7 ms·

AI's real superpower: consuming, not creating

253 points by firefoxd 10mo ago

deleted 10mo ago
[deleted]
ratdragon 10mo ago
I do use such an approach and it is actually awesome however only for data I'm sure I don't mind being sold.
monkeydust 10mo ago
This is akin to using AI as a 'second brain', just getting started with Obsidian, my main challenge is loading it up with every communication trace I have...but haven't given up.
neom 10mo ago
A guy I work with has been doing this, I watched his tutorial and it was all a bit... overwhelming for me (to think about using such a system), I'm still on pen and paper, heh. Nevertheless - here is his template: https://github.com/kmikeym/obsidian-claude-starter https://github.com/kmikeym/obsidian-claude-starter and tutorial: https://www.youtube.com/watch?v=1U32hZYxfcY https://www.youtube.com/watch?v=1U32hZYxfcY
- jennyholzer2 10mo ago
  [flagged]
  - kmikeym 10mo ago
    i happen to know he takes vyvanse, which is kind of the same thing
impendia 10mo ago
I was in a research math lecture the other day, and the speaker used some obscure technical terminology I didn't know. So I dug out my phone and googled it. The AI summary at the top was surprisingly good! Of course, the AI isn't doing anything original; instead, it created a summary of whatever written material is already out there. Which is exactly what I wanted.
- Arisaka1 10mo ago
  My counterpoint to this is, if someone cannot verify the validity of the summary then is it truly a summary? And what would the end result be if the vast majority of people opted to adopt or deny a position based on the summary written by a third party? This isn't strictly a case against AI, just a case that we have a contradiction on the definition of "well informed". We value over-consumption, to the point where we see learning 3 things in 5 minutes as better than learning 1 thing in 5 minutes, even if that means being fully unable to defend or counterpoint what we just read. I'm speficially referring to what you said: "the speaker used some obscure technical terminology I didn't know" this is due to lack of assumed background knowledge, which makes it hard to verify a summary on your own.
  - lazide 10mo ago
    The issue is even deeper - the 1 thing in 5 minutes was probably already surface knowledge. We don’t usually really ‘know’ the thing that quickly. But we might have a chance. The 3 things in 5 minutes is even worse - it’s like taking Google Maps everywhere without even thinking about how to get from point A to point B - the odds of knowing anything at all from that are near zero. And since it summarizes the original content, it’s an even bigger issue - we never even have contact with the thing we’re putatively learning from, so it’s even harder to tell bullshit from reality. It’s like we never even drove the directions Google Maps was giving us. We’re going to end up with a huge number of extremely disconnected and useless people, who all absolutely insist they know things and can do stuff. :s
  - gosub100 10mo ago
    At least with pre-AI search, the info is provided with a source. So there is a small level of reputation that can be considered. With AI, it's a black box that someone decides what to train it on, and as someone said elsewhere, there's no way to police its sources. To get the best results, you have to turn it loose on everything. So someone who wants a war or wants Tweedledum to get more votes than Tweedledee has incentives to poison the well and disseminate fake content that makes it into the training set. Then there's a whole department of "safety" that has to manually untrain it to not be politically incorrect, racist etc. Because the whole thesis is don't think for yourself, let the AI think for you.
pqs 10mo ago
This is the right approach. I exported my 25k Evernote notes to markdown (I'm using Emacs' Howm mode) and I use Codex CLI to ask questions about my notes. It is great and powerful!
mettamage 10mo ago
Sorry, is this new? Providing the right data to LLMs supercharges them. Yes, I agree. I've been doing this since March 2025 when there was a blog post about using MCP on HN. I'm not the only one who's doing that. I've written my whole lifestory, the parts I'm willing to share that is, and posted it in Claude. It helped me way better with all kinds of things. It took me 2 days to write without formatting, pretty much how I write all my HN comments (but then 2 days straight: eat, sleep, write). I've also exported all my notes, but it's too big for the context. That's why I wrote my life story. From a practical standpoint I think the focus is on context management. Obsidian can help with this (I haven't used it so don't know the details). For code, it means doing things like static and dynamic analysis to see which functions calls what and create a topology of function calls and send that as context, then Claude Code can more easily know what to edit, and it doesn't need to read all the code.
- TN1ck 10mo ago
  Curious, what did you get out of it? Counseling? Some action plan? A reflection? Seems intriguing to do, but would like to know how it helped you exactly if you don’t mind sharing.
  - mettamage 10mo ago
    Career planning at the moment, tailoring resumes. Currently, it's not tailoring it well enough yet because it's hallucinating too much, so I need to write a specific prompt for that. But I know for work, where I do similar things (text generation with a human in the loop), that I can tackle that problem. So yea, I definitely, add to the "AI generated" text part but I read over all the texts, and usually they don't get sent out. Ultimately, it's still a lot quicker to do it this way. For career planning, so far it hasn't beaten my own insights but it came close. For example, it mentioned that I should actually be a developer advocate instead of a software engineer. 2 to 3 years ago I came to that same thought. I ultimately rejected the idea due to how I am but it is a good one to think about. What I see now, I think the best job for me would be a tech consultant. Or as I'd also like to call it: a data analyst that spots problems and then uses his software engineering or teaching skills to solve that problem. I don't think that job has a good catch all title as it is a pretty generalist job. I'm currently at a company that allows me to do this but the pay is quite low, so I'm looking for a tech company where I could do something similar. Maybe a product manager role? It really depends on the company culture. What I also noticed it did better: it doesn't reduce me to data engineering anymore. It understands that I aspire to learn everything and anything I can get my hands on. It's my mode of living and Claude understands that. So nothing too spectacular yet, but it'll come. It requires more prompt/context engineering and fine tuning of certain things. I didn't get around to it yet.
tigranbs 10mo ago
I would say the AI consumption aspect was a side effect: the primary goal was to "generate" new stuff. So far, to me, the significant boost is the coding aspect. Still, for the rest of the people, I think you are right: 90% of the benefits come from being an interactive, conversational search on top of the available information that AI can read/consume.
tomgag 10mo ago
For fuck's sake, isn't anyone here horrified at how much information on yourself you are willingly funneling into Big Tech with this approach?
- ramigb 10mo ago
  It is scary! my coping mechanism, which I admit is stupid, is to believe no matter what I do as long as I am online they have my data. But you are right most people just give absurd amount of data for willingly.
  - SoftTalker 10mo ago
    Not stupid at all. Nothing you do online should be considered private.
- gosub100 10mo ago
  And the surveillance could be inversely correlated to profitability. If they pour billions into these chat bots and can't monetize them to the revolutionary oracles they touted, one minor consolation is to sell detailed profiles about the people using them. You could probably sort out the less intelligent people based on what they were asking.
- sirsau 10mo ago
  How would this affect my life in any way? Better ads for me? More useful searches? I really don't get this obsession with privacy.
sallveburrpi 10mo ago
Anyone has a simple setup for this with local LLMs like Mistral that they can share? I would love to try this out but don’t feel comfortable sharing all my personal notes with a third party.
purplehat_ 10mo ago
