I don’t have some grand theory on SO’s downfall. All I will say is that sometimes us programmers try to optimize every single thing in life and that’s simply not how humans work.
SO tried to optimize the Q/A by eagerly rejecting repeat questions, without considering what the consequences of that were. If you’re in a classroom / lecture hall, your teacher / professor isn’t going to chide you for asking an “obvious” or “repeat” question (bad ones might). Imagine if every time you wanted to talk to a TA or professor you first needed to lookup previously asked questions in a database and then, iff your question hasn’t been asked before, you may ask the professor or TA after hours. Programmers might call this system “efficient” but most people would be pretty unhappy with it.
Been using it for half a year now in prod to collect sensor data from IoT devices.
My only complaints are:
1) Memory usage is a bit high. We went with the AWS instance they recommended in the docs and even that went over our provisioned memory. It's not much but I think it could be improved
2) You need to buy their enterprise plan if what you're storing is remotely sensitive like health data, PII, etc. Any row level security or credential features are locked behind that license. Our use case isn't that sensitive so we can get away with putting it in a VPN and password protecting it, but if you need DB-level security the FOSS license is severely behind Postgres in terms of features.
Other than that, it's never gone down, it's very, very fast and comes with it's own webui for querying your data. We migrated from AWS Timestream and couldn't be happier with the switch.
It's a fun toy program but calling this a flight simulator is doing a disservice to the communities and efforts putting in an immense amount of work to make actual flight simulators.
In the time before LLMs, humans made satellites, Concorde, life-saving medical surgery, James-Webb Space Telescope, communication at the speed of light, the list goes on.
What changes have LLMs (Not AI, not machine learning in general, I'm not going to waste time discussing the definition), LLMs made in the past 4 years that indicate anything close to the above? Solving a whiteboard math problem?
It's clear the OC was using hyperbole but we're honestly not too far off. Just a few examples:
- Sam Altman & Worldcoin collecting everyone's eyeball scan
- Discord attempting to roll out worldwide age & id verification
- LinkedIn collecting data on your web browser extensions
- WhatsApp collecting browser data via a local server running on device
Supposedly humans have become “100x”™ more productive with these AI tools, but nowhere to be seen are the benefits for the wielders of said tools. Is your salary 100x higher? Are you able to spend more time with your family/friends instead of at the office? Why are we still putting up with these outdated work practices if LLMs have made everybody so much more productive?
“Thing x happened in the past, therefore it will continue to happen in the future” is perhaps one of the most, if not the most pervasive human-created fallacies anywhere.
The rust maintainers need to learn from the mistakes of the c++ design committee and understand that not adding a feature at all is in itself a desirable feature.
For example, your section on effects:
> Functions which guarantee they do not unwind (absence of the panic effect)
> Functions which guarantee they terminate (absence of the div effect)
> Functions which are guaranteed to be deterministic (absence of the ndet effect)
> Functions which are guaranteed to not call host APIs (absence of the io effect)
The vast majority of rust programs don’t need such validation. And for those that do, the Ferrocene project is maintaining a downstream fork of the compiler where this kind of feature would be more appropriate.
I think rust is in a perfect spot right now. Covers 99.99% of use cases and adding more syntax/functionality for 0.001% of users is only going to make the language worse. The compiler itself provides a powerful api via build.rs and proc macros which let downstream maintainers build their desired customization.
> From what I understand these systems are legal because there is no expectation of privacy in public.
This is a common line of phrasing parroted by Flock and their supporters to no end but it's a myth. The SC, as much of a joke as they are now, established that a person has a reasonable expectation to privacy in their long term movements in Carpenter v. United States (2018). To date there is NO precedent carved out in the constitution or ANY Supreme Court case stating that people have zero expectation to privacy in public.
Why not Go? I don’t understand starting new backend projects in a JVM language when go exits and its both faster and simpler. People love to proclaim Java’s ability to handle “big data” but I have programs parsing TB of data daily in Go without a sweat. And it was much faster to write and teach new engineers on than Java
Tailscale has made all of their client source code available for anyone to view so if you want to confirm that you’re not sending unencrypted data or keys through their servers you’re more than free to do so.
I think there is some merit to setting up wireguard (e.g. you want more devices than what Tailscale offers for free, or their servers become unreliable for some reason)
But people who push the “scarey boogeyman will look at your data” with Tailscale are either technically illiterate or overly-paranoid.
If Apple wanted to score easy points they would leave this be and add a widget/app icon animation api in the next major release of iOS. This would be way more useful than whatever crap Siri and Apple intelligence are.
SO tried to optimize the Q/A by eagerly rejecting repeat questions, without considering what the consequences of that were. If you’re in a classroom / lecture hall, your teacher / professor isn’t going to chide you for asking an “obvious” or “repeat” question (bad ones might). Imagine if every time you wanted to talk to a TA or professor you first needed to lookup previously asked questions in a database and then, iff your question hasn’t been asked before, you may ask the professor or TA after hours. Programmers might call this system “efficient” but most people would be pretty unhappy with it.