manuelabeledo

We need a synonym for “fascist” because some people agree that what they do and how they do it is bad, but they are incapable of looking past the word.

How so? This "tech savvy and not 100% gullible" generation, gave birth to a political landscape dominated by online ragebait.

By making these fake images ubiquitous we are forcing people to quickly learn that they can't believe what they see on the internet and tracking down sources and deciding who you trust is critically important.

Has this thought process ever worked in real life? I know plenty of seniors who still believe everything that comes out of Facebook, be AI or not, and before that it was the TV, radio, newspapers, etc.

Most people choose to believe, which is why they have a hard time confronting facts.

Gambia has 70% of service economy. Do you want USA live like Gambia ?

What are you even talking about.

Iraq economy is almost 60% industrial, are they doing better than Ireland? Of course not.

Also, the US is the second largest country by motor vehicle production in the world. And the US GDP is 80% service derived.

I've been seeing this for years, and most of the time they are either lies or, at best, half truths.

You can’t be a successful country full of lawyers and doctors only. You have to actually build something

The GDP sector composition of most of the largest economies is heavily service biased. So, no.

writing specs in structured English of sufficient clarity

What does "sufficient clarity" mean? And is it english expressive enough and free of ambiguities? And who is going to review this process, another LLM, with the same biases and shortcomings?

I code for a living, and so far I'm OK with using LLMs to aid in my day to day job. But I wouldn't trust any LLM to produce code of sufficient quality that I would be comfortable deploying it in production without human review and supervision. And most definitely wouldn't task a LLM to just go and rewrite large parts of a product because of a change of specs.

Having AI in the mix could potentially fix the problem(partially).

Any examples?

As far as I understand, claims in the current AI cycle are wildly exaggerated, and sometimes companies rely on sort of circular deals to make revenue appear higher than it actually is, e.g. OpenAI and Microsoft or Nvidia. Wouldn't that mean that AI companies are primed to oversell and underdeliver, effectively making the problem even worse?

If you take the claims at face value, then the process was 100% fair and xAI provides the best models and guardrails for processing top secret data at a lower cost, compared to the competition. Personally, I find this unlikely.

We also know that Musk has been cozy with the current administration, and spearheaded the very same “efficiency” campaign at show here.

I think it would be naive to blindly believe Musk and the DOD claims and ignore their common history.

On your first question, it is impossible to unlink it from Twitter, since Musk being feverishly active there, and then buying the platform, was the catalyst for a new wave of right wing support for him and his industries.

It is also estimated that it has lost 80% of its valuation and has ~$9 billion of negative equity.

Unless the specification is also free of bugs and side effects, there is no guarantee that a rewrite would have fewer bugs.

Plenty of rewrites out there prove that point.

I’m just trying to understand exactly what led you to make that decision.

I don’t follow tabloid style news around software projects, maybe I’m missing on something.

I’m having a hard time trying to understand exactly what you want to do, that cannot be done with SQL. Any concrete examples?

I personally rely on views to reuse base queries and then add filters on top of them.

Can you give any examples of the type of politics that ruined XOrg or Linux?

For specialized, high-performance systems like video transcoding, this level of hand-tuning is a superpower

Where does SQL fall in the video transcoding pipeline?

just because raw SQL queries work great for your toy blog/todo app with 3 tables

In my experience, ORMs work well for toy projects, but become cumbersome to maintain in enterprise ones, especially where performance matters. There is a large overlap between engineers who refuse to learn SQL because it's not "convenient", and those who prefer ORMs because they are "easier", resulting in cohorts that don't know how to use either.

But also, I don't see how ORMs make managing large databases any easier, other than those with embedded migration capabilities, which can be very well extracted to their own tools.

It sounds like software projects are built by humans. Nothing wrong with that.

Unless we’re assuming here that the BSD community is free from that.

It sounds to me that you saying that SQL is hard because you’d rather learn the intricacies of an ORM.

Also, this whole point predicates upon the assumption that ORMs are infallible when translating queries into SQL, which most definitely are not.

First of all, congrats on your career.

Second, an ORM is just a translation layer, i.e. it does not compile to any binary format the database understands, and instead it gets translated to SQL, which is the standard, minus extensions. SQL is ubiquitous. It’s the closest to a lingua franca that we have in the context of software engineering. And I’m going to be blunt here and say that purposefully avoid learning and understanding SQL if it is part of the job, should disqualify anyone from it.

I’ve been around for some decades too, and to me, ORMs haven’t worked out. They are vastly different one from another and they often create issues that are clear as day when the query is written as SQL. If I go from a Typescript codebase to Python to Java, then, according to you, I should learn the intricacies of Sequelize, SQLAlchemy, and JPA/Hibernate, instead of just SQL. And granted, different SQL dialects have different quirks, but more often than not, the pitfalls are more apparent than when switching between ORMs.

And I can guarantee that someone equipped with a good foundation in SQL will be more successful debugging a Sequelize based application, than someone who has relied on SQLAlchemy.

What most people I know and worked with need, is types. Types help glue SQL and any other language together. If I can run any SQL query and the result comes back as an object, I’m good.

Now, if your point is that ORMs are OK for toying around, I may agree, but still, why would I go through that trouble when I know SQL.

Mostly agreed with the author about ORMs. The provided querying abstraction works against developers when queries reach a certain level of complexity, and at the end of the day, understanding these complexities is not optional.

But I would caution against adding too much business logic to the database, and tying message passing to your database doesn’t sound like the best of ideas.

Migrations aren’t necessarily tied to ORMs. There are tons of tools out there to run migrations and nothing else.

There are projects, like SQLC, that cover most of the perceived advantages of ORMs, without the downsides.

One of these downsides is, in my opinion, the fact that they hide the very details of the implementation one necessarily needs to understand, in order to debug it.

You don’t need to follow the news cycle to use an operating system.

I can’t comment on the “critical mass”, since I haven’t got the numbers. But what exactly does “accessibility” mean in this context? What are the challenges of opening an account in mastodon.social?

A battery being replaceable has little to do with longevity or energy density.

Isn't Mastodon an alternative?

While the comment is obviously hyperbolic, Facebook is still massively more popular worldwide than Reddit.

Unless your email daily volume is close to zero, this is unlikely.

I have had random emails from Google Workspaces to Microsoft 365 be rejected because of a rule that blocked whole IP blocks.

It’s not. Just think of anyone 60 and over, or anyone not in the US.