materielle

There are all sorts of contracts that are deemed non-enforceable. Our government should pass a law that bans non-disparagement clauses.

One of the most pressing problems of our time is that these large corporations, on balance, have too much power compared to the electorate.

The problem is funding.

There seems to be a pervasive believe that the Python tooling and interpreter suck and are slow because the maintainers don’t care, or aren’t capable.

The actual problem is that there isn’t enough money to develop all of these systems properly.

Google says that Astral had 15 team members. Or course, it’s so hard to make these projections. But it wouldn’t shock me if uv and ruff are each individually multi-million dollar pieces of software.

If you’d like to invest a million dollars to improve pip, or work for free for 3 years to do it yourself, I’m not sure if anyone would object.

As a Go developer, this is right on the mark. I’ve been hearing good things about Java lately, so I decided to check out the language for the first time since 2012 or something. And I was impressed!

The language maintainers have added so many great features while maintaining backwards compatibility. And slowly but surely improved the JVM and garbage collection. So after toying around for a bit, I decided to write some personal projects in Java.

After a week, I gave up and returned to Go. The build tooling is still an over engineered mess. Third party library APIs are still horrible. I will never invest even 5 minutes in learning that horrible Spring framework when stuff like Django, Rails, or the Go ecosystem exist.

The community, and thus the online forums and open source libraries, still approach engineering and aesthetics in a way that is completely foreign and off putting to me.

What’s actually going to happen is the second they start to lose market share or struggle at all, they will cancel everything Chromebook related and give up.

With that said, I think Chromebook’s still hold a competitive advantage for public school contracts. It doesn’t matter that the Neo is pretty cheap and the best value. Contracts are signed based on what’s cheapest, period.

Also, a big blind spot for a lot of HN: this is going to be big in developing Markets. This is within budget for middle class Latin Americans in a way that even the Air isn’t.

I would really urge everyone to actually engage in the arguments people are making.

Go’s core design philosophy is stability. This means backwards compatibility forever. But really, even more than that. The community is largely against “v2” libraries. After the first version is introduced, Go devs trend towards stability, live with its flaws, and are super hesitant to fix things with a “v2”.

There have been exceptions. After 20 years of the frankly horrible json library, a v2 one is in the works.

Most of the uuid concerns come from a place of concern. After the api is added to the standard library, it will be the canonical api forever.

There are surely pros and cons to this design philosophy. I just don’t understand why people who disagree with Go’s core goals don’t just use a different language? Sorry to take a jab here, but are we really short on programming languages that introduce the wrong v1 api, so then the language ends up with codebases that depend on v1, v2, and v3? (Looking at you Java, Python, and C#)

That’s just not true though. Sure English doesn’t have tones, but there are other tricky parts of the language. Additionally, Russian is another “difficult” language, but all the satellite nations had no problem picking it up.

The real reason people learn English isn’t because it’s easy. It’s because they need to. As someone who is married to an immigrant, it’s not easy for them. They’ve just worked really hard over decades.

Americans will do fine learning Chinese if it ever becomes an economic necessity.

It’s sort of surprising how naive developers still are given the countless rug pulls over the past decade or two.

You’re right on the money: the important thing to look at are the incentive structures.

Basically all tech companies from the post-great financial crisis expansion (Google, post Balmer Microsoft, Twitter, Instagram, Airbnb, Uber, etc) started off user-friendly but all eventually converged towards their investment incentive structure.

One big exception is Wikipedia. Not surprising since it has a completely different funding model!

I’m sure Anthropic is super user friendly now, while they are focused on expansion and founding devs still have concentrated policial sway. It will eventually converge on its incentive structures to extract profit for shareholders like all other companies.

I really think corporations are overplaying their hand if they think they can transform society once again in the next 10 years.

Rapid de industrialization followed by the internet and social media almost broke our society.

Also, I don’t think people necessarily realize how close we were to the cliff in 2007.

I think another transformation now would rip society apart rather than take us to the great beyond.

Most of the core products at Google are still written in pre-C++11.

I wish these services would be rewritten in Go!

