correlator

From my experience NIMBYs are typically local property owners who don't want their view, neighborhood, etc. to change. These folks could be better off financially than their YIMBY counterparts who maybe don't own all that same property.

If there's a group of people with money and a group with less debating the same issue, I would expect the politician to support the party most likely to make large campaign contributions.

I have no data to support this idea and should not be taken seriously in this context.

The majority of published scientific papers have been proven wrong by future discoveries. This is what learning and progress looks like.

More complete datasets, a better understanding of how that data was collected and how to interpret it, solid statistical foundations, etc. etc.

People who go out to change minds should be versed in all this and more. But I don't believe they are required to roll up your sleeves and play with some data! :)

You're not wrong.

"I don't have the data or tools at my disposal to do this properly" Should not prevent you from trying, sharing, and learning. However, it definitely should prevent you from trying to change other people's minds.

I enjoyed this and respect citizens who feel motivated enough to look at underlying data..

This type of discourse ("here is what I did and here is what I saw") leaves room to comment and make progress. People can discuss measurement methods, statistical analysis, and other objective things about a tightly scoped project like this.

This is very clear reading the comments in the substack. A comment exchange that reminded me of my days in grad school:

commenter: "What I think can be taken conclusively from this survey is that temperature is quite regionally variable, and there are a variety of different trends over time in these locations. Do you feel that there is some more significant conclusion that can be drawn from this?"

author: "I am hesitant to draw any conclusions. I am more in a state of examining the data itself and asking questions."

Anyone who has seen their infants instantly cry when they receive their moment of birth vaccinations knows that they feel pain. The infant's pain creates more pain in the parents....what a cycle!

I think OP was saying the ledger mechanics are the useful part here, not the volatile speculation.

IMHO this is the de-facto tutorial: https://www.railstutorial.org/

Thank you for writing this. I personally just walked into a very similar role and this rang really true. This article made me realize how much more effort I need to put into the data culture side of the role.

Stable, efficient and intuitive. Thank you to the stimulus team!

Misleading because the solution did not provide reactive front ends, or misleading because the solution did in fact require extensive javascript?

This one is a fun read

That is an interesting approach. Our of curiosity, how is an engineer made aware of the psql view? For example, the view likely relies on specific columns in specific models. What guard rails are available for preventing this kind of breaking change with the view approach?

Everything you outlined is a use case that is powered by machine learning algorithms. You can discuss all of them without using the phrase "AI." They all likely started with rules engines that solved a real business problem and iterated over time to use more sophisticated back ends.

The thing that I don't appreciate in this field is that companies seem more focused on discussing their "AI" than the actual problems they hope to solve. When I see this, my mind jumps to the assumption that these companies are either: 1) looking for easy valuation multiples. 2) looking for a way to impress VCs/investors. 3) they don't actually understand the problem they are solving. This is admittedly a big stereotype on my part, but this stereotype was built on pattern recognition over time.

Simpsons did it

Rails turbolinks is magic!

Incentives are really messed up here. Tacking the letters "AI" on the end of your company name will increase it's multiple. It will force your engineers to call their rules engine "AI" when on calls with customers. It's really unfortunate.

I think it's ripe for useful tools. No need for disruption.

Another "AI" hammer looking for a nail to solve bites the dust. I hope those 100 employees land on their feet.

No need to look at AZ for this. If you're building "AI" I wish you a speedy road to being acquired by a company that can put it to use. You've become a high priced recruiting firm.

If you're solving a real problem and use ML in service of solving that problem, then you've got a great moat....happy trusting customers.

It's not complicated

Nothing gets scalable applications shipped faster.

It sounds a lot like raising venture funding. Make sure there's a slide that says "$10 billion" because that's the new billion. Talk about your "AI" which was formerly "blockchain" or "big data" and make sure you fit the mold of whatever the funding is looking for. Leave creativity at the door please.

I hope not.

Rails is a business tool. It allows developers to move quickly to build and iterate rapidly on the business vision.

This means a lot of interesting engineering work and optimizations are out of your hands. Some people think that's a bad thing, I think it's a great thing. Depends on your goals.

Are they a tech company? Not really sure what the distinction is to get that title, but it's not the first thing that comes to mind when I think about wework ... P@ssw0rd

We still have a ways to go https://www.thedrive.com/news/18135/united-airlines-refuses-...

Simpsons did it

Then once people stop texting they can tax: - Telegram - Whatapp - Wechat - etc. etc. etc.

Good luck!

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Glad to see Sean make such a noteworthy discovery. I worked in the lab next door and remember him being the happiest and kindest person in the building. Kudos!