It’s human nature to pattern-match experiences. As the number of experiences grows, more fit into something seen before. So, yes, we’re just getting old.
Every student is forced to read the same materials and books. Tests are designed to test how close they remember the same correct answers. It’s always been rare that a novel interpretation or idea has come out of a classroom. The modern, structured education has never been designed to generate creative people.
Taking the restaurant ordering app, it’s certainly better than a server. Each individual picks what they want and pays for what they got on their own bill. It removes any chance of communication error between the customer and the kitchen. Appetizers to share easily split across who wanted them. No bill splitting discussions. OP just had to use a bad implementation.
Physics is applying math to Model phenomena. Finance is already numbers so it’s a good fit. If you are insinuating the money corrupts it, they’re paid for the skills they developed. Are medical doctors less noble because they make massive salaries?
Has that not been what a senior SWE is? You’re making it sound like engineers need to be asked to implement features rather than contribute to design. At my company, if you are not coming up with new features or applications, your days are numbered.
Allowing non-technical PMs to ship code is fine if they’re the one getting called up in the evenings and weekends when it breaks. Maybe it’s a good exercise to show how much has effort must be applied to each commit.
Felt the same way. Set aside the hyperbole, and it’s coming from the very real fear that data labeling does not have long-term job security. If the company continues to run after you’ve been moved, it’s pretty obvious you were redundant. Tough realization for people that see themselves as having been successful career-wise.
“You” being the operative word. The writing is on the wall when an AI-centric cloud company with falling profits can’t compensate its workers in an age where other companies are scrambling to jam AI into everything. It reads as a last ditch effort to resuscitate the business.
GE moved off Clearcase in 2019 because even IBM didn’t want to use or support it anymore. Wasn’t set up as bad as you had but wouldn’t describe it as pleasant. Lot of alias cheatsheets. Now we’re on perforce transitioning to git.
I certainly didn’t understand it. We were using it up to 2019. A coworker set up a spec that would automatically mirror to the main codebase, unknown to me that was possible. I made a branch there, did some stuff, and then reverted. Little did I know I was essentially working on production. Broke a bunch of stuff and had to remember what I changed because there was no history. Point is it was too powerful for people that did and didn’t know how to use it.
Between this and blipped-CAIPI in 2011, there hasn’t been much change from an acquisition perspective in the industry. Mostly everyone shifted to AI reconstruction, workflow improvements, and reducing helium use. Those are the low-hanging fruit. I’d be happy to be proven wrong but I don’t see any major breakthroughs coming from advanced math in the near future. ISMRM was this week though so maybe something came out of it.
It’s a poor example. Recently, I did have to email myself photos taken with my phone to access them on my laptop. Would be nice if they were automatically synced. It’s work phone and laptop so I could have gone through OneDrive or Box but just as inconvenient as email.
The article gave one anecdotal example of a person who misdiagnosed themself and then tried to make a broader point by disregarding the definition of addiction. Addiction is not just how many times a compulsive behavior is done. It’s the inability to regulate oneself for the behavior often at the expense of relationships or other responsibilities. If you’re looking at porn when you should be working, that could be addiction, for example. Apply that to relationships too. If you’re looking at porn and masturbating instead of being with your spouse, that’s addiction too.
When I generate code with AI, I will read through each change as it makes them (babysitting). If I don’t understand it, then I ask for explanation right away. At least by the end I have a grasp on what each change does and the reasoning. Then, I can make a PR and highlight the same info for my reviewer and for longevity. Our codebase style is not to litter comments everywhere. We go back to the code review for details and discussion. Obviously, this only works if the changes are small.
May not have been clear. My job is not AI development. I have features to deliver. The ask from employer is to add the AI knowledge sharing on top of it. They don’t pay for that. When layoffs come, it wouldn’t save me from missed deliverables.