation'.

Looking at this: https://arxiv.org/pdf/2107.10356.pdf

My general impression (no more than that) is a whole bunch of people crowding into a paper. The paper is mostly applying trivial image processing functions and seeing how some software they don't understand is responding. The main aim is pearl-clutching about 'bias' rather than any kind of understanding. God knows what they're going to do when any medical exam includes some kind of deep dive into the patient's genetics.

No surprises. It's the nature of the era.

Looks like a bit of a hit piece to me...

I loved maps.me, especially when travelling to new countries - best of luck with this

Yeah, so someone else suggested this too - I'm going to look into the API and see what information I can get from it

Yeah, it's not that easy to at the moment. I was planning to build a front-end site, where you could just type your search terms and parameters and it would show you the videos, but to honest I ran out of steam after I couldn't get the code to run on Lambda.

Ok, fair enough

amen! I wish you could crank up exploration cf. exploitation in your settings or something

It would be cool in general if recommendation algorithms or search algorithms were more customizable. I would imagine you could put some code into your settings that controls which recommendations you see. The platform, like YouTube in this case, could compute features that enable different kind of recommendation algorithms. There could be communities of people who tinker with this and share their recommendation algorithms.

Steam added this feature recently (https://store.steampowered.com/recommender/ lets you add weights for "niche/popular" and "older/newer") and I've never had so much fun browsing a store. I hope other platforms take note

really interesting suggestion, I like it

what do you think would be good markers of a bad video? other than the obvious (clickbait terms, repetitive/generic titles), I'm not sure what could work. any suggestions?

Personally GRAPE content (Guns / Religion / Abortion / Politics / environment) especially from opinion news sources.

I notice that when I consume these content I never end up feeling better than when I started regardless of whether I agree / disagree with them. Also a huge time sink.

Also, entertainment content about celebrities like the kardashians.

I'm thinking maybe an extension where when you sign up, it asks: "what do you NOT want to see", and then for all topics you pick it will block videos on those.

Kind of like when you sign up for Twitter or Medium, it asks you for topics of interest - here it would do the inverse

I like the blog!

Yeah, that's pretty much my exact gripe - that the algorithm just keeps wanting to show you more of the same. It's like a friend who gets obsessed about one thing after you said you liked it once :')

I'm not sure how best to solve this though

I like when YouTubers talk about other channels they like, and I often go check those out – especially if they are on some completely different topic. Because if someone is making content I like, they might also have good taste when it comes to what they watch. But I think in general the art of "taste-making" remains just that: an art.

Maybe a "this is cool; but enough for now" button? It would remember the category that you like but turn down its recommendation frequency for a duration (session?).

ah okay, thanks. Yeah I think I may have over-complicated things by trying to use lambda. Will look into doing this on DO

Since your code is already hosted on GitHub you could also try using GitHub Actions with a scheduled trigger. https://docs.github.com/en/free-pro-team@latest/actions/refe...

If you already made an AWS account, the t2.micro EC2 will work as well, free tier!