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> The notetaking people—and I say this with all the love in the world—are never, like, a researcher at the cutting edge of their field, building this vast cathedral of knowledge, note-by-note, so they can derive new insights. Never a historian who has to read tens of millions of words across thousands of sources to synthesize the life of some historical person. It’s never someone doing something hard. It’s always some blogger. Their “digital garden” is about how to keep a digital garden. It’s very solipsistic: there’s no output, no deliverables. The deliverable is you take a screenshot of your Obsidian graph and tweet about it to show off how much it looks like an incomprehensible ball of twine.
> Sometimes, tools don’t move the needle because there’s no needle to move.
It reminds me of something my old CS mentor, now elderly, had said about LLMs a few months ago: "it's a force multiplier, but there has to be some force to multiply."
This likewise is a basic fact I encounter over and over:
> Knowledge is another limiting factor. I find that even very educated people tend to underrate the importance of knowledge. A lot of people have this attitude that you can just Google everything just-in-time as it comes up. Like Babbage, I can’t rightly apprehend the confusion of ideas that would lead someone to think this.
It's quite possible that those researchers and historians do exist, but are working instead of posting about notetaking. It's like saying the people who write Python tutorials never seem to ship anything impressive, so Python must be useless.
The assumption here is that the multiplier x is a number >1 and not a fraction <1
Most time the best they can muster is “A faster horse”
This was a good read but this felt like a personal attack :)
> Is an agent going to match the effectiveness of methylphenidate in ADHD? I doubt it.
having, only recently, been diagnosed, it is clear to me methylphenidate > claude-sub-pro-max
And I'd also add that AI strongly disaggregates the returns to different levels of the capability to deal with abstraction -- higher levels get more, lower levels get less -- rather than uniformly boosting returns across the board (unfortunately). Of course, this has been the trend of information technology since at least the '80s, but now the slice at the top is really small and the returns very high.
But of course he's not really wrong. I've been a heavy user of Anki and a heavy reader of certain schools of academic literature on second language acquisition and knew exactly what I wanted and why and how it differed from existing tools.
The lesson I take is that you need a specific problem that you truly understand, whether it's your own problem or not.
Then… I wanted to apply this to (beginner level) language learning. And yep you have to be disciplined to go through the cards daily, but it works.
My app is 100% free so my trick was to have users write what they need, the app generates a prompt to give to any AI provider, which in turn gives you back a JSON that will be converted into a deck.
Nothing truly ground breaking, but again it works for beginner level concepts :-)
uhoh
i've been spotted
I have another post you might find useful :)
https://borretti.me/article/notes-on-managing-adhd
It made me think, considering how much content is being written with AI, would an LLM ever write something like this?
For some reason they I can’t explain, the article smells human and I don’t use the word smell as a bad thing.
It gives me some relief to know there are others out there who struggle with some similar issues, but I was hoping the piece may offer some guidance, but sadly I do not feel it has.
I think using 'bottleneck' to describe a process that isn't amenable to automation frames the situation incorrectly in my head. 'positive bottleneck' isn't any help.
Reminds me of a time someone asked an influencer how to write better blog posts with LLMs. They responded "oh, it's easy", and then crafted a very specific and niche prompt about comparing and contrasting very specific things with technical details they clearly had deep knowledge in.
Yes... imagine...
Tell me you've got little empathy for the autist mind without telling me...
I laughed out loud when I read this paragraph. There are so many "consciousness" or "memory" or "learning" AI bullshit startups right now...all of them not understanding how positional encoding of LLMs work. It's getting so ridiculous that I don't even understand why they're in the (uncurated) news everywhere.
It's like everyone tries it out, and writes without any journalistic integrity because it's a sponsored article that costs 100$, and moves on. Spamming as a bought in service or something. It doesn't make sense to me, and I have no clue how broken the economics of this must be to get into the state of "AI news" we are in right now. Excuse my French, but something must be utterly broken.
AI is just better in a fundamental way vs human intelligence. It can be reproduced infinitely, has perfect logging, no mental illnesses/hangups over certain things, far faster, able to ingest more kinds of data, etc. The only limitation now is a lack of intuitive in-context learning during test time, but once that final bottleneck falls then humans will have nothing valuable comparatively.