My wife has gone through a large number of iPhones in the past 14 years, where as I've had a total of 2 android phones. Way easier to repair, and add software well past the end of life date.
Why has she gone through so many iPhones? I’m typing this on my iPhone 12 from 2020. Before that I had an iPhone 6s from 2015. I’m considering upgrading this year, but I could hold off for another few years if I wanted to. My phone still runs like it did when it was new. I get through most days with 60%+ battery remaining.
The biggest problem with my phone is modern software bloat. I only have the 64gb model. Modern software - especially iOS itself - has gotten ginormous. Every time a patch comes out I’ve gotta delete a bunch of stuff in order to update. And running unpatched software seems pretty dangerous right about now.
I had a Galaxy S3 from 2012 to 2024, then got a hand me down Galaxy S9 for free.
I don't like that I can't remove the battery, but it's got a SD card so I don't have to worry about storage ever and a headphone jack, so I don't have to worry about my headphones running out of batteries.
Banks are known for running mainframes which handle dates differently and will not be rolling over. The ones that use unix are likely to 64 bit systems that won't roll over.
They were competing with the biggest advertiser in the world who put an ad about their own browser on the front page of the biggest search engine in the world.
Not sure it was entirely their own doing.
That turned off a fraction of a fraction of users. And I believe i was largely misunderstood. There are also Firefox forks of somehow that was a bridge too far. I don’t understand how the answer would be to jump to chrome as if they have a better ToS.
It's not "us" that matters, assuming that means very on-the-pulse power user types. We're a tiny fraction of users. Over 99% of users have probably never even spared a thought for the ToS.
Attacking one of Russia's few allies and weapon suppliers is counterproductive to such a goal, even if higher oil prices also help the Russian state finances.
This ill-conceived, Kegsbreath-run operation depleted weapons stocks, gave enormous levels of intel on its systems (which both Russia and China are loving), burned through hundreds of billions in spend, and made Ameirca look like an impotent pathetic joke.
Yes, the Iran operation 100% served Russia and China. It could not have gone better for them.
And of course it helped Russia make hundreds of billions more on oil. Win win win.
And they should not even be needed. In many places the issue is solved at start. Copy or copies of each commercially produced book is send to national library. Which with tax payer money keeps an archive. Meaning that at least one copy exist for research purposes if needed.
Unfortunately, that's not the case in the United States. The LOC only selects around half of published books to be permanently held. The rest are disposed of (usually returning them to the publisher, donating them to a library, or destroying them).
How about before it was partitioned into colonies of various European powers? Population of China 60 years ago was half what it is now (700 Million).
Anyway, the answer is both. They were being exploited 60+ years ago, and they're still being exploited now, regardless of if they can take the train away from the factory that they work at to visit their relatives over the holidays.
China’s population was absolutely fucked over by the CCP to a level that is hard to comprehend. That had nothing directly to do with any foreign powers, but because Chinese workers became valuable to foreign markets their lives massively improved.
The government is still horrible, that’s unlikely to change but foreign markets aren’t the issue.
Solar panels were made in China. The reason that solar panels are so cheap there is that the state has bankrolled these companies to produce them at a massive scale.
Good for them. They really can’t win: if they don’t modernize they get blamed for high CO2 emissions and used as an excuse for the US to shirk its responsibilities to the Paris Agreements. If they do, and help the rest of the world at the same time, they get accused of dumping.
If only everyone else had the guts to follow their lead.
I just want to point out that this isn't something that is uncommon in capitalist societies (see CHIPS act) and the price delta is somewhere between 150%-200% more expensive for a western manufactured product which gets heavily diluted over the 25-year curve.
I think you misunderstood the point I was making. Solar panels are incredibly cheap and provide a large swathe of power, the problem being that it depresses daytime prices meaning there is significantly less capacity at nighttime causing an increase in pricing, this delta in the form of time delayed arbitrage is the juice to be squeezed for home battery technology, The free energy market is what allowed this to happen and that is a capitalist function
The broader point here is that solar is here, it's very very cheap and the raw materials and manufactring processes are actually incredibly simple.
To a first approximation, basically no one in the industry does. Users regularly report performance regressions in basically every major piece of software, most of which would have been caught by performance testing.
It can sometimes be difficult to predict what will cause performance regressions when developing an application or web server with test data. So you do your best with what you know at the time of release, and then deal with performance issues when you know what is causing regressions (e.g. saved searches) and can then make measurements and profiling to see what exactly is causing the issue.
Likewise, improving performance pushes the limit at which performance regressions happen allowing more data (documents, triangles/pixels, etc.) to be processed. This allows things like more complex game graphics. That in turn makes it harder to improve performance for the next round (more advanced triangle/face culling and pre-processing).
There can also be trade-offs with things like data layout, memory usage (caching and memoization), or implementation. For example, when processing XML/HTML data you could use DOM (more memory and upfront parsing, but easier to perform complex queries across the data), SAX (less memory, but more complex to process due to tracking state), or reader API (similar to SAX but a different processing model).
There can be challenges with various features, such as type checking with higher-order generic types. Others add various levels of overhead, such as parsing a program, constructing an AST (Abstract Syntax Tree), generating an IR (Intermediate Representation), the optimization passes and final code generation.
JavaScript evaluation for example is complex. Before Chrome the approach was to use a slow interpreter. IIRC, Chrome was the first browser to introduce JIT (Just-in-Time) compilation, leading to faster JavaScript and eventually more complex applications running in that language. Modern browser JavaScript pipelines are complex in order to achieve and maintain performance:
1. start interpreting the code on the AST so it is run immediately (or only rely on (2));
2. generate a machine code equivalent of that interpreted code (for faster baseline performance);
3. run more aggressive optimizations on known types based on profiling/analysis for even faster performance, including special handling of things like asm.js.
Startups have limited resources, we prioritize the best we can. As a staff engineer it's my responsibility to bring this to my company, but it's not an overnight process.
why wouldn't you use those limited resources to test things before they go to production, instead of creating more crappy things that go to production?
What do you test? How much time/effort do you spend testing each of those things? How do you know those will be performance issues?
There's only so much you can do -- making reasonable assumptions, choosing suitable data structures, database indices, testing various workloads, etc. -- in a limited test environment.
You may spend a week optimizing a feature that only 10 people use or that never gets to the point where it becomes an issue. Or you may have something that can't easily be tested at scale, such as various counts or other dynamic data that are determined by complex queries that you may (likely) find you need to cache but don't necessarily know which values will become issues until you start using the system.
We have a test team that runs various test suites(automated) and manual testers that test functionality. They spend their entire working day, every day testing.
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