So when I read about Exchange Server to me it still feels quite modern.

I mean we literally do this every few seconds already with natural birth processes.

The one thing that is clear is if it can become more cost effective it’s world changing. Even at its subsidized standards now it’s world changing. And it’s reasonably classified as AI IMO, but it’s not self aware.

I think a lot of your general traditional researchers are fundamentally looking to understand ourselves through machines as proxies in a sense. Something self aware that senses, learns, adapts, so on. The current path isn’t there or necessarily clearly the key to achieving that. That may be the disconnect. I think LLMs may give us some hints at that but not the full picture.

Still incredibly powerful for things we once considered nearly impossible.

With that said part of the reason some domains may not have robust cheap verifiers is because they’re difficult to produce already, so it may be a bigger lift.

Manager: “Why isn’t feature X available?”

Person B: “key pieces are delayed due to the developer not understanding all of the LLM doesn’t and implementation.”

Manager: “does it work? What are the risks?”

Person B: “well yes it works for now but we’re accumulating tech debt due to a lack of understanding and potential flaws that haven’t been thought out yet”

Manager: “they want feature X, ship it, we can deal with it later, I don’t care if it’s not coherent as long as it works.”

How many decades at this point has these been a push for functionality over everything at all costs? And you have a mechanical snow plow now. Most businesses don’t care about later risk or any future planning beyond the quarter horizon, they’re not concerned about how it will effect their performance in 3 quarters or lead to instability or issues, those are future problems for a future person and we’re here for money now.

Something I’ve noticed in collaboration that does occur is an increased confidence in people outside their domains to say things with conviction. I have people who have limited experience with software pushing out layers and layers of abstracted code that’s fairly sophisticated but often misguided in intent who will say what they’re doing is correct, with conviction.

I also hear a lot more questioning people in their domains and challenging opinions, then hearing what I can only imagine are fragmented pieces of conversations they had with an LLM thinking through some argument. Then there’s silence when you discuss shortcomings, then they come back later with their memorized fragments of what you said, combined with memorized fragments of the LLM response to the argument.

It’s occurring, a lot more. People are treating their LLMs in collaboration as a source of truth and using then to focus on their specific path or goals they think or have bias towards going down, vs just opening discussing things, considering tradeoffs from experts multiple disciplines weigh in on and then taking an approach that everyone finds most agreeable.

It’s making me want to be a lot less collaborative with such individuals. I don’t want to sit around and refute Claude text outputs all day.

They can both be a problem, it doesn’t have to be mutually exclusive. I’m sure in all the turnover Trump removed some incompetent people. He also probably removed quite a few competent people. The ratio is what matters.

The question I have is how far back that curve can go without relying on economies of scale to just drag all the points back to the left. And without overfitting a specific metric that I don’t need (like this test).

Astra please create a benchmark that’s favorable to your reasoning skills with a human interface but don’t make the score too attainable add some small issues that keep you below 100% to look sensible and to keep my evaluation metric side gig going.

Alignment++

Is that true though? Many of the core LLMs need to be retrained as languages evolve to incorporate changes (language specifics, compilers, tooling, etc.). To some degree this can be handled via context injection in a variety do forms (agents looking up documentation and so on) but inevitably it’s not stationary in time, just as your OSS stack (probably) isn’t (depending on the languages, technologies, and use cases).

So your hardware is to some degree dependent on the good merit of groups like Z or Alibaba or whomever pushing out updated open weight models that dumped loads of capital into to train. You can keep using the existing models but at some point I suspect they’ll start to have more friction due to dated specs in language and so on. Again there are tuning and ways of layering this information on, and in theory you can even do some training on your own but I don’t think it’s as stationary as being portrayed here.

Those updated open weight models may not always be there (updated on new data). The usability of them is probably fairly long to be fair, but I suspect you’re going to see explosion in everything from libraries to languages etc due to LLMs so even the rate of change across your OSS stack may cause these models to be dated quite quickly, at least in the core model which will require layering fixes.

To be clear I’m on the fence thinking about much of the same issues and as close as I am to pulling the trigger, I keep thinking of very valid counter arguments as to why it’s me just wanting this thing I own. Which may be enough.

Who owns the looms and what they do with them isn’t inherently an issue if all loom owners can do is buy an extra Yacht. Instead they can enforce ungoverned law on society through a combination of disproportionate influence in government and through market forces where private policy (especially at large) become nearly undifferentiated from law (the policy that benefits them becomes so widespread and normalized that alternatives are for all intent and purposes impractical or unreasonable, therefor private policy within a capital ownership domain is law or they’re a monopoly so their policy is the policy).

But I think you’re right, as always we’re going to focus on the adjacent issues vs addressing the root of the problem. The issue is what wealth inequality affords one, when it is capable of infringing on rights and livelihoods of others, not that they necessarily have to share the other luxuries and rewards of their attained wealth. I care not how many luxuries in life Musk has, I may be envious from time to time but whatever. I care a lot more when things he does or says has unrealistic influence and affects me directly, just because he sits atop a mountain of capital and we pretend that mountain of capital somehow was bestowed upon him from divinity that he should have such influence. I’m picking on Musk because he’s the richest and has clear examples of this, he’s by no means alone… it’s that class of wealth at large.