That’s where a lot of the development time goes: trying to make incredibly small changes that cause cascading bugs and regressions a massive 2000s C++ codebase that doesn’t even use smart pointers half the time.

Also, I think the outside world has a very skewed view on Go and how development happens at Google. It’s still a rather bottom up, or at least distributed company. It’s hard to make hundreds of teams to actually do something. Most teams just ignored those top-down “write new code in Go” directives and continued using C++, Python, and Java.

I think the problem is actually political capital.

Someone who deeply understands how to qualify the product.

But with enough political sway to tell entire orgs of 1000s employees to shred their timelines and planning docs and go back to the lab until it’s right.

Without those two pieces, the problem is that individual devs and leaders know that there’s a problem. But the KPIs and timelines must lurch onwards!

This just feels so backwards. Yes, I know recreating ambiguous issues is annoying because it’s a lot of work, but it’s also our job.

Reminder: we are asking users to give us money in exchange for software.

It’s our job to deliver that working software. It’s not the user’s job to hold our hands and pep talk us into fixing problems. Users can and should find another product that will just do it for them without the whining.

I think the real point of the website, besides joking around, is poking fun at the broke state of the software industry where a bunch of whiny developers and managers will make a million tired excuses for why their software doesn’t just work.

Highlighting bug report and bureaucratic process in response to “your keyboard is jank” is exactly the mindset we need to change.

The point isn’t to start a forum or technical conversation with Apple devs. The point is to laugh at them because their software sucks and “just one more Jira ticket” isn’t going to fix it.

Hopefully the published postmortem will announce that all features will be frozen for the foreseeable future and every last employee will be focused on reliability and uptime?

I don’t think GitHub cares about reliability if it does anything less than that.

I know people have other problems with Google, but they do actually have incredibly high uptime. This policy was frequently applied to entire orgs or divisions of the company if they had one outage too many.

I don’t think that the parent comment is saying all of the bugs would have been prevented by using Rust.

But in the listed categories, I’m equally skeptical that none of them would have benefited from Rust even a bit.

Is that really true, though?

First off, you’re ignoring error bars. On average, frontier models might be 99.95% accurate. But for many work streams, there are surely tail cases where a series of questions only produce 99% accuracy (or even less), even in the frontier model case.

The challenge that businesses face is how to integrate these fallible models into reliable and repeatable business processes. That doesn’t sound so different than software engineering of yesteryear.

I suspect that as AI hype continues to level-off, business leaders will come to their senses and realize that it’s more marginally productive to spend on integration practices than squeaking out minor gains on frontier models.

Why isn’t it the governments role?

Because you think it’s not?

What if I, and many other people, think that it is?

I think investors would certainly love this. So why hasn’t it already happened?

My guess: they would lose a ton of cultural cachet.

Turning OpenAI into an ads business is basically admitting that AGI isn’t coming down the pipeline anytime soon. Yes, I know people will make some cost-based argument that ads + agi is perfectly logical.

But that’s not how people will perceive things, and OpenAI knows this. And I think the masses have a point: if we are really a few years away from AGI replacing the entire labor force, then there’s surely higher margin businesses they can engage in compared to ads. Especially since they are allegedly a non-profit.

After Google and Facebook, nobody is buying the “just a few ads to fund operating costs” argument either.

I’m actually not a huge Zig person.

But yes, avoiding arcaneness for the sake of arcaneness will earn you more users.

A big success of Rust has nothing to do with systems programming or the borrow checker.

But just that it brings ML ideas to the masses without having to learn a completely new syntax and fight with idiosyncratic toolchains and design decisions.

I actually think this is a pretty good argument against AI dooming that I don’t here that often.

Sam Altman doesn’t own AI. His investors actually own most of the actual assets.

Eventually there is going to be pressure for open ai to deliver returns to investors. Given that the majority of the US economy is consumer spending, the incentive is going to be for open ai to increase consumer spending in some way.

That’s essentially what happened to Google during the 2000s. I know everyone is negative about social media right now. But one could envision an alternative reality where Google explicitly controls and sensors all information, took over roadways with their driving cars, completely merged with the government, etc. Basically a doomsday scenario.

