alt Hacker NewsOne thing this really highlights to me is how often the "boring" takes end up being the most accurate. The provocative, high-energy threads are usually the ones that age the worst.
If an LLM were acting as a kind of historian revisiting today’s debates with future context, I’d bet it would see the same pattern again and again: the sober, incremental claims quietly hold up, while the hyperconfident ones collapse.
Something like "Lithium-ion battery pack prices fall to $108/kWh" is classic cost-curve progress. Boring, steady, and historically extremely reliable over long horizons. Probably one of the most likely headlines today to age correctly, even if it gets little attention.
On the flip side, stuff like "New benchmark shows top LLMs struggle in real mental health care" feels like high-risk framing. Benchmarks rotate constantly, and “struggle” headlines almost always age badly as models jump whole generations.
I bet theres many "boring but right" takes we overlook today and I wondr if there's a practical way to surface them before hindsight does
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The one about LLMs and mental health is not a prediction but a current news report, the way you phrased it.
Also, the boring consistent progress case for AI plays out in the end of humans as viable economic agents requiring a complete reordering of our economic and political systems in the near future. So the “boring but right” prediction today is completely terrifying.
Instead of "LLM's will put developers out of jobs" the boring reality is going to be "LLM's are a useful tool with limited use".
I predict that, in 2035, 1+1=2. I also predict that, in 2045, 2+2=4. I also predict that, in 2055, 3+3=6.
By 2065, we should be in possession of a proof that 0+0=0. Hopefully by the following year we will also be able to confirm that 0*0=0.
(All arithmetic here is over the natural numbers.)
This suggests that the best way to grade predictions is some sort of weighting of how unlikely they were at the time. Like, if you were to open a prediction market for statement X, some sort of grade of the delta between your confidence of the event and the “expected” value, summed over all your predictions.
It's because algorithmic feeds based on "user engagement" rewards antagonism. If your goal is to get eyes on content, being boring, predictable and nuanced is a sure way to get lost in the ever increasing noise.
> One thing this really highlights to me is how often the "boring" takes end up being the most accurate.
Would the commenter above mind sharing the method behind of their generalization? Many people would spot check maybe five items -- which is enough for our brains to start to guess at potential patterns -- and stop there.
On HN, when I see a generalization, one of my mental checklist items is to ask "what is this generalization based on?" and "If I were to look at the problem with fresh eyes, what would I conclude?".
Is this why depressed people often end up making the best predictions?
In personal situations there's clearly a self fulfilling prophecy going on, but when it comes to the external world, the predictions come out pretty accurate.
"Boring but right" generally means that this prediction is already priced in to our current understanding of the world though. Anyone can reliably predict "the sun will rise tomorrow", but I'm not giving them high marks for that.