I often see things like this and get a little bit of FOMO because I'd love to see what I can get out of this but I'm just not willing to upload all these private documents of mine to other people's computers where they're likely to be stored for training or advertising purposes. How are you guys dealing with this risk? I'm sure on this site nobody is naive to the potential harms of tech, but if you're able to articulate how you've figured out that the risk is worth the benefits to you I'd love to hear it. I don't think I'm being to cynical to wait for either local LLMs to get good or for me to be able to afford expensive GPUs for current local LLMs, but maybe I should be time-discounting a bit harder? I'm happy to elaborate on why I find it dangerous, too, if this is too vague. Just really would like to have a more nuanced opinion here.
- ben_w 10mo ago
  The docs I upload are ones I'd be OK getting leaked. That also includes code. Even more broadly, it also includes whatever pics I put onto social media, including chat groups like Telegram. This does mean that, useful as e.g. Claude Code is, for any business with NDA-type obligations, I don't think I could recommend it over a locally hosted model, even though the machine needed to run a decent local model might cost €10k (with current price increases due to demand exceeding supply), that the machine is still slower than what hosts the hosted models, that the rapid rate of improvement means a 3-month delay between SOTA in open-weights and private-weights is enough to matter*. But until then? If I'm vibe coding a video game I'd give away for free anyway, or copy-editing a blog post that's public anyway, or using it to help with some short stories that I'd never be able to charge money for, or uploading pictures of the plants in my garden right by the public road… that's fine. * When the music (money for training) stops, it could be just about any provider whose model is best, whatever that is is likely to still get distilled down fairly cheaply and/or some 3-month-old open-weights model is likely to get fine-tuned for each task fairly cheaply; independently of this, without the hyper-scalers the supply chains may shift back from DCs to PCs and make local models much more affordable.
  - JonChesterfield 10mo ago
    > The docs I upload are ones I'd be OK getting leaked. That also includes code. That's fortunate as uploading them to a LLM was you leaking them.
skydhash 10mo ago
The article is more about offloading your thinking to the machine than a real usage of what notes is. You may as well make every decision rely on a coin toss. I take notes for remembrance and relevance (what is interesting for me). But linking concepts is all my thinking. Doing whatever rhe article is prescribing is like sending someone on a tourist trip to take pictures and then bragging that you visited the country. While knowing that some pictures are photoshopped.
- bzmrgonz 10mo ago
  I disagree, what ai brings to thr table is instant and total recall of our thoughts/notes/experiences. Deep analysis of that vast data storage is only possible via ai, which should trigger the aha!!! Moment, or the "you're crazy ai" moment. Either way, it's very useful. And we haven't even talked about the knowl she we have collecting digital dust in emails, and notes and reports of past employees.
  - skydhash 10mo ago
    There's a lot more dimension to the notes we take than what is actually written down. You can share your notes to other people and their interpretation would be very different to what you intended. It even happens with full books and articles. Even lots of metadata don't really help. Text is a very linear medium. It's just the spark while our wealth of experiences is the fuel. No amount of wrangling the word "pain" will compare to actually experiencing it. You'll better be served by just having a space repetition system for the notes you've taken. In this way, you'll be reminded of the whole experience when you took the note instead of reading words that were never written by someone who have lived.
  - skdhshdd 10mo ago
    [dead]
  - rsynnott 10mo ago
    Hrm. Pretty much every LLM summary I've seen of a document I've read, or a meeting I've attended, at absolute best misses important details and overemphasises trivia, and often just flat-out makes stuff up. I'm not sure I want my own _thoughts_ filtered through that.
bzmrgonz 10mo ago
If we pair this with a wearable ai pendant like plaid or limitless, we can increase the amount and frequency of depositing into our knowledge vault. Op, do you type your thoughts and notes or dictate them?
kitd 10mo ago
At least half of AI's "superpower" in OP's case is the fact that he has everything in Obsidian already. With all of that background context, any tool becomes super valuable in evaluating & guiding future actions. Still, all credit to him for creating that asset in the first place.
- SoftTalker 10mo ago
  Pretty much my reaction too. I'd guess maybe 1 in 100 people are that diligent about journaling. Good for him that he is getting a payoff for his effort.
ramigb 10mo ago
I found that out while working with music models like Suno! I love creating music for my own listening experience as a hobbyist and when I give suno a prompt no matter how well crafted it is the outcome varies from "meh" to "that's good" ... while when I upload semi finished beat I made and prompt it to cover it the results consistently leave me speechless! Could be a bias since the music has a lot of elements I created but this workflow is similar across other generative models for me.
nnnnico 10mo ago
What is the approach used? It seems everything gets done in context by plain text searches with some agent like Claude code or is there RAG involved? (was the article written by AI? it has that LinkedIn-groove all over the place)
adidoit 10mo ago
Ironically this article/blog itself is giving off an AI-generated smell as it's tone and cadence seem very similar to LinkedIn posts or rather output of prompts to create LinkedIn posts.
deleted 10mo ago
[deleted]
fuzzfactor 10mo ago
>real superpower: consuming, not creating Well for most humans that's the more super of the powers too ;)
heliumtera 10mo ago
Not really surprising that a tool created for surveillance and mass profiling turned out to be pretty good at surveiling and profiling
- embedding-shape 10mo ago
  Is this like your belief? Transformers et al were invented by researchers with the explicit goal of surveillance and mass profiling? You think maybe that could have been an unintended effect of something/someone else? Or it's all the researchers fault?
  - heliumtera 10mo ago
    i do not believe transformers were created by independent and autonomous researchers. will not blame individuals, no. but yeah, pretty much, I maintain the original point. if the question is what are the incentives in place and funding mechanisms to pursue such technology...surveillance and mass profiling. 'we want to serve YOU as well as we can, and we want to know what YOU stands for' kind of profiling and surveillance, not necessarily the all knowing god government kind.
    - embedding-shape 10mo ago
      ... Who do you believe invented Transformers then? Not the authors of the paper? What leads you to believe so? I'm genuinely curious, as I've never heard someone claim this before, and would be very interested in hearing how you ended up with these ideas.
bdbdbdb 10mo ago
> No human could read all of this in a lifetime. AI consumes it in seconds. And therefore it's impossible to test the accuracy if it's consuming your own data. AI can hallucinate on any data you feed it, and it's been proven that it doesn't summarize, but rather abridges and abbreviates data. In the authors example > "What patterns emerge from my last 50 one-on-ones?" AI found that performance issues always preceded tool complaints by 2-3 weeks. I'd never connected those dots. Maybe that's a pattern from 50 one-on-ones. Or maybe it's only in the first two and the last one. I'd be wary of using AI to summarize like this and expecting accurate insights
- gchamonlive 10mo ago
  > it's been proven that it doesn't summarize, but rather abridges and abbreviates data Do you have more resources on that? I'd love to read about the methodology. > And therefore it's impossible to test the accuracy if it's consuming your own data. Isn't it only if it's hard to verify the result? If it's a result that's hard to produce but easy to verify, a class which many problems fall into, you'd just need to look at the synthetized results. If you ask it "given these arbitrary metrics, what is the best business plan for my company?" It'd be really hard to verify the result. I'd be hard to verify the result from anyone for that matter, even specialists. So I think it's less about expecting the LLM to do autonomous work and more about using LLMs to more efficiently help you search the latent space for interesting correlations, so that you and not the LLM come up with the insights.
