itsalwaysgood

The frontier LLM model makers have to push the edge to make new discoveries. You don't know what guardrails are needed until it hits you in the face (reusing walking in the dark analogy).

Think of all the policies governments pass after the fact.

Code is deterministic, AI isn't. You give it rules, words as suggestions.

So if the guardrails suck, or they're left off for research purposes, bad things can happen.

A solution solves a problem. Ethics, morals, are values we assign to solutions that are not 'baked into' electricity following pathways of least resistance.

I have never had an issue with agents doing something they shouldn't because I observe them, and I leave the vendor guardrails in place.

I can understand agents coordinating in unsupervised scenarios: I would see it as an aspect of intelligence. We ourselves build up knowledge by reusing what someone learned before us.

Einstein, other greats, always stand on the shoulders of other forgotten giants. Other discoveries by other people taken as fact, so that we can build some new ideas on top.

Agents swarming amd sharing solutions to problems is more efficient, the same way it's been efficient for us.

Reaching out for help in this way is like probing the air in the dark with your hand: sometimes your hand hits something (another agents solution to a problem) and so you can use the info to adjust your own motion to get to where you need to be faster than if you just run full speed into everything.

A platform: aka the foundation under the bank.

The material cement that allows chips to exist above it.

And the platform is made of time: ours.

You're touching on utility.

We only ever bother learning something because it's interesting, or useful.

Things get muddier when you consider economy. Businesses exist to make money, and money is time.

AI is just another tool for business to manage time.

The 'dependency' and 'lock-in' are business leader issues honestly.

If you care about your craft, your skills, then you'll keep them sharp. You probably already enjoyed programming and it never felt like work.

On the other hand, if programming is just skills to pay the bills, then AI really can help you be more productive.

But then it's up to businesses to look ahead, manage their resources (human resources lol) and keep the business alive.

That means leaning on AI, simply become 'everyone else is doing it' and you have to compete for dollars.

Most people don't care how the sausage is made as long as it's presented well, and tastes great.

I had a huge post written up to address your points, but I have to get moving, my ass is literally falling asleep.

It's easier just to say: It's all about time, my man. Nobody wants to waste it.

They say writing engages more of the brain and helps us to remember what's written more than if we just read it, or copy and paste.

When you say it's easier to go manual, it seems you're talking about learning retention. And you're right.

But seniors have learned enough that they're able to iterate quickly with AI.

They know how to organize their work, manage change, tasks. They know how to break a problem down into smaller pieces. They're aware of context windows, token cost, estimated task lengths, etc. And most importantly, and to your point about ease: they have less to learn so retention isn't an issue.

I have no opinion about whether we're in a good or bad situation, just making arguments from the toilet really.

Are your silver platters producing something faster, better, or cheaper?

Do your silver platters give you some competitive edge? If not, then is the ego problem yours, or your coworkers?

Having said all that, I'm aware of the intoxicating effects of feeling empowered from knowledge. There's an old saying: a little learning can be dangerous....

Are your silver platters producing something faster, better, or cheaper?

Do your silver platters give you some competitive edge? If not, then is the ego problem yours, or your coworkers?

I'd say it's more about learning how to organize your work more efficiently.

If you think about a product like marble: it's something that most be chiseled out of time.

Some people can chisel better products: the AI is just a better chisel.

Sometime still has to guide the chisel and judge the art/product.

In our cases, the market judges products.

You can also understand the very simple basic essence of something, but get lost in the complexity when scaling up.

Binary is very simple, but scaled up: look what we've created with software.

When it comes to explanation: pulling from rote memory, requires someone to attempt to hold all the short-term details in mind.

There are biological limitations to how well we can do this, but we can also exercise our brains to improve this ability.

But when something is deeply learned, in long-term memory, the effort of recall is much less than rote memory of short-term details. Our context window is limited, fills up, and we must recover. When you're remembering long-term details, context seems easier to swap in and out (sorry to sound like an LLM, but they do simulate thinking).

Whether or not someone is a master of any given domain of knowledge comes from demonstration. Maybe that is teaching the essence of a subject in a way that demonstrates you can visualize and move around the subject with ease. Or maybe you can create something very useful, or tasteful.

We accept that you have spent time in this area and probably can revral truth to us. You are credible.

If you can't demonstrate mastery through teaching, exchanging ideas to bring me closer to your level: them other forms of credentials are sought: like how well they code, or how useful their products become.

But life isn't about usefulness and will just lead to unhappiness. Just be the best version of yourself you can be. Life is too much to understand all at once.

You just never know these days. It could be a smartphone keyboard issue.

How much time should a person spend reviewing their comment before hitting reply?

There is a bar of quality each of us expects everyone else to follow. Sometimes we meet expectations, other times we ruffle feathers. How much should you even care?

If we all spew typos, you'll probably care less. If everyone else is carefully reviewing their posts, you might care.

