This weekly roundup thread is intended for all culture war posts. 'Culture war' is vaguely defined, but it basically means controversial issues that fall along set tribal lines. Arguments over culture war issues generate a lot of heat and little light, and few deeply entrenched people ever change their minds. This thread is for voicing opinions and analyzing the state of the discussion while trying to optimize for light over heat.
Optimistically, we think that engaging with people you disagree with is worth your time, and so is being nice! Pessimistically, there are many dynamics that can lead discussions on Culture War topics to become unproductive. There's a human tendency to divide along tribal lines, praising your ingroup and vilifying your outgroup - and if you think you find it easy to criticize your ingroup, then it may be that your outgroup is not who you think it is. Extremists with opposing positions can feed off each other, highlighting each other's worst points to justify their own angry rhetoric, which becomes in turn a new example of bad behavior for the other side to highlight.
We would like to avoid these negative dynamics. Accordingly, we ask that you do not use this thread for waging the Culture War. Examples of waging the Culture War:
-
Shaming.
-
Attempting to 'build consensus' or enforce ideological conformity.
-
Making sweeping generalizations to vilify a group you dislike.
-
Recruiting for a cause.
-
Posting links that could be summarized as 'Boo outgroup!' Basically, if your content is 'Can you believe what Those People did this week?' then you should either refrain from posting, or do some very patient work to contextualize and/or steel-man the relevant viewpoint.
In general, you should argue to understand, not to win. This thread is not territory to be claimed by one group or another; indeed, the aim is to have many different viewpoints represented here. Thus, we also ask that you follow some guidelines:
-
Speak plainly. Avoid sarcasm and mockery. When disagreeing with someone, state your objections explicitly.
-
Be as precise and charitable as you can. Don't paraphrase unflatteringly.
-
Don't imply that someone said something they did not say, even if you think it follows from what they said.
-
Write like everyone is reading and you want them to be included in the discussion.
On an ad hoc basis, the mods will try to compile a list of the best posts/comments from the previous week, posted in Quality Contribution threads and archived at /r/TheThread. You may nominate a comment for this list by clicking on 'report' at the bottom of the post and typing 'Actually a quality contribution' as the report reason.
Jump in the discussion.
No email address required.
Notes -
The psychic cost of AI is already here
Ugh, another AI post.
Today Block laid of about half its 10k employees for AI reasons and the sock soared. Was this pr cover for shedding bloat? Maybe. Elon famously slimmed down Dorsey’s crazy bloated twitter, no AI cover story needed.
But still, the market loved this and will demand more.
Earlier this week IBM stock dived on some Anthropic COBOL skill. Was this premature doom? Maybe. But still.
Let’s put aside whether AI will destroy white collar work in a short term time horizon. Despite the outcome, the idea that it very much might is already mainstream. It’s in the water. How much is the impending fear already shaping decisions? How much psychological weight is it already causing? How much will it accelerate
Certainly people are already changing career plans, college plans, savings strategies, family planning, etc. and it will only get much worse. New broadly available opportunities in AI are not going to open up faster than the fear of AI disruption will spread; we are already in a spiral.
Like many in these spaces, I’ve been worried for a while now, but now it’s going mainstream and will cause aggregate changes in behavior which will have their own effects on society and the economy regardless of the first order effects of AI disruption.
As a minor example, my wife has wanted to move for a few years now. Unfortunately, we’re chained to a 3% mortgage without enough income to achieve escape velocity beyond moving sideways to pay more. We’re finally in a spot this year where we could be a little indulgent and justify moving into a house the right size for a young family of 7, even if means taking on some unoptimized mortgage rate increase.
But I can’t imaging compounding that risk with AI disruption. The music could stop and never start again. Our marriage is good, but my resistance causes its own minor stress. How many marriages aren’t so good, break down over things like this?
How many people don’t get married altogether, etc.
Regardless if Covid was just a flu, the real world response to the percieved threat was transformative. Regardless if AI is just a fad…
The AI bubble is going to pop this year. Private equity no longer has enough money to continue to fund massively unprofitable OpenAI and Anthropic, or even the NVIDIA chip glut. A lot of these layoffs are either performative attempts to raise stock prices, or cutting fat that would have been cut a long time ago even if AI wasn't a thing. As long as you don't have all your savings in AI companies (or are over invested in index funds), and can avoid getting fired in the next 6-10 months, I think you will be okay.
Further reading
This is outright wrong [1]. It’s trivial to run an LLM deterministically. Just do greedy decoding (or beam search, etc.) The fact that the author doesn’t know something so basic about how to use LLMs now makes me doubt that he knows enough to predict what they will or will not be able to do in the future, so I stopped reading here.
[1] Barring nitpicks about subtle non-determinism due to hardware differences or software environment differences across machines. Also, LLMs (particularly older ones) can be highly sensitive to specific changes in their inputs, but this has nothing to do with LLMs being probabilistic.
I think you can trivially make an LLM deterministic in the technical, narrow sense that for exactly the same input you get exactly the same output. Just initialize the pseudo-random number generator deterministically.
However, where LLMs differ from most classical deterministic algorithms is that they are not stable, a small change in the input might result in a big change in the output.
Suppose I have a list of strings I want to sort lexicographically. If I use std::sort (and stick to ASCII), I can expect to get reasonable results every single time. If instead I give the task to a neural network, such as a human, I will get some significantly non-zero error rate. If I use an LLM, I would also expect an elevated error rate. Of course, both the LLM and the human might also refuse to work with certain strings, e.g. racial slurs.
Generally, nobody uses neural networks to solve problems which are easily solvable by classical algorithms, teaching aside. But there are a lot of problems where we do not have nice classical algorithms, such as safely driving a car through the city or translating a text or building a website from informal specifications. So we accept the possibility of failure and hand them out to LLMs or grad students.
This is not unique to LLMs. This happens to pretty much any algorithm that feeds its outputs back into its inputs without converging. Probably the simplest example is that, if take a degree 3+ polynomial, and you use Newton's method to find the complex roots, and you plot which root was found by the initial value, you get a fractal (Newton's Fractal) rather than a smooth diagram. There's a great 3blue1brown video on this actually.
But yeah, that generalizes to a surprising number of iterative processes (e.g. neural net training)
More options
Context Copy link
More options
Context Copy link
More options
Context Copy link
More options
Context Copy link
More options
Context Copy link