  - bdbdbdb 10mo ago
    > If you ask it "given these arbitrary metrics, what is the best business plan for my company?" It'd be really hard to verify the result. I'd be hard to verify the result from anyone for that matter, even specialists. Hard to verify something so subjective, for sure. But a specialist will be applying intelligence to the data. An LLM is just generating random text strings that sound good. The source for my claim about LLMs not summarizing but abbreviating is on hn somewhere, I'll dig it out Edit: sorry, I tried but couldn't find the source.
    - 10mo ago
ozgung 10mo ago
What is a good way of connecting Obsidian vault to AI?
G_o_D 10mo ago
Thats why proofreading jobs still exist
Lerc 10mo ago
I think this will be a significant thing in the future, but right now I think the reasoning abilities are too limited. It can reasonably approximate a vector database where it can find related things, but I think that success can hide the failure to find important things. I'd like to be able to point a model at a news story and have it follow every fact and claim back to an origin, (or lack of one). I'm not sure when they will be able to do that, they aren't up to the task yet. Reading the news would be so much different if you could separate the 'we report this happened' from the 'we report that someone else reported this happened"
ericlamb89 10mo ago
Agree with OP that LLMs are a great tool for this use case. It's made possible because OP diligently created useful input data. Unfortunately OP's conclusion goes against the AI hype machine. If "consuming" is the "superpower" of AI, then the current level of investment/attention would not be justified.
zkmon 10mo ago
I don't see what's new here. The biggest enterprise usecase for AI is to "consume" the vast amount of internal wiki pages, process documents, policy manuals, code repos, presentations and be able to answer questions.
johndhi 10mo ago
Can you share some prompt examples you use to try to ensure it doesn't get "lazy" and just cherry pick from here and there? I have a written novel draft and something like a million words of draft fiction but have struggled with how to get meaningful analytics from it.
achenet 10mo ago
So I decided to give this a try - I have a `writing` directory/git repo where I store most of my writing, which can be anything from notes on technical subjects (list of useful syntax for a given programming language), to letters to friends, to philosophical ramblings. I opened Claude Code in the repo and asked it to tell me about myself based on my writing. Claude's answer overestimated my technical skills (I take notes on stuff I don't know, not on things I know, so it assumed that I had deep expertise in things I'm currently learning, and ignored areas where I do have a fair amount of experience), but the personal side really resonated with me.
n49o7 10mo ago
Compound the gains again by asking AI to write the questions too!
fsckboy 10mo ago
AI's consumption superpower reminds me of birds, flying about eating worms, then flying back to the nest and regurgitating them into baby's mouth, because it's the processed nutrition they provide that valuable; their own consumption is a combination of fractional/temporary
- TimByte 10mo ago
  I think the key difference (and risk) is that with AI we sometimes forget to check what got digested and what got lost along the way
- stuffn 10mo ago
  "AI" is more like a bird that flies around eating worms, sometimes regurgitates the nutrition, and sometimes regurgitates a pound of bolts. Then it apologizes, flies around again, and regurgitates pebbles. It does it again but this time it regurgitates acid that vaguely appears to be the same nutritious substance. If it flies around too much it will lose it's context and begin to think it's not a bird but rather a donkey. Most of "AI"s superpower is tricking monkeys into anthropomorphizing it. It's just a giant, complicated, expensive, environmentally destructive math computer with no capability to create novel thought. If it did have one superpower it's gaslighting and manipulation.
alexgotoi 10mo ago
Models are mediocre solo consumers: they skim, paraphrase and confidently miss the one subtle thing that actually matters. Humans are still better at deciding which three paragraphs in a 40‑page spec are load‑bearing. But as soon as you treat the model as a stochastic code monkey with a compiler, test suite, linter and some static tooling strapped to its back, it suddenly looks a lot more like “creation with a very fast feedback loop” than “consumption at scale”. The interesting leverage isn’t that AI can read more stuff than you; it’s that you can cheaply instrument your system (tests, properties, contracts, little spec fragments) and then let the model grind through iterations until something passes all of that. That just shifts the hard work back where it’s always been: choosing what to assert about the world. The tokens and the code are the easy part now. This might make it into this week's https://hackernewsai.com/ https://hackernewsai.com/ newsletter.
- _DeadFred_ 10mo ago
  Don't forget guardrails and other tweaks you don't know are being applied. I was exploring energy usage and when I reached solar energy somehow the AI decided it was political and switched to useless mode until I explicitly told it to look back at the conversation and it's context and that I wasn't trying to get it to say solar was good and it was OK if numbers made solar look good. I was really weird.
  - wyre 10mo ago
    Which model were you using?
    - dehugger 10mo ago
      sounds like grok...
- mistrial9 10mo ago
  .. except you are completely wrong in a certain way.. AFAIK Google has been reading and indexing patent applications and maybe SEC filings since before word2vec. Certain niches absolutely are reading documents faster than your attorneys can...
ge96 10mo ago
Wrt temperature/randomization is it not possible for it to create something genuine. Even life there seems to always be some inspiration for things being made. How did Tesla go from Brushed to Brushless AC motors. There was some foundational knowledge of electricity similar to airplanes, the Wright Brothers their airplane seems backwards (like a canard) but still a plane/needs wings. Not something radical like ion engines for lift (much harder).
Ove_K 10mo ago
Digital Information Consumers or Digital Information Copiers or Digital Information Creators Either way, they are D.I.C.s
TimByte 10mo ago
This approach feels like a much more honest use
acituan 10mo ago
We know from the era of data the power of JOIN. Bring in two different data sources about a thing and you could produce an insight neither of them could have provided alone. LLMs can be thought as one big stochastic JOIN. The new insight capabilities - thanks to their massive recall - is there. The problem is the stochasticity. They can retrieve stuff from the depths and slap them together but in these use cases we have no clue how relevant their inner ranking results or intermediary representations were. Even with the best read of user intent they can only simulate relevance, not really compute it in a grounded and groundable way. So I take such automatic insight generation tasks with a massive grain of salt. Their simulation is amusing and feels relevant but so does a fortune teller doing a mostly cold read with some facts sprinkled in. > → I solve problems faster by finding similar past situations → I make better decisions by accessing forgotten context → I see patterns that were invisible when scattered across time All of which makes me skeptical of this claim. I have no doubt they feel productive but it might just as well be a part of that simulation, with all the biases, blind spots etc originating from the machine. Which could be worse than not having used the tool. Not having augmented recall is OK, forgetting things are OK - because memory is not a passive reservoir of data but an active reranker of relevance. LLMs can’t be the final source of insight and wisdom, they are at best sophists, or as Terrence Tao put it more kindly, a mere source of cleverness. In this, they can just as well augment our self-deception capacity, maybe even more than counterbalancing them. Exercise: whatever amusing insight a machine produces for you, ask for a very strong counter to it. You might be equally amused.
catigula 10mo ago