What actually happened is Google was incentivized by capital to narrow the scope of their vision. Today, the company mainly sells ads to increase consumer spending.

Devils advocate: is it really such a problem? Perhaps it should be banned simply on moralistic grounds.

But I fail to see how a hundred or so buildings sold to millionaires and billionaires numbering in the thousands has any affect at all in a city with 20 million people.

Again, surely it’s not the best nor most democratic thing that these buildings exist at all.

But I don’t see how it can impact the bread and butter real estate and rental market. Surely this is caused by the city’s numerous bad housing policies like rent control, zoning, public transportation, education.

My problems with ORMs is that they are a solution in search of a problem most of the time.

We already have an abstraction for interfacing with the DBMS. It’s called SQL, and it works perfectly fine.

That’s certainly an advantage, but I’m not sure that’s the value proposition.

It’s that Chrome and V8’s implementation has grown to match resourcing. You probably can’t maintain a fork of their engine long-term without Google level funding.

It doesn’t even have to be a bug. Having some rule like “invalidate all data older than 6 months” makes it easier to reason about and test for backwards compatibility.

I’m sure the data format of Apple Maps is constantly changing to support new features and optimizations.

Wait, so if we give the foreign workers the same at will employment rights as Americans, then they are no longer interested?

I thought they needed these foreign workers because no American could do the job?

It should be marshaled into {} by default, with a opt-out for special use cases.

There’s a simple reason: most JavaScript parsers reject null. At least in the slice case.

My opinion is that AI isn’t actually the root of the problem here.

It’s that we are heading towards a big recession.

As in all recessions, people come up with all sorts of reasons why everything is fine until it can’t be denied anymore. This time, AI was a useful narrative to have lying around.

Traditionally, there are two strategies:

1) Use the network thread pool to also run application code. Then your entire program has to be super careful to not block or do CPU intensive work. This is efficient but leads to difficult to maintain programs.

2) The network thread pool passes work back and forth between an application executor. That way, the network thread pool is never starved by the application, since it is essentially two different work queues. This works great, but now every request performs multiple thread hops, which increases latency.

There has been a lot of interest lately to combine scheduling and work stealing algorithms to create a best of both worlds executor.

You could imagine, theoretically, an executor that auto-scales, and maintains different work queues and tries to avoid thread hops when possible. But ensures there are always threads available for the network.

That really seems to be the defining characteristic of the 21st century elite: they’re shameless and proud of it.

This has actually been one of the ideas floated by regulators.

The idea is that merit based admissions is actually pretty complicated, so we can allow individual universities continue to experiment with their own implementations and approaches.

However, we can hold them accountable by grading them based on retrospective data.

I think there are two things to keep in mind.

1) Apple and Firefox have enough resources to implement the most recent web standards. When you see a feature which goes un-implemented for too long, it’s almost surely because nobody was even working on it because of internal resourcing fights.

2) Devs aren’t created equal. It’s possible for a team of 8 people to be 10x more productive than another team of 8.

I think a problem with AI productivity metrics is that a lot of the productivity is made up.

Most enterprise code involves layers of interfaces. So implementing any feature requires updating 5 layers and mocking + unit testing at each layer.

When people say “AI helps me generate tests”, I find that this is what they are usually referring to. Generating hundreds of lines of mock and fake data boilerplate in a few minutes, that would otherwise take an entire day to do manually.

Of course, the AI didn’t make them more productive. The entire point of automated testing is to ensure software correctness without having to test everything manually each time.

The style of unit testing above is basically pointless. Because it doesn’t actually accomplish the goal. All the unit tests could pass and the only thing you’ve tested is that your canned mock responses and asserts are in-sync in the unit testing file.

A problem with how LLMs are used is that they help churn through useless bureaucratic BS faster. But the problem is that there’s no ceiling to bureaucracy. I have strong faith that organizations can generate pointless tasks faster than LLMs can automate them away.

Of course, this isn’t a problem with LLMs themselves, but rather an organization context in which I see them frequently being used.