ignirtoq

The thing is it’s been like that forever. Good products made by small- to medium-sized businesses have always attracted buyouts where the new owner basically converts the good reputation of the original into money through cutting corners, laying off critical workers, and other strategies that slowly (or quickly) make the product worse. Eventually the formerly good product gets bad enough there’s space in the market for an entrepreneur to introduce a new good product, and the cycle repeats.

I think what’s different now is, since this has gone on unabated for 70+ years, economic inequality means the people with good ideas for products can’t afford to become entrepreneurs anymore. The market openings are there, but the people that made everything so bad now have all the money. So the cycle is broken not by good products staying good, but by bad products having no replacements.

The author hits on exactly what’s happening with the comparison to carcinisation: crustacean evolution converges to a crab like form because that’s the optimization for the environmental stresses.

As tiramichu said in their comment, digital platforms are converging to the same form because they’re optimizing for the same metric. But the reason they’re all optimizing that metric is because their monetization is advertising.

In the golden days of digital platforms, i.e. the 2010s, everything was venture capital funded. A quality product was the first goal, and monetization would come “eventually.” All of the platforms operated this way. Advertising was discussed as one potential monetization, but others were on the table, too, like the “freemium” model that seemed to work well for Google: provide a basic tier for free that was great in its own right, and then have premium features that power users had to pay for. No one had detailed data for what worked and what didn’t, and how well each model works for a given market, because everything was so new. There were a few one-off success stories, many wild failures from the dotcom crash, but no clear paths to reliable, successful revenue streams.

Lots of products now do operate with the freemium model, but more and more platforms had moved and are still moving to advertising ultimately because of the venture capital firms that initially funded them have strong control over them and have more long term interest in money than a good product. The data is now out there that the advertising model makes so, so much more money than a freemium model ever could in basically any market. So VCs want advertising, so everything is TikTok.

The open availability of cutting-edge models creates a multiplier effect, enabling startups, researchers, and developers to build upon sophisticated AI technology without massive capital expenditure. This has accelerated China’s AI capabilities at a pace that has shocked Western observers.

Didn’t a Google engineer put out a white paper about this around the time Facebook’s original LLM weights leaked? They compared the rate of development of corporate AI groups to the open source community and found there was no possible way the corporate model could keep up if there were even a small investment in the open development model. The open source community was solving in weeks open problems the big companies couldn’t solve in years. I guess China was paying attention.

It’s not disingenuous. There’s multiple definitions of “offline” being used here, and just because some people aren’t using yours doesn’t mean they’re ignorant or arguing in bad faith.

Your definition of “offline” is encompassing just the executable code. So under that definition, sure, it’s offline. But I wouldn’t call an application “offline” if it requires an internet connection for any core feature of the application. And I call saving my document a core feature of a word processor. Since I wouldn’t call it “offline” I’m not sure what I would call it, but something closer to “local” or “native” to distinguish it from a cloud based application with a browser or other frontend.

I’m not the person you’re replying to, but I think their point is that the bars don’t scale linearly. The red bar (2014 price) for the McChicken is supposed to represent $1 and the yellow bar (2024 price) ~$3, but the yellow bar is not 3 times the length of the red bar. This means the relative differences between the bar lengths doesn’t match the percent increase number printed above then. This is most egregious comparing relative differences between the McChicken and the Quarter Pounder with Cheese meal: why does a 122% increase look so much worse than the 199% increase?

I suspect the cause of problem is that the small bars were stretched a bit to fit printing the dollar value within then, but if it throws off the visual accuracy of the bars, what’s the point of using bars at all?

Been the only one in my family for years using Linux, but over the last few months struggles with Windows have basically resulted in all but one computer in the house being migrated to Linux.

Put it on my 10-year-old son’s desktop because Windows parental controls have been made overly complicated and require Internet connectivity and multiple Microsoft accounts to manage. Switched to Linux Mint, installed the apt sources for the parental control programs, made myself an account with permissions and one for him without permissions to change the parental controls, and done. With Steam he can play all of the games in his library.

Only my wife is still using Windows, but with ads embedded in the OS ramping up, and features she liked getting replaced with worse ones, she’s getting increasingly frustrated with Microsoft.

The judge also noted that the cited study itself mentions that GitHub Copilot “rarely emits memorised code in benign situations.”

“Rarely” is not zero. This looks like it’s opening a loophole to copying open source code with strong copyleft licenses like the GPL:

1. Find OSS code you want to copy
2. Set up conditions for Copilot to reproduce code
3. Copy code into your commercial product
4. When sued, just claim Copilot generated the code

Depending on how good your lawyers are, 2 is optional. And bingo! All the OSS code you want without those pesky restrictive licenses.

In fact, I wonder if there’s a way to automate step 2. Some way to analyze an OSS GitHub repo to generate inputs for Copilot that will then regurgitate that same repo.

That strongly depends on the job. If the company has to follow regulations to meet some security posture, wiping the OS (and all the security tools and configuration set up by IT) to put your own favored OS without matching the security requirements could wind up with you getting fired.

I think it was pine, actually, but it was over 10 years ago so I can’t say for sure.

Not only did my math master’s thesis adviser use Linux, he read his email from a command line program and wrote his papers in plain TeX, considering LaTeX a new fangled tool he didn’t need.

Don’t worry, H5N1 is here to save the gaming industry!

On Sundays I do lunch prep for the days in office. A few slices of deli meat and block cheese for a nice flavor. Then a pile of raw veggies and a small container of dipping sauce. I prefer sliced bell pepper and green onion with ranch dressing, but you can do whatever veggies you prefer (for example spinach, sugar snap peas, carrots). I always feel great after that lunch; grains like bread or chips always made me feel lethargic.

I take it into the office in a plastic bento box to keep everything from jostling around, and the sauce goes in a smaller reusable container separately.

The article touches on that. VPN traffic is itself a small category, so even if we assume all VPN traffic is torrenting, that doesn’t push it very far up the charts.