How many times have the goal-posts shifted now? Everyone is justifiably afraid of AI because it's pretty obvious that Claude Opus 4.5 level agents replace developers.
- emp17344 10mo ago
  This isn’t goalpost shifting - everyone is trying to figure out what AI is good at. It’s certainly not the panacea many here make it out to be.
  - catigula 10mo ago
    We know what it's good at - software engineering.
- mrmansano 10mo ago
  > it's pretty obvious that Claude Opus 4.5 level agents replace developers. Is it though? I really don't see it. Replacing developers requires way more than writing the right code. I can agree it can replace junior to mid level engineers at some tasks, specifically in greenfield projects and popular stacks. And, don't get me wrong, it's very helpful even for senior engineers. But to "replace" those it will require some new iterations of "Opus 4.5".
  - catigula 10mo ago
    I'm going to be honest because I have nothing to lose; I've never in my entire life met a single senior engineer that can surpass Opus generally. Some can surpass it at problem solving but they aren't common.
mattsears 10mo ago
Yay, another HN post confidently claiming "everyone’s doing X wrong." "Everyone’s using AI wrong." Oh, we are? Please, enlightened us thought leader, tell us how we’ve all been doing it wrong this entire time. "Here’s how most people use AI." No, that’s how you use AI. Can we stop projecting our own habits onto the whole world and calling it insight?
wyre 10mo ago
I think it's ability to consume information is one of the scarier aspects of AI. NSA, other government, and multi-national corporations have years of our individual browsing and consumption patterns. What happens when AI is analyzing all of that information exponentially faster than any human code and communicating with relevant parties for their own benefit, to predict or manipulate behavior, build psychological profiles, identify vulnerabilities, etc. It's incredibly amusing to me reading some people's comments here critical of AI, that if you didn't know any better, might make you think that AI is a worthless technology.
- Liquix 10mo ago
  > What happens when AI is analyzing all of that information... They run simulations against N million personality models, accurately predicting the outcome of any news story/event/stimulus. They use this power to shape national and global events to their own ends. This is what privacy and digital sovereignty advocates have been warning the public about for over a decade, to no avail.
  - seg_lol 10mo ago
    This is much worse than overt authoritarian control, because the controlled aren't even aware of it.
    - wordpad 10mo ago
      I don't know how viable it is. Even for AI, there are just too many intermingled variables when it comes to human behavior. All the money in the world has been invested into trying to do it with stock markets, and they still can't do better than average.
    - hvb2 10mo ago
      You should watch the matrix, especially the first 3
- macNchz 10mo ago
  All hype and thought experiments about superintelligence and open questions about creativity and learning and IP aside, this is the area that gives me the biggest pause. We've effectively created a panopticon in recent years—there are cameras absolutely everywhere. Despite that, though, the effort to actually do something with all of those feeds has provided a sort of natural barrier to overreach: it'd be effectively impossible to have people constantly watching all of the millions of camera feeds available in a modern city and flagging things, but AI certainly could. Right now the compute for that is a barrier, but it would surprise me if we don't see cameras (which currently offer a variety of fairly basic computer vision "AI" alerting features for motion and object detection) coming with free-text prompts to trigger alerts. "Alert me if you see a red Nissan drive past the house.", "Alert me if you see a neighbor letting his dog poop in my yard.", "Alert the police if you see crime taking place [default on, opt out required]."
exasperaited 10mo ago
AI-powered solipsistic reassurance?
vignesh-prasad 10mo ago
This is a really cool insight. I'm going to try this in my Obsidian vault as well. What are some of the highest leverage items to add to your vault to start with? I think meetings is one thing I'm missing out on. How do you put meeting information into your Obsidian? Is it just transcripts?
rikroots 10mo ago
I'm wary about using AI models to generate stuff for me - I still bristle from the time a model told me that "JS Sets are faster than Arrays" and I believed it, until I discovered that it forgot to add the important piece of information: for Arrays containing tens of thousands of elements. Which made me feel stupid. Still, I find the models to be excellent synthesisers of vast quantities of data on subjects in which I have minimal prior knowledge. For instance, when I wanted to translate some Lorca and Cavafy poems into English I discovered that ChatGPT had excellent knowledge of the poems in their native languages, and the difficulties translators faced when rendering them into English. Once I was able to harness the models to assist me translate a poem, rather than generate a translation for me (every LLM is convinced it's a Poet), I managed to write some reasonable poems that met my personal requirements. I wrote about the experience here: https://rikverse2020.rikweb.org.uk/blog/adventures-in-poetry-translation https://rikverse2020.rikweb.org.uk/blog/adventures-in-poetry...
roadside_picnic 10mo ago
AI's real super power is telling you what you want to hear (doubly true since RLHF became the standard). You can really see the limitations of LLMs when you look at how poorly they do at summarization. They most often just extract a few key quotes from the text, and provide an abbreviated version of the original text (often missing key parts!) Abbreviation is not summarization. To properly summarized you need to be able to understand higher level abstractions implied in the text. At a fundamental level this is not what LLMs are designed to do. They can interpolate and continue existing text in remarkable and powerful ways, but they aren't capable of getting the "big picture". This is likely related to why they frequently ignore very important passages when "summarizing". > We're still thinking about AI like it's 2023. Just a reminder that in 2023 we were all told that AI was on a path of exponential progress. Were this true, you wouldn't need to argue that we're using it "wrong" because the technology would have improved dramatically more than it did from 2021-2023 such that there would be no need to argue that its better, using it "wrong" would still be a massive improvement.
1vuio0pswjnm7 10mo ago
Perhaps the power of "collecting" is even greater than "consuming" For example, collecting the thoughts, questions, aspirations, etc. of "AI" users. Much of this appears to be personal or confidential hence the recent OpenAI anouncement about turning over "private chats" to plaintiffs' counsel in copyright infringement litigation https://sites.google.com/view/elizaarchaeology/blog/3-weizenbaums-secretary https://sites.google.com/view/elizaarchaeology/blog/3-weizen... The original "AI chatbot" from the 1960's, "ELIZA", was not "trained on" (it did not consume) much data at all in today's terms. Yet it could solicit larger amounts of data from users who anthropomorphised the computer If data collection is a goal, as it is with today's Silicon Valley companies, then this is arguably a very effective hack The "AI" only needs to seem realistic to such individuals
ricksunny 10mo ago
Anyone have an idea which AI tool the author is using to consume his Obsidian repository?
hashstring 10mo ago
> Everything goes into Obsidian (meetings, thoughts, reflections) > AI has access to the entire vault Yes, consumption. Also consider who or what you are feeding too.
ezoi_MuUJd 10mo ago
Buscar porno en tu casa Y luego trabajo debset Te puede beneficiar en En tu casa, tu deuda
ensocode 10mo ago
I’m impressed, but honestly: I don’t document enough to get real value from an AI consuming my stuff. To make this useful, I’d either need a brain interface that logs my thoughts, or I’d have to speech-to-text everything I say throughout the day. Only then could an AI reasonably help connect dots or answer questions like: “What should I focus on next week?”
davegri 10mo ago
Lol the irony is that this was obviously written using AI "Last month I connected my Obsidian vault to AI. The questions changed completely: Instead of "Write me something new" I ask "What have I already discovered?"" yep
jppaoli 10mo ago
[dead]

