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Essentially every high schooler had an active Facebook account and essentially every school paper was written on a word processor by, like, 2010. By 2018 even Instagram is starting to be played out. I would be very surprised to see a material increase in the share of US or western students using social media over the 2018-2022 period.

You say this as if 2010 Facebook was comparable to 2022 Instagram/TikTok.

Parent comment was talking about "widespread adoption of social media", not anything qualitative.

The timeline is more plausible for the rise of short-form video.

Feels like a hobbyhorse. The article discusses issues between the educator and the child, like:

> An even bigger problem, though, is muddle-headed thinking among educators. Some have fallen for the leftist canard that tests are harmful and grades are racist. Some have allowed reasonable worries about children’s mental health to warp into an excuse for low expectations. Some unhelpful habits acquired during the pandemic have stuck: children are still missing more lessons than before, and many teachers who relaxed their grading standards have failed to tighten up again.

I think we should look there and focus on what’s actually happening between the educator and the child.


Like so many conservative scare tactics, this is complete bullshit.

I hang out with a lot of teacher. Grade inflation is because if you dare give anything less to an A to a student, their parents complain to administration and administration always gives in and never stands up for the teacher. Same if students aren't turning work in - parents complain, administration says to pass them.

Educators are underwater, overworked, burnt out, and it's getting worse - and none of that is their fault. Every year they're asked to do more with less, which is why many of the best have retired or moved to other work.


That just sounds like another hobbyhorse.

My take is real. Everything else is people pushing agendas.

Most people were still accessing Facebook via desktop in 2010, and the term "engagement algorithm" had yet to be coined.

I don't know for kids specifically but average user time: 2012 1:30 2016 2:08 2019-now ~2:30

If child patterns match the average, an average 8th grader from now has accumulated something like 30% more than one in 2018.


I think it can shift rapidly when an addiction or compulsory behaviour becomes a problem.

For example, made-up numbers, but: 1-2 hours of doom-scrolling daily is okay, as it still leaves time for 1-2 hours of schoolwork at home. 3-4 hours of such doom-scrolling, doom-scrolling between classes or during classes will have a measurable negative effect on your academic knowledge and abilities. (I don't have much information on how US schoolkids live today.)


I'd say the main difference is that you couldn't take a device with good media capabilities, good and cheap-ish networking and lasting battery everywhere. Laptops, netbooks, tablets were a tad too bulky, lasted only a few hours unplugged and mainly wifi, and mobile internet was not all that great.

If only we knew what could possible have happened right in that time period to really throw a wrench in the works of the education system...

Right? Imagine how badly it could go if a disease known to cause brain damage became widespread and was circulating in the population.

If you click on the article that has actual data, the trend started in 2013 and has been mostly the same since then.

And surely one could never predict the impact of sending kids home for two years and expecting them to manage their own education on their own honor. Surely school aged children are better at paying attention to Zoom meetings than I am as an adult. It's in the computer! Kids are good at computer!

People need to stop believing insane, delusional things like the existence of a human being with a certain name, address, phone number, birthday, SSN being secret or private information.

Downstream of that, people need to stop accepting knowledge of the basic public metadata fields or possession of images containing them as evidence of identity verification. Do actual public key cryptography on the internet or check biometrics and the document’s physical security measures in person.


I do not buy that LLMs and the capability to run them are fundamentally different from other software or general purpose computing infrastructure in this regard. Moves to ban open source software or force OEMs to put little cops in everyone's computers are bad.

They aren't open source? And no one said anything about cops.

The proposal I’m hearing is to make people training models accountable for anything users do with them.

Obviously you’re going to keep the model behind an API and be very selective about the people allowed to call and the queries it’s willing to answer, in that case. As Anthropic has done with Fable. But that is voluntary restraint - mostly in today’s regime we get frontier capabilities in open weight models on a ~year delay.


It’s to keep “the people running it accountable.” The context is agents ran by OpenAI/Anthropic doing damage outside.

There is no user-involved damage. No one is recklessly running agents by the thousands without air-gapped containers, except “the people” than run these labs.


One through eight read as the list of sacrifices you make in having children. But the experiences of loving and being loved back seem at least incomplete without that.


Even startups that beat the incredibly long odds to become successful mostly aren’t successful enough to make up for a long stretch of not earning BigCo RSUs.


I work at a household name tech company and pretty much all our "data" dashboards are running SQL queries against a Hive/Presto environment that's at least 24 hours behind. Real-time dashboards are limited to the service metrics time series database (so combinations of categorical variables, no individual records) or rare expensive Pinot tables.


I have seen this on the business side too. A lot of we need live data requests don’t really need live data. If the decision is made once a day, hourly data is more than enough. Yet we still build dashboards that refresh every few minutes just because people asked for it.


In this case, we do actually need live data! We use wide events for monitoring business events and it lets us understand our platform with utmost flexibility, which is important for us as a fintech company.

Traditional observability is ill-suited for observability around business events. What if you forget to instrument a counter or gauge for something? In my experience it's far easier to log wide events with as much context as possible instead of agonizing over anticipating the dimensionality of metrics upfront (you're going to miss something).


Perhaps changing is a better word.

Yes this was also my experience working at a large tech co. I work in fintech now and data volumes are low enough to maintain 2-3 minute up to a few hour data freshness.


>Despite all the noise, remote work has not really decreased much in recent years. "Less than 1/3 of companies requiring fully in-person work in 2026."[3]

Remote work is generally being displaced by hybrid. That still requires employees to live in expensive metros and employers to maintain offices with space for everyone. The offices can be a little more austere and the commutes a little worse given that they're only for 2-3 days a week, but everybody's still got to pay for basically the same stuff. Downtown retail, though, is screwed with only 2-3 days of foot traffic to pay the bills.


Most of the 60 minute travel time radius around a San Francisco or Silicon Valley tech HQ is water and nature preserve.


It doesn’t make sense to assume SF logistics even on this board because it’s such an outlier. Just my opinion.


The obvious 21st century United States instance of "don't collect data that the government might later use for persecution" is E-Verify.


The part that has stood the test of time and genuinely seems to carve reality at the seams is the query part. The data definition and data manipulation parts are just ok.


Even so, "FROM t SELECT t.foo, …" has an ergonomic advantage over "SELECT t.foo, … FROM t" in that editors can autocomplete column names without needing to backtrack while editing.

IIRC, this is why C# query syntax uses the former.


The problem with the query part is that query fragments aren't composable.


CTEs are how you compose SQL.

I don't quite like how the same CTE lives in 60 different places in my codebase, but at least the WITH clause changed things for me.

Also really liked Snowflake's result_scan for composing chains, mostly because I don't rerun expensive parts again and again. You can use ->> as a shortcut, but I don't think it uses results caching internally to skip waiting for them to all re-run & actually optimizes the whole thing.


you create one view and have the ctes query that, to deduplicate the implementation


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