Funding for basic research is being slashed by the current administration. Our society is underinvesting in basic scientific research. And, AI will not fill the gap.

It's just because of this administration but future admins can revert it back and even then, i would expect the fund receivers themselves will eventually use AI so.

tech writers disrupted by AI a couple of years ago? Seems very dubious. A couple of years ago, AI was terrible at writing anything.

AI writing is soooo annoying. It's always way too long and way too "serious" for what ultimately is almost always a really dumb point. There is no calibration to the seriousness of the topic or thesis against the actual length of the writing. It's insufferably pompous. Will it get better? Probably.

ever since the discovery of amyloid plaques, it's been an open question. Are they causative or a symptom? Would reducing or eliminating them help treat the disease? There is lots of data that supports amyloid as a disease treatment target, particularly in animal models. Of course the abject failure to actually develop a good anti-amyloid treatment that actually provable and significantly mitigates the disease weighs against the idea that amyloid is a good target. And the high profile frauds that have been discovered haven't helped. But, the biomedical community are not a bunch of morons. All these drug companies wouldn't have spent these billions of dollars on anti-amyloid and anti-tau if they were such obviously terrible ideas.

I think that's an incorrect way of looking at it. A small unforeseen factor is almost always going to be a negative factor, not an unforeseen benefit. Space is a hostile and unforgiving environment without an easy way to bring things back, fix stuff, and/or re-deploy. A small mistake on the engineering, planning and/or implementation is likely to sink the whole thing worse than the napkin math suggests is almost certain failure anyway. Similarly, there are few ways to "get it right" and many ways to fail.

Will be interesting to see if, in hindsight, there are clues to this in the preexisting literature that we just hadn't quite recognized.

This is one of the areas where AI will accelerate scientific research, by scanning through the journal archives to make connections that no one had noticed before.

See, my thought would have been the opposite: in a situation like this—where nobody tries the thing because “everybody knows” it’s counterproductive—I’d expect AI literature surveys to confidently assert received wisdom.

It sounds from the quote like even the researchers thought it was a mistake at first… and that on the basis of the literature PLUS their collective professional wisdom. Now, obviously, they did in fact try the thing, so maybe the idea was not quite so wacky as they paint it for the article.

But the point feels similar here as with LLMs and writing: they can do what’s come before pretty well, and they can exhaust a well-specified problem space through sheer muscle; but they seem to be less good at evolving the frontiers of the domain, and I see no mechanism by which to expect that to change.

So I tend to take the opposite lesson: surprises like this renew my hope that there will remain a place in science long into the AI era for meatbags and serendipity and the spirit of curiosity.

LLMs don't rely completely on received wisdom. The training process works in a higher dimensional space so some data points that might seem unrelated to humans end up being clustered close together if there is a hidden or unrecognized relationship.

True, but the clusters do come from somewhere—namely the training set and the input. The more technical the literature, the sparser the prior work; the more answers depend on labwork, the less the bottleneck is purely symbolic reasoning or data-retrieval-at-scale.

To hear it from the researchers, this feels like the sort of finding that, even in retrospect, is non-obvious from existing literature.

I remember hearing scientific progress described in terms of punctuated equilibrium: some Big New Idea, then a bunch of work generalizing that new idea to the rest of the problem space. I could see AI tools speeding up the second type of work: taking a new framework and chewing through everything that came before, in that new light.

But I have a hard time thinking about how the AI techniques could produce novel, surprising outcomes like this one—ones where it’s not just a permutation of existing knowledge, but where it turns out reality actually cuts against the accumulated written knowledge that came before. The “there is magic to be explained here!” aspect of science.

> But I have a hard time thinking about how the AI techniques could produce novel, surprising outcomes like this one

The comparison is not equivalent as a human isolated from the environment and unable to perform experiments would fair the same.

It is through conducting experiments that we make discoveries.

Once AI can hypothesize and run experiments from start to finish I see no reason why novel discoveries won't be made this way.

Yes, that's only if AI would ask you to validate all prior assumptions to avoid being led by a false premise. I don't see AI or humans bothering to do that.

There are so many counterexamples proving that your statement is just not true. I'll give you just one example, the Berkeley physics professor Richard Muller that took funding from the Koch foundation to attempt to "prove" that the satellite temperature data was "miscalibrated" and estimates of actual warming were overblown. Started the project in 2010. First published in 2011 showing that in fact the warming was real and using more advanced calibration techniques actually showed the warming was worse than we thought.

You can't definitively diagnose it without an autopsy of the brain.

We truly do not know the root cause. There are plenty of folks with "degraded" endocrine, cardiovascular, and both systems. Most of them do not develop Alzheimer's.

How many of them have their lymphatic and glymphatic systems effectively halted by parking their bodies in a chair or being bedridden?

Even the most unwell person (in the US) is still dragging themselves to the store and work, on average.

Simple, brief movement that we often relieve the elderly of is the pump that actions the lymphatic system.

Being older brings its own additions to the table.