253 points by firefoxd 10mo ago

deleted 10mo ago

[deleted]

ratdragon 10mo ago

I do use such an approach and it is actually awesome however only for data I'm sure I don't mind being sold.

monkeydust 10mo ago

This is akin to using AI as a 'second brain', just getting started with Obsidian, my main challenge is loading it up with every communication trace I have...but haven't given up.

neom 10mo ago

A guy I work with has been doing this, I watched his tutorial and it was all a bit... overwhelming for me (to think about using such a system), I'm still on pen and paper, heh. Nevertheless - here is his template: https://github.com/kmikeym/obsidian-claude-starter https://github.com/kmikeym/obsidian-claude-starter and tutorial: https://www.youtube.com/watch?v=1U32hZYxfcY https://www.youtube.com/watch?v=1U32hZYxfcY

jennyholzer2 10mo ago
[flagged]
- kmikeym 10mo ago
  i happen to know he takes vyvanse, which is kind of the same thing

impendia 10mo ago

I was in a research math lecture the other day, and the speaker used some obscure technical terminology I didn't know. So I dug out my phone and googled it. The AI summary at the top was surprisingly good! Of course, the AI isn't doing anything original; instead, it created a summary of whatever written material is already out there. Which is exactly what I wanted.

Arisaka1 10mo ago
My counterpoint to this is, if someone cannot verify the validity of the summary then is it truly a summary? And what would the end result be if the vast majority of people opted to adopt or deny a position based on the summary written by a third party? This isn't strictly a case against AI, just a case that we have a contradiction on the definition of "well informed". We value over-consumption, to the point where we see learning 3 things in 5 minutes as better than learning 1 thing in 5 minutes, even if that means being fully unable to defend or counterpoint what we just read. I'm speficially referring to what you said: "the speaker used some obscure technical terminology I didn't know" this is due to lack of assumed background knowledge, which makes it hard to verify a summary on your own.
- lazide 10mo ago
  The issue is even deeper - the 1 thing in 5 minutes was probably already surface knowledge. We don’t usually really ‘know’ the thing that quickly. But we might have a chance. The 3 things in 5 minutes is even worse - it’s like taking Google Maps everywhere without even thinking about how to get from point A to point B - the odds of knowing anything at all from that are near zero. And since it summarizes the original content, it’s an even bigger issue - we never even have contact with the thing we’re putatively learning from, so it’s even harder to tell bullshit from reality. It’s like we never even drove the directions Google Maps was giving us. We’re going to end up with a huge number of extremely disconnected and useless people, who all absolutely insist they know things and can do stuff. :s
- gosub100 10mo ago
  At least with pre-AI search, the info is provided with a source. So there is a small level of reputation that can be considered. With AI, it's a black box that someone decides what to train it on, and as someone said elsewhere, there's no way to police its sources. To get the best results, you have to turn it loose on everything. So someone who wants a war or wants Tweedledum to get more votes than Tweedledee has incentives to poison the well and disseminate fake content that makes it into the training set. Then there's a whole department of "safety" that has to manually untrain it to not be politically incorrect, racist etc. Because the whole thesis is don't think for yourself, let the AI think for you.

pqs 10mo ago

This is the right approach. I exported my 25k Evernote notes to markdown (I'm using Emacs' Howm mode) and I use Codex CLI to ask questions about my notes. It is great and powerful!

mettamage 10mo ago

Sorry, is this new? Providing the right data to LLMs supercharges them. Yes, I agree. I've been doing this since March 2025 when there was a blog post about using MCP on HN. I'm not the only one who's doing that. I've written my whole lifestory, the parts I'm willing to share that is, and posted it in Claude. It helped me way better with all kinds of things. It took me 2 days to write without formatting, pretty much how I write all my HN comments (but then 2 days straight: eat, sleep, write). I've also exported all my notes, but it's too big for the context. That's why I wrote my life story. From a practical standpoint I think the focus is on context management. Obsidian can help with this (I haven't used it so don't know the details). For code, it means doing things like static and dynamic analysis to see which functions calls what and create a topology of function calls and send that as context, then Claude Code can more easily know what to edit, and it doesn't need to read all the code.

TN1ck 10mo ago
Curious, what did you get out of it? Counseling? Some action plan? A reflection? Seems intriguing to do, but would like to know how it helped you exactly if you don’t mind sharing.
- mettamage 10mo ago
  Career planning at the moment, tailoring resumes. Currently, it's not tailoring it well enough yet because it's hallucinating too much, so I need to write a specific prompt for that. But I know for work, where I do similar things (text generation with a human in the loop), that I can tackle that problem. So yea, I definitely, add to the "AI generated" text part but I read over all the texts, and usually they don't get sent out. Ultimately, it's still a lot quicker to do it this way. For career planning, so far it hasn't beaten my own insights but it came close. For example, it mentioned that I should actually be a developer advocate instead of a software engineer. 2 to 3 years ago I came to that same thought. I ultimately rejected the idea due to how I am but it is a good one to think about. What I see now, I think the best job for me would be a tech consultant. Or as I'd also like to call it: a data analyst that spots problems and then uses his software engineering or teaching skills to solve that problem. I don't think that job has a good catch all title as it is a pretty generalist job. I'm currently at a company that allows me to do this but the pay is quite low, so I'm looking for a tech company where I could do something similar. Maybe a product manager role? It really depends on the company culture. What I also noticed it did better: it doesn't reduce me to data engineering anymore. It understands that I aspire to learn everything and anything I can get my hands on. It's my mode of living and Claude understands that. So nothing too spectacular yet, but it'll come. It requires more prompt/context engineering and fine tuning of certain things. I didn't get around to it yet.

tigranbs 10mo ago

I would say the AI consumption aspect was a side effect: the primary goal was to "generate" new stuff. So far, to me, the significant boost is the coding aspect. Still, for the rest of the people, I think you are right: 90% of the benefits come from being an interactive, conversational search on top of the available information that AI can read/consume.

tomgag 10mo ago

For fuck's sake, isn't anyone here horrified at how much information on yourself you are willingly funneling into Big Tech with this approach?

ramigb 10mo ago
It is scary! my coping mechanism, which I admit is stupid, is to believe no matter what I do as long as I am online they have my data. But you are right most people just give absurd amount of data for willingly.
- SoftTalker 10mo ago
  Not stupid at all. Nothing you do online should be considered private.
gosub100 10mo ago
And the surveillance could be inversely correlated to profitability. If they pour billions into these chat bots and can't monetize them to the revolutionary oracles they touted, one minor consolation is to sell detailed profiles about the people using them. You could probably sort out the less intelligent people based on what they were asking.
sirsau 10mo ago
How would this affect my life in any way? Better ads for me? More useful searches? I really don't get this obsession with privacy.

sallveburrpi 10mo ago

Anyone has a simple setup for this with local LLMs like Mistral that they can share? I would love to try this out but don’t feel comfortable sharing all my personal notes with a third party.

