alt.hn

But it's not fun to be figuring out new things all the time. Some amount of routine work is necessary to 1) exercise mastery (feels good), and 2) recover energy. This is why a lot of people find agentic coding exhausting and less fun, you're basically always having to be creative (what's the next feature?) or solve the hardest 5% of issues the LLM can't handle.

by lebek

> This is where LLM is currently going.

This is not where LLMs are currently going. They are trained and benchmarked explicitly in all areas that humans produce economically and cognitively valuable work: STEM fields, computer use, robotics, etc.

Systems are already emerging where AI agents autonomously orchestrate subagents which again all work towards a goal autonomously and only from time to time communicate with you to give you status updates.

Thinking that you as a slow human will be needed for much longer to fill some crucial role in this AI system that it cannot solve by itself, and to bring some crucial skill of creativity or thinking to the table that it cannot generate itself is just wishful thinking. And to me personally, telling an AI to "do cool thing X" without having made any contribution to it beyond the initial prompt also feels very depressing and seems like much less fun than actually feeling valued in what I do. I'm sorry for sounding harsh.

by mofeien

I suppose it depends on your definition of “doing” - if it’s “writing code”, then sure. But there’s a whole world of actual, physical “doing” that AI is nowhere close to matching humans at, and it’s much easier for me to envision a world where AI replaces the management / “thinking” layer of society than the physical labor. Which is scary, because it’s the opposite of his (and I would assume most people’s) ideal.

by plaidfuji

So you just lose your job.

by croes

LLMs are shit at doing stuff to anyone who is a domain expert in the thing that they are supposed to be doing. They are trained on a huge corpus of average stuff. They produce average to crappy solutions quickly. The technology industry bubble is trained to accept that as good enough which is why everyone is excited. Elsewhere it's a complete and utter joke.

And on top of that, a huge chunk of doing requires humans to physically do something or absolute determinism is better anyway, neither of which an LLM is capable of.

None of it makes sense.

Edit: actually the technology industry moves the goalposts to match the claims. That is the dishonest bit. I've not seen any evidence of novel capability which isn't corrupted by some dishonest measurement approach.

by dgxyz

We currently have two broad mechanisms to equate people's value.

*Employees:*

Easy to replace = Low Salary = Gets Few Resources

Hard to replace = High Salary = Gets Many Resources

*Entrepreneurs:*

Output consumed low = Low Pay = Gets Few Resources

Output consumed high = High Pay = Gets Many Resources

(Resource consumption ignored)

In a world where machines do everything, aspects of these change:

*Employees:*

Easy to replace = Gets whatever resources

(no-one hard to replace)

It is up to us to define whether 'whatever' is bleak or not. If we decide that resources need to be shared fairly, it could be heaven, not hell.

*Entrepreneurs:*

Resource consumption: Whatever

It is up to us how much resource consumption we allow. If we decide that resource consumption need to be sustainable, it could be heaven, not hell.

by elevatortrim

If the Epstein class won't allow for everyone to have a reasonable standard of living when they relied on workers to produce, the chances of them allowing it when they don't is next to nil. They couldn't even bear the thought of people working from home, for no other reason than the workers liked it, and that cost them nothing.

by Devasta

But the difference is:

What Deep Blue did was (if the Wikipedia page is correct) Alpha-beta pruning[0], where some humans came up with the function for what "better" and "worse" board states look like.

And what LLMs do (at least the end models) includes at least some steps where there's an AI trying to learn what human preferences are in the first place, in order to maximise the human evaluation scores. Some of those things are good, like "what's the right answer to the trolley problem?" and "which is the better poem?", but some are bad such as "what answer best flatters the ego of the user without any regard for truth?"

The former is exactly like route-finding, in that you could treat travel time as your score of better-worse and the moves as if they're on a map rather than a chess board.

The latter is like being dumped into a new video game with no UI and all NPCs interact with you only in a language you don't know such as North Sentinelese.

[0] https://en.wikipedia.org/wiki/Alpha–beta_pruning

by ben_w

It's neither how computer chess works or how LLMs are trained.

Computer chess uses various tricks to prune the search space of board states, where the search is guided by the "value" of each board state. Neural networks can be used (and probably was at the time) to approximate this value, but there can be hand coded algorithms with learned statistics or even lookup tables for smaller games than chess.

There's no search in LLM training.

by yobbo

The reference to pong makes even less sense.

by Lionga

LLM’s are the virus of the mind - people think so what? I get my output and move on.

Yeah.. no. You need that thinking capacity to protect yourself. Once that’s gone en-masse, what’s left of the democratic system (not much) will completely collapse. Congrats to legally creating an environment that yields oligarchy.

Altman and his cronies yearn for a swath of people who cannnot think for themselves.

by ugtr3