Fuck AI

There are a few, yeah. Whether it's enough to balance the massive weight of all the externalities, I have no idea. Currently leaning no. Could be wrong about that, who knows.

Basically: we now have the tech to make sense of language and language semantics, and use language as a universal interface. You and I are fine clicking buttons in programs, sure, but you and I are also having this discussion on an obscure federated social media platform the general public has never heard about. Interacting usefully with a computer system through language alone becomes possible in a way that it wasn't before. I'm not quite sure how valuable this is going to be in the long term, but then, I'm also a tech nerd who is used to clicking buttons and writing command lines.

We can now process large amounts of text fast for data extraction, which is a deceptively hard problem. You can do things like importing itemized PDF bills into an accounting database with no prior knowledge of how those bills are formatted. This extends beyond text. We can now generate a textual description of arbitrary images and videos. That too is a very hard problem. It can now be done on a regular desktop computer using a small local LLM.

It's an even harder problem when the text is computer code and the data being looked for is the cause for a specific behavior. The process of debugging an obscure issue can now be massively accelerated.

Given a reliable corpus of knowledge, that corpus can be queried more or less instantly using natural language. That's also something we could not do before.

LLMs suck at designing software but can produce code to spec faster than a human, which means they can be used to increase throughput where a skilled human does the design and is limited only by the speed of implementing it. Given the prevalence of software in the economy, the impact of that alone will be significant.

All of these come with major drawbacks and sometimes intractable problems. Language is squishy and ambiguous. LLMs don't THINK, they extrude statistically probably continuation tokens. AI content sucks, be it writing, images, videos, because the probable tokens there are the median of the training corpus, and median is a cognate of mediocre for a reason. I hope AI slop goes away. But I don't think it will. The ability to generate custom porn on demand alone will likely sustain a market.

And I didn't think we can go back to the world of before. But personally, I wish we could. Because the externalities here are, and remain, enormous.

I've heard the underlying maths is good for doing statistical analysis of particle physics. It won't "find" new physics, but it will point to models that are at least mathematically sound.

Of course, researchers will still have to test those models with real world experiments. Science is mostly establishing how the universe doesn't work.

Programmer here. They can be a useful tool if used correctly. They are great at writing unit tests, useful for upgrading older code, and really useful as a semi-intelligent autocomplete.

If used incorrectly they will generate a giant mess that works briefly but becomes impossible to expand on, full of duplicated sections that makes maintenance super difficult, and have weird logical flaws.

I prefer using agents running on my own desktop rather than paying somebody for it.

Yeah so far all the "advantages" have been "cutting corners inaccurately."

I think it's good for pattern matching. However, I think LLMs are mostly useless because it lacks human context. It's a chat bot at best.

I'm generally an AI skeptic/hater, but finding new medicines, detecting cancer earlier on, IT security auditing, discovering new battery chemistries......for things that are predicated on pattern recognition, are audited by a human, and basically regurgitating a blended up version of previously established data is what you're after, it's really good at those things and I'd argue there is a real use case for generative AI in these places.

As a means of mental health therapy, customer support, computer programming tasks that aren't reviewed, or basically any task that is NOT audited by subject matter experts, it fucking sucks and, unfortunately, it's being broadly applied in these roles that it sucks at. Per usual, it's because those things make money and the things that actually could help humanity don't always.

The capitalists are driving AI adoption. They want to use it to make the unwashed masses lazy and stupid by being dependent on their product and make trained, skilled employment a thing of the past. That is the problem with generative AI.

For me, AI is great at comparing large data sets. It can detect the most miniscule change in the night sky and is great for measuring luminosity changes over time.

Other than that, it's kinda useless for me. Maybe I'll play with it and change out actors in famous scenes for cats like those kungfu clips of late.

All the GenAI art, video and even vibe coded websites can dramatically speed up prototyping and seeing how something might look or work.

Yes that costs jobs even if its only at the early stage and is done by humans after, but its real value and can overall speed up development on ideas.

Like I was building a new feature in my software, I knew the constraints, what I wanted it to do, and I asked it to start making some visual mockups of what might work. There's no way I could manually generate that many ideas and then fine tune them before finally coding it myself for real faster. Like it or not, that is positive.

LLMs are really good at pattern recognition, making them an excellent tool for scientists and medical researchers.