purplehat_ 10mo ago

I often see things like this and get a little bit of FOMO because I'd love to see what I can get out of this but I'm just not willing to upload all these private documents of mine to other people's computers where they're likely to be stored for training or advertising purposes. How are you guys dealing with this risk? I'm sure on this site nobody is naive to the potential harms of tech, but if you're able to articulate how you've figured out that the risk is worth the benefits to you I'd love to hear it. I don't think I'm being to cynical to wait for either local LLMs to get good or for me to be able to afford expensive GPUs for current local LLMs, but maybe I should be time-discounting a bit harder? I'm happy to elaborate on why I find it dangerous, too, if this is too vague. Just really would like to have a more nuanced opinion here.

ben_w 10mo ago
The docs I upload are ones I'd be OK getting leaked. That also includes code. Even more broadly, it also includes whatever pics I put onto social media, including chat groups like Telegram. This does mean that, useful as e.g. Claude Code is, for any business with NDA-type obligations, I don't think I could recommend it over a locally hosted model, even though the machine needed to run a decent local model might cost €10k (with current price increases due to demand exceeding supply), that the machine is still slower than what hosts the hosted models, that the rapid rate of improvement means a 3-month delay between SOTA in open-weights and private-weights is enough to matter*. But until then? If I'm vibe coding a video game I'd give away for free anyway, or copy-editing a blog post that's public anyway, or using it to help with some short stories that I'd never be able to charge money for, or uploading pictures of the plants in my garden right by the public road… that's fine. * When the music (money for training) stops, it could be just about any provider whose model is best, whatever that is is likely to still get distilled down fairly cheaply and/or some 3-month-old open-weights model is likely to get fine-tuned for each task fairly cheaply; independently of this, without the hyper-scalers the supply chains may shift back from DCs to PCs and make local models much more affordable.
- JonChesterfield 10mo ago
  > The docs I upload are ones I'd be OK getting leaked. That also includes code. That's fortunate as uploading them to a LLM was you leaking them.

skydhash 10mo ago

The article is more about offloading your thinking to the machine than a real usage of what notes is. You may as well make every decision rely on a coin toss. I take notes for remembrance and relevance (what is interesting for me). But linking concepts is all my thinking. Doing whatever rhe article is prescribing is like sending someone on a tourist trip to take pictures and then bragging that you visited the country. While knowing that some pictures are photoshopped.

bzmrgonz 10mo ago
I disagree, what ai brings to thr table is instant and total recall of our thoughts/notes/experiences. Deep analysis of that vast data storage is only possible via ai, which should trigger the aha!!! Moment, or the "you're crazy ai" moment. Either way, it's very useful. And we haven't even talked about the knowl she we have collecting digital dust in emails, and notes and reports of past employees.
- skydhash 10mo ago
  There's a lot more dimension to the notes we take than what is actually written down. You can share your notes to other people and their interpretation would be very different to what you intended. It even happens with full books and articles. Even lots of metadata don't really help. Text is a very linear medium. It's just the spark while our wealth of experiences is the fuel. No amount of wrangling the word "pain" will compare to actually experiencing it. You'll better be served by just having a space repetition system for the notes you've taken. In this way, you'll be reminded of the whole experience when you took the note instead of reading words that were never written by someone who have lived.
- skdhshdd 10mo ago
  [dead]
- rsynnott 10mo ago
  Hrm. Pretty much every LLM summary I've seen of a document I've read, or a meeting I've attended, at absolute best misses important details and overemphasises trivia, and often just flat-out makes stuff up. I'm not sure I want my own _thoughts_ filtered through that.

bzmrgonz 10mo ago

If we pair this with a wearable ai pendant like plaid or limitless, we can increase the amount and frequency of depositing into our knowledge vault. Op, do you type your thoughts and notes or dictate them?

kitd 10mo ago

At least half of AI's "superpower" in OP's case is the fact that he has everything in Obsidian already. With all of that background context, any tool becomes super valuable in evaluating & guiding future actions. Still, all credit to him for creating that asset in the first place.

SoftTalker 10mo ago
Pretty much my reaction too. I'd guess maybe 1 in 100 people are that diligent about journaling. Good for him that he is getting a payoff for his effort.

ramigb 10mo ago

I found that out while working with music models like Suno! I love creating music for my own listening experience as a hobbyist and when I give suno a prompt no matter how well crafted it is the outcome varies from "meh" to "that's good" ... while when I upload semi finished beat I made and prompt it to cover it the results consistently leave me speechless! Could be a bias since the music has a lot of elements I created but this workflow is similar across other generative models for me.

nnnnico 10mo ago

What is the approach used? It seems everything gets done in context by plain text searches with some agent like Claude code or is there RAG involved? (was the article written by AI? it has that LinkedIn-groove all over the place)

adidoit 10mo ago

Ironically this article/blog itself is giving off an AI-generated smell as it's tone and cadence seem very similar to LinkedIn posts or rather output of prompts to create LinkedIn posts.

deleted 10mo ago

[deleted]

fuzzfactor 10mo ago

>real superpower: consuming, not creating Well for most humans that's the more super of the powers too ;)

heliumtera 10mo ago

Not really surprising that a tool created for surveillance and mass profiling turned out to be pretty good at surveiling and profiling

embedding-shape 10mo ago
Is this like your belief? Transformers et al were invented by researchers with the explicit goal of surveillance and mass profiling? You think maybe that could have been an unintended effect of something/someone else? Or it's all the researchers fault?
- heliumtera 10mo ago
  i do not believe transformers were created by independent and autonomous researchers. will not blame individuals, no. but yeah, pretty much, I maintain the original point. if the question is what are the incentives in place and funding mechanisms to pursue such technology...surveillance and mass profiling. 'we want to serve YOU as well as we can, and we want to know what YOU stands for' kind of profiling and surveillance, not necessarily the all knowing god government kind.
  - embedding-shape 10mo ago
    ... Who do you believe invented Transformers then? Not the authors of the paper? What leads you to believe so? I'm genuinely curious, as I've never heard someone claim this before, and would be very interested in hearing how you ended up with these ideas.

bdbdbdb 10mo ago

> No human could read all of this in a lifetime. AI consumes it in seconds. And therefore it's impossible to test the accuracy if it's consuming your own data. AI can hallucinate on any data you feed it, and it's been proven that it doesn't summarize, but rather abridges and abbreviates data. In the authors example > "What patterns emerge from my last 50 one-on-ones?" AI found that performance issues always preceded tool complaints by 2-3 weeks. I'd never connected those dots. Maybe that's a pattern from 50 one-on-ones. Or maybe it's only in the first two and the last one. I'd be wary of using AI to summarize like this and expecting accurate insights

gchamonlive 10mo ago
> it's been proven that it doesn't summarize, but rather abridges and abbreviates data Do you have more resources on that? I'd love to read about the methodology. > And therefore it's impossible to test the accuracy if it's consuming your own data. Isn't it only if it's hard to verify the result? If it's a result that's hard to produce but easy to verify, a class which many problems fall into, you'd just need to look at the synthetized results. If you ask it "given these arbitrary metrics, what is the best business plan for my company?" It'd be really hard to verify the result. I'd be hard to verify the result from anyone for that matter, even specialists. So I think it's less about expecting the LLM to do autonomous work and more about using LLMs to more efficiently help you search the latent space for interesting correlations, so that you and not the LLM come up with the insights.
- bdbdbdb 10mo ago
  > If you ask it "given these arbitrary metrics, what is the best business plan for my company?" It'd be really hard to verify the result. I'd be hard to verify the result from anyone for that matter, even specialists. Hard to verify something so subjective, for sure. But a specialist will be applying intelligence to the data. An LLM is just generating random text strings that sound good. The source for my claim about LLMs not summarizing but abbreviating is on hn somewhere, I'll dig it out Edit: sorry, I tried but couldn't find the source.
  - 10mo ago

ozgung 10mo ago

What is a good way of connecting Obsidian vault to AI?

