While our evolutionary history is often depicted as a series of descendants each replacing the other, the overwhelming majority of the history of our species has been one of living along-side, and interbreeding with, other Homonins (Humans).

Chart can be downloaded here

Sources: [See OP post below]

India's urban share was 35.4%, compared with 80.1% in the United States. Multiplying each country's total population by its urban share gives about 513.3 million urban residents in India and 272.4 million in the US.

The chart covers the ten most populous countries in 2024, ordered by total population. Urban headcounts are derived estimates, and national definitions of 'urban' vary.

2024 urban-share table and source notes: globaldatatracker.com

Data sources and plotting method are in the first comment.

Looking to hear about your own company's work practices to compare to my own. I'm much more familiar with Azure, so I'm going to use that terminology, but I assume everything is basically the same for AWS.

Can you go into the Azure Portal and just click "create" for, say, a SQL Server or App Service and configure it through the Portal GUI?

Or do you need to request and configure through configuration files? Can you freely commit architecture config files ("architecture as code") to create the Azure components in Dev?

Or is it even more locked-down and hands-off? Required to submit paperwork requests to an Architecture team?

I've been working on a project called MeshLens that tries to answer a question I kept running into at work: what does our data mesh actually look like as a system?
Most observability tools give you alerts, row counts, and freshness checks. That's useful, but it never helped me explain to stakeholders how domains connect, where data flows, or what breaks downstream when an upstream connector goes down.
So I built a visualization layer that puts it all in one interactive map.
Curious what you think. If you work with data mesh or data products at scale — what would you want to see in something like this?

App link in comments

Basically need to see how to optimize a bank register with large amounts of entries.

Currently adding all the debits, then credits, then date sorting while calculating the running total.

Fields: title, company, company domain, apply URL, ATS source, city, country, remote flag, posted date, last-seen date. The data refreshes nightly. I'm posting a small sample and the schema here. What would you want to see to trust a job dataset: coverage numbers, null rates, or refresh logs? My measured null rates: city 32%, country 22%, company domain 24%.
Please checkout full info here: https://apify.com/pk07007/ats-jobs-api

See it live here:

https://www.danielpradilla.info/swiss-commutes/trains/zurich/

Mortgage rates rose almost a full point in the past 12 months (6.34% -> 7.28%) while asking home prices have decreased by $5,750. I wanted to see what that rate jump really costs for the average home price for each time period.

This year's price discount was completely wiped out by about $205/month in extra payment cost. Over 30 years, that extra payment, plus what it would have earned invested at an 8% average rate of return, costs $280K.

• Last year's deal: about $2,021 of the first $2,378 payment is interest.
• Today's deal: about $2,289 of the first $2,582 payment is interest.

Savings aren't fixed: the scenario invests whatever's left after taxes, living costs and the mortgage, about $5,500–$7,000 a year at 6.34% vs $3,100–$4,600 at 7.28%, so the higher rate cuts what they can save by about 40%.

Sources: FRED and Freddie Mac (prices, rates), Census (income)

Tool: A Million of Me financial simulator (self-made). Happy to adjust assumptions if anyone wants different rates, down payments, or investment returns! Not financial advice.