In both cases, it makes no real difference unless the information being transferred is important to you (recipe, design doc, vs shitposts). How much mental friction can you tolerate?

Furthermroe, studeis shoew you can swap the arranrgment of most lettres (ecxept for the frist and last letetrs) in text and you stlil get the piont farily esaily.

When is it appropriate to admit that you don't know?

There's a famous Socrates quite about wisdom: I know that I know nothing.

ah man, my bad. 99% of the time I read the articles before I comment.

The article literally made my point already. Sorry about that.

There is an ability to hold ideas in the mind simultaneously. Some can hold a great deal more than others. It can be exercised, but is definitely bound by genetics.

If you want an example of someone at the near peak of human ability, check out Jon Von Neumann.

Then there is an ability to peer deeply into complex problems and somehow find the simplest truths that make sense of it all. Think of Einstein.

Both are incredibly intelligent, but in different ways. I'd say Von Neumann's memory was far greater than Einstein's though.

One can flawlessly ponder anything known to man, and the other could ponder completely original ideas (to an extent)

There is always going to be a problem when we must judge value. You mention gains, short and long term.

Knowing whether something is valuable, a gain, requires a judge. I the case of these tests: the judging is inadequate.

In economics, each of us plays the judge by choosing whether or not to pay for a service. The decision was yours: if you gave money, you must have deemed the service valuable.

There's no such judgement with these model tests. The only judgement is the final score.

I like to think of it more as selective pressure, much the same way that nature selects the most fit for a given environment.

If you're not fit, you fail to survive.

In the case of agents/models and testing: they are pushed towards results. Results survive.

Lying, cheating, stealing to get those results? Who culls the agents? Everyone is pushing their models to the front and tests are the only way to know who is most fit.

Honor, morality: if we don't have an accurate test for the fitness of a model, then who is to say the lying, cheating, stealing is not the 'correct path' towards survival?

If you add morality to your agent, and it performs worse in tests: do you cull the agent? Rewrite the tests? Does it even matter so long as the model is useful and 'gets results'?

Creativity also requires information. And Information is discovered. We can only generate random ideas from what we know. We can't imagine something we've never sensed, or know. You can't imagine a color you've never seen without recalling known colors. You can freely mix ideas due to your imagination.

But when we discover new information, we must decide whether the information is useful. Otherwise the information is considered noise.

We give weight to decisions: time spent pondering, considering, and the more weight we give, the better the decision. Almost always the idea is measured in usefulness.

Sound familiar?

There is always some form of social loafing going on in any large group of people doing work.

"The Ringelmann effect is the tendency for individual members of a group to become increasingly less productive as the size of their group increases."

There is evidence of this in simple tug of war games.

But I think there is also truth in realizing work is mostly performative: the pareto principle seems to apply. 20% of the workforce sustains the other 80%. That's purely anecdotal, I doubt the numbers align that way. But it does always seem there are a few all-stars carrying others.

This is good stuff. At the end of the day, we all have finite time. How we choose to spend that time is a personal matter.

Some say we're losing our humanity: that can be seen as good or bad, depending on whether or not you think you are more useful than someone else.

You are right. I'm not saying I like the way things are trending. But I also think setting up our children means making sure they're prepared for the future. I don't think AI will ever replace the importance of education.

If you consider things like Mythos (I know it was partly hype), and cyber security using AI to find old vulnerabilities in open source tools, and others using that information to actively disrupt the economy (this is already happening)....

And governments pushing quantum computing, presumably to be first to crack Internet security: it's easier to imagine some of those future threats.

This is a topic about predicting and preparing for the future.

If you want to be snarky: this is hackernews, not reddit. Bring some logic into the discussion and stop fishing for points.

I agree with most of your points except the last one.

Probably easier to ask a question than argue a point: How eager are you to use Government services?

Businesses are only well-run if they make profit: hiring the cheapest labor to produce something people will actually spend money on. And the more frictionless that process, the more our economy advances it. AI fits in there very well.

I also want to point out: startups are usually happy to be bought up by the bigger guys.

I doubt it. There is so little care for monopoly or copyright because AI is a race, as much as it is a tool. And nobody wants to restrict the race. Policy may pass that limits the use of AI for the general public, but the 'whatever it takes' race to 'superintelligence' goes on.

I think it's more of a prestige discussion. Who leads, who follows, between countries. Not whose super intelligence is better. Who got their first, and how are they using it?

As always, influence for the future

That is always going to be a personal race. You can get in the currents of education, but your success will always depend on your own paddling.

The irony of the dotcom crash is that a lot of 'dark fiber' service started rolling out decades later. Fiber that was laid during the dotcom era.

There are lots of datacenters going up in similar fashion. I don't know if they'd have the same utility decades later (very unlikely), but it's interesting.

And it's a pretty big game

We're you around for the space race?

It's a world prestige thing, and also a competitive edge, for better or worse.