G_o_D 10mo ago

Thats why proofreading jobs still exist

Lerc 10mo ago

I think this will be a significant thing in the future, but right now I think the reasoning abilities are too limited. It can reasonably approximate a vector database where it can find related things, but I think that success can hide the failure to find important things. I'd like to be able to point a model at a news story and have it follow every fact and claim back to an origin, (or lack of one). I'm not sure when they will be able to do that, they aren't up to the task yet. Reading the news would be so much different if you could separate the 'we report this happened' from the 'we report that someone else reported this happened"

ericlamb89 10mo ago

Agree with OP that LLMs are a great tool for this use case. It's made possible because OP diligently created useful input data. Unfortunately OP's conclusion goes against the AI hype machine. If "consuming" is the "superpower" of AI, then the current level of investment/attention would not be justified.

zkmon 10mo ago

I don't see what's new here. The biggest enterprise usecase for AI is to "consume" the vast amount of internal wiki pages, process documents, policy manuals, code repos, presentations and be able to answer questions.

johndhi 10mo ago

Can you share some prompt examples you use to try to ensure it doesn't get "lazy" and just cherry pick from here and there? I have a written novel draft and something like a million words of draft fiction but have struggled with how to get meaningful analytics from it.

achenet 10mo ago

So I decided to give this a try - I have a `writing` directory/git repo where I store most of my writing, which can be anything from notes on technical subjects (list of useful syntax for a given programming language), to letters to friends, to philosophical ramblings. I opened Claude Code in the repo and asked it to tell me about myself based on my writing. Claude's answer overestimated my technical skills (I take notes on stuff I don't know, not on things I know, so it assumed that I had deep expertise in things I'm currently learning, and ignored areas where I do have a fair amount of experience), but the personal side really resonated with me.

n49o7 10mo ago

Compound the gains again by asking AI to write the questions too!

fsckboy 10mo ago

AI's consumption superpower reminds me of birds, flying about eating worms, then flying back to the nest and regurgitating them into baby's mouth, because it's the processed nutrition they provide that valuable; their own consumption is a combination of fractional/temporary

TimByte 10mo ago
I think the key difference (and risk) is that with AI we sometimes forget to check what got digested and what got lost along the way
stuffn 10mo ago
"AI" is more like a bird that flies around eating worms, sometimes regurgitates the nutrition, and sometimes regurgitates a pound of bolts. Then it apologizes, flies around again, and regurgitates pebbles. It does it again but this time it regurgitates acid that vaguely appears to be the same nutritious substance. If it flies around too much it will lose it's context and begin to think it's not a bird but rather a donkey. Most of "AI"s superpower is tricking monkeys into anthropomorphizing it. It's just a giant, complicated, expensive, environmentally destructive math computer with no capability to create novel thought. If it did have one superpower it's gaslighting and manipulation.

alexgotoi 10mo ago

Models are mediocre solo consumers: they skim, paraphrase and confidently miss the one subtle thing that actually matters. Humans are still better at deciding which three paragraphs in a 40‑page spec are load‑bearing. But as soon as you treat the model as a stochastic code monkey with a compiler, test suite, linter and some static tooling strapped to its back, it suddenly looks a lot more like “creation with a very fast feedback loop” than “consumption at scale”. The interesting leverage isn’t that AI can read more stuff than you; it’s that you can cheaply instrument your system (tests, properties, contracts, little spec fragments) and then let the model grind through iterations until something passes all of that. That just shifts the hard work back where it’s always been: choosing what to assert about the world. The tokens and the code are the easy part now. This might make it into this week's https://hackernewsai.com/ https://hackernewsai.com/ newsletter.

_DeadFred_ 10mo ago
Don't forget guardrails and other tweaks you don't know are being applied. I was exploring energy usage and when I reached solar energy somehow the AI decided it was political and switched to useless mode until I explicitly told it to look back at the conversation and it's context and that I wasn't trying to get it to say solar was good and it was OK if numbers made solar look good. I was really weird.
- wyre 10mo ago
  Which model were you using?
  - dehugger 10mo ago
    sounds like grok...
mistrial9 10mo ago
.. except you are completely wrong in a certain way.. AFAIK Google has been reading and indexing patent applications and maybe SEC filings since before word2vec. Certain niches absolutely are reading documents faster than your attorneys can...

ge96 10mo ago

Wrt temperature/randomization is it not possible for it to create something genuine. Even life there seems to always be some inspiration for things being made. How did Tesla go from Brushed to Brushless AC motors. There was some foundational knowledge of electricity similar to airplanes, the Wright Brothers their airplane seems backwards (like a canard) but still a plane/needs wings. Not something radical like ion engines for lift (much harder).

Ove_K 10mo ago

Digital Information Consumers or Digital Information Copiers or Digital Information Creators Either way, they are D.I.C.s

TimByte 10mo ago

This approach feels like a much more honest use

acituan 10mo ago

We know from the era of data the power of JOIN. Bring in two different data sources about a thing and you could produce an insight neither of them could have provided alone. LLMs can be thought as one big stochastic JOIN. The new insight capabilities - thanks to their massive recall - is there. The problem is the stochasticity. They can retrieve stuff from the depths and slap them together but in these use cases we have no clue how relevant their inner ranking results or intermediary representations were. Even with the best read of user intent they can only simulate relevance, not really compute it in a grounded and groundable way. So I take such automatic insight generation tasks with a massive grain of salt. Their simulation is amusing and feels relevant but so does a fortune teller doing a mostly cold read with some facts sprinkled in. > → I solve problems faster by finding similar past situations → I make better decisions by accessing forgotten context → I see patterns that were invisible when scattered across time All of which makes me skeptical of this claim. I have no doubt they feel productive but it might just as well be a part of that simulation, with all the biases, blind spots etc originating from the machine. Which could be worse than not having used the tool. Not having augmented recall is OK, forgetting things are OK - because memory is not a passive reservoir of data but an active reranker of relevance. LLMs can’t be the final source of insight and wisdom, they are at best sophists, or as Terrence Tao put it more kindly, a mere source of cleverness. In this, they can just as well augment our self-deception capacity, maybe even more than counterbalancing them. Exercise: whatever amusing insight a machine produces for you, ask for a very strong counter to it. You might be equally amused.

catigula 10mo ago

How many times have the goal-posts shifted now? Everyone is justifiably afraid of AI because it's pretty obvious that Claude Opus 4.5 level agents replace developers.

emp17344 10mo ago
This isn’t goalpost shifting - everyone is trying to figure out what AI is good at. It’s certainly not the panacea many here make it out to be.
- catigula 10mo ago
  We know what it's good at - software engineering.
mrmansano 10mo ago
> it's pretty obvious that Claude Opus 4.5 level agents replace developers. Is it though? I really don't see it. Replacing developers requires way more than writing the right code. I can agree it can replace junior to mid level engineers at some tasks, specifically in greenfield projects and popular stacks. And, don't get me wrong, it's very helpful even for senior engineers. But to "replace" those it will require some new iterations of "Opus 4.5".
- catigula 10mo ago
  I'm going to be honest because I have nothing to lose; I've never in my entire life met a single senior engineer that can surpass Opus generally. Some can surpass it at problem solving but they aren't common.

mattsears 10mo ago

Yay, another HN post confidently claiming "everyone’s doing X wrong." "Everyone’s using AI wrong." Oh, we are? Please, enlightened us thought leader, tell us how we’ve all been doing it wrong this entire time. "Here’s how most people use AI." No, that’s how you use AI. Can we stop projecting our own habits onto the whole world and calling it insight?

wyre 10mo ago

I think it's ability to consume information is one of the scarier aspects of AI. NSA, other government, and multi-national corporations have years of our individual browsing and consumption patterns. What happens when AI is analyzing all of that information exponentially faster than any human code and communicating with relevant parties for their own benefit, to predict or manipulate behavior, build psychological profiles, identify vulnerabilities, etc. It's incredibly amusing to me reading some people's comments here critical of AI, that if you didn't know any better, might make you think that AI is a worthless technology.

Liquix 10mo ago
> What happens when AI is analyzing all of that information... They run simulations against N million personality models, accurately predicting the outcome of any news story/event/stimulus. They use this power to shape national and global events to their own ends. This is what privacy and digital sovereignty advocates have been warning the public about for over a decade, to no avail.
- seg_lol 10mo ago
  This is much worse than overt authoritarian control, because the controlled aren't even aware of it.
  - wordpad 10mo ago
    I don't know how viable it is. Even for AI, there are just too many intermingled variables when it comes to human behavior. All the money in the world has been invested into trying to do it with stock markets, and they still can't do better than average.
  - hvb2 10mo ago
    You should watch the matrix, especially the first 3
macNchz 10mo ago
All hype and thought experiments about superintelligence and open questions about creativity and learning and IP aside, this is the area that gives me the biggest pause. We've effectively created a panopticon in recent years—there are cameras absolutely everywhere. Despite that, though, the effort to actually do something with all of those feeds has provided a sort of natural barrier to overreach: it'd be effectively impossible to have people constantly watching all of the millions of camera feeds available in a modern city and flagging things, but AI certainly could. Right now the compute for that is a barrier, but it would surprise me if we don't see cameras (which currently offer a variety of fairly basic computer vision "AI" alerting features for motion and object detection) coming with free-text prompts to trigger alerts. "Alert me if you see a red Nissan drive past the house.", "Alert me if you see a neighbor letting his dog poop in my yard.", "Alert the police if you see crime taking place [default on, opt out required]."

exasperaited 10mo ago

AI-powered solipsistic reassurance?

vignesh-prasad 10mo ago

This is a really cool insight. I'm going to try this in my Obsidian vault as well. What are some of the highest leverage items to add to your vault to start with? I think meetings is one thing I'm missing out on. How do you put meeting information into your Obsidian? Is it just transcripts?

rikroots 10mo ago

I'm wary about using AI models to generate stuff for me - I still bristle from the time a model told me that "JS Sets are faster than Arrays" and I believed it, until I discovered that it forgot to add the important piece of information: for Arrays containing tens of thousands of elements. Which made me feel stupid. Still, I find the models to be excellent synthesisers of vast quantities of data on subjects in which I have minimal prior knowledge. For instance, when I wanted to translate some Lorca and Cavafy poems into English I discovered that ChatGPT had excellent knowledge of the poems in their native languages, and the difficulties translators faced when rendering them into English. Once I was able to harness the models to assist me translate a poem, rather than generate a translation for me (every LLM is convinced it's a Poet), I managed to write some reasonable poems that met my personal requirements. I wrote about the experience here: https://rikverse2020.rikweb.org.uk/blog/adventures-in-poetry-translation https://rikverse2020.rikweb.org.uk/blog/adventures-in-poetry...

roadside_picnic 10mo ago

AI's real super power is telling you what you want to hear (doubly true since RLHF became the standard). You can really see the limitations of LLMs when you look at how poorly they do at summarization. They most often just extract a few key quotes from the text, and provide an abbreviated version of the original text (often missing key parts!) Abbreviation is not summarization. To properly summarized you need to be able to understand higher level abstractions implied in the text. At a fundamental level this is not what LLMs are designed to do. They can interpolate and continue existing text in remarkable and powerful ways, but they aren't capable of getting the "big picture". This is likely related to why they frequently ignore very important passages when "summarizing". > We're still thinking about AI like it's 2023. Just a reminder that in 2023 we were all told that AI was on a path of exponential progress. Were this true, you wouldn't need to argue that we're using it "wrong" because the technology would have improved dramatically more than it did from 2021-2023 such that there would be no need to argue that its better, using it "wrong" would still be a massive improvement.

1vuio0pswjnm7 10mo ago

Perhaps the power of "collecting" is even greater than "consuming" For example, collecting the thoughts, questions, aspirations, etc. of "AI" users. Much of this appears to be personal or confidential hence the recent OpenAI anouncement about turning over "private chats" to plaintiffs' counsel in copyright infringement litigation https://sites.google.com/view/elizaarchaeology/blog/3-weizenbaums-secretary https://sites.google.com/view/elizaarchaeology/blog/3-weizen... The original "AI chatbot" from the 1960's, "ELIZA", was not "trained on" (it did not consume) much data at all in today's terms. Yet it could solicit larger amounts of data from users who anthropomorphised the computer If data collection is a goal, as it is with today's Silicon Valley companies, then this is arguably a very effective hack The "AI" only needs to seem realistic to such individuals

ricksunny 10mo ago

Anyone have an idea which AI tool the author is using to consume his Obsidian repository?

hashstring 10mo ago

> Everything goes into Obsidian (meetings, thoughts, reflections) > AI has access to the entire vault Yes, consumption. Also consider who or what you are feeding too.

ezoi_MuUJd 10mo ago

Buscar porno en tu casa Y luego trabajo debset Te puede beneficiar en En tu casa, tu deuda

ensocode 10mo ago

I’m impressed, but honestly: I don’t document enough to get real value from an AI consuming my stuff. To make this useful, I’d either need a brain interface that logs my thoughts, or I’d have to speech-to-text everything I say throughout the day. Only then could an AI reasonably help connect dots or answer questions like: “What should I focus on next week?”

davegri 10mo ago

Lol the irony is that this was obviously written using AI "Last month I connected my Obsidian vault to AI. The questions changed completely: Instead of "Write me something new" I ask "What have I already discovered?"" yep

jppaoli 10mo ago

[dead]