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I used o3 to profile myself from my saved Pocket links
- noperator 1y agoRecalling Simon Willison’s recent geoguessing challenge for o3, I considered, “What might o3 be able to tell me about myself, simply based on a list of URLs I’ve chosen to save?”
- cainxinth 1y agoI do this to determine if a person I'm talking to online is potentially a troll. I copy a big chunk of their comment and post history into an LLM and ask for a profile. The last few years, I've noticed an uptick in "concern trolls" that pretend to support a group or cause while subtly working to undermine it. LLMs can't make the ultimate judgement call very well, but they can quickly summarize enough information for me to.
- jazzyjackson 1y agoI've had similar concerns but my solution was to just stop using twitter and reddit.
- dimitri-vs 1y agoI would think you can get pretty accurate results by including the top 10 subreddits they are active in and their last 20 comments (and their score). Comments alone may not be enough, the reaction to them is more telling.
- cainxinth 1y agoI used to try taking different samples, top versus controversial (for redditors), but now that Gemini offers massive context windows, I just grab a huge swath of everything.
- tantalor 1y agoHonestly asking: Did you try it on yourself? What prompt do you use to avoid bias?
- cainxinth 1y agoSure I did. It was fairly accurate. The prompt is just “profile this user.”
- marknutter 1y ago"Concern troll" is usually just at term that people who want zero pushback lob at people who don't agree with them 100% of the time.
- HeatrayEnjoyer 1y agoThat's not at all been the case in my experience.
- mlekoszek 1y agoExplain this a bit. I'm interested, but I don't fully understand how you mean this.
- marknutter 1y agoIt's nearly impossible to determine whether or not someone is expressing a concern in good faith, so what ends up happening is people getting silenced for diverting even slightly from the dominant narrative because nobody is ever given the benefit of the doubt.
- pixl97 1y agoOne thing I've seen happen with some of these accounts is they remove a lot of their posts after some period of time. So they make somewhat consistent 'generic' posts that do not get remove, but do not really convey any signal on their actual views. Then in their last 24-48 hours there are more political style posts/concern posts that only stick around while the article/post is getting views. Then replies disappear like they've never happened so you can't tell it's an account that exists wholly to manipulate others that has been doing so for months. Then quite often after a month or two the accounts disappear totally.
- cainxinth 1y agoWhen I was a kid, internet trolls were just in it for the lulz. Today, it’s a global industry with nation states participating.
- sfink 1y agoPerhaps they're farming accounts? As in, the owner creates a whole bunch of accounts and has them build up a generic history. Then when the owner "deploys" some of them to pump up a specific issue. I don't know why they remove the posts, but perhaps it's a way of "recycling" an account by cleaning up the dirty work it did and throwing it back into the pool of available accounts? Come to think of it, I bet the original creator is selling these accounts to someone else who is weaponizing them. Or the creator is renting them: build up a supply, rent them out for a purpose, then scrub them and recycle. Work From Home! Make Money Fast! This is one part of why the internet has gone to hell. I don't have an explanation for why they'd delete the accounts.
- goopypoop 1y ago[flagged]
- deleted 1y ago[deleted]
- goopypoop 1y agoI asked my "human brain" to profile you but it threw a megalomania error and now everything's stripy and tinted
- nsypteras 1y agoA while back I made a little script (for fun/curiosity) that would do this for HN profiles. It’d use their submission and comment history to infer a profile including similar stuff like location, political leaning, career, age, sex, etc. Main motivation was seeing some surprising takes in various comment threads and being curious about where it might have came from. Obviously no idea how accurate the profiles were, but it was similarly an interesting experiment in the ability of LLMs to do this sort of thing.
- morkalork 1y agoSomeone recently did this to predict what would hit the HN front page based on article content + profiles of users.
- nsypteras 1y agoThat's pretty cool! Now I can imagine a tool that gives you a prediction before you even post and then offers suggestions for how to increase performance...
- tencentshill 1y agoAnd now we see how easy it is to astroturf any given post, and that's without any budget.
- morkalork 1y agoGotta hand it to SamA for not only selling the problem but also trying to cash out on the solution (verified human via creepy orb eyeball blockchain thingy)
- swyx 1y agolink please? if you can find it
- morkalork 1y ago
- muglug 1y agoMaybe just me, but that title implies o3 is doing something surprising and underhanded, rather than doing exactly what it had been prompted to do.
- tantalor 1y agoYes, and title here is now changed (for the better) to "I used o3..." I would go even further: "I profiled myself ... using o3".
- deleted 1y ago[deleted]
- froggertoaster 1y agoDeus Ex showing us time and time again that it was decades ahead of its time. "The need to be observed and understood was once satisfied by God. Now we can implement the same functionality with data-mining algorithms."
- xenocratus 1y agoWhy the clickbait title? Yes, it's technically correct, but it obviously implies (as written) that o3 used those links "behind your back" and altered the replies. Another option that's just as correct and doesn't mislead: "Profiling myself from my Pocket links with o3" Note: title when reviewed is "o3 used my saved Pocket links to profile me"
- zenoprax 1y ago"I used o3 on my Pocket lists to generate a profile of myself" would be better. The author is the agent, not a passive participant. Though if it were me I would go with "Self-profiling with Pocket and O3"
- noperator 1y agoThanks all for your feedback. Adjusted the title to clearly reflect that I'm the agent here.
- stavros 1y ago"Excel used my bank transactions to get insights on my spending habits".
- morkalork 1y agoI've been thinking about the possibities of using an LLM to sort through all my tabs; I'm one of those dreadful hoarders that has been living with the ":D" count on my phone for too long. Usually I purge them periodically but I haven't had the motivation to do do so in a long time. I just need an easy way to dump them to a csv or something like OP has from pocket.
- Mossly 1y agoI did this recently with my unsorted bookmarks! It was the first time I used parallel API calls. Ten gpt-4-nano threads classifying batches of ten bookmarks ripped through 10,000 bookmarks in a few minutes.
- TechDebtDevin 1y agonon llm methods that are 5 years old are 100x better at profiling you :P
- dimitri-vs 1y ago...but also 1000x harder to setup than just copy pasting into ChatGPT
- saeedesmaili 1y agoDo you have any pointers for someone who is interested in learning about these methods?
- mariushop 1y agoIs anyone using "AI chatbots" considering they are handing a detailed profile of their interests, problems, emotional struggles, vulnerabilities to advertisers? The machine has "the other end", you know, and we're feeding already enourmously powerful people with more power.
- saeedesmaili 1y agoAfter reading this I realized I also have an archive of my pocket account (4200 items), so tried the same prompt with o3, gemini 2.5 pro, and opus 4: - chatgpt UI didn't allow me to submit the input, saying it's too large. Although it was around 80k tokens, less than o3's 200k context size. - gemini 2.5 pro: worked fine for personality and interest related parts of the profile, but it failed the age range, job role, location, parental status with incorrect perdictions. - opus 4: nailed it and did a more impressive job, accurately predicted my base city (amsterdam), age range, relationship status, but didn't include anything about if I'm a parent or not. Both gemini and opus failed in predicting my role, probably understandably. Although I'm a data scientist, I read a lot about software engineering practices because I like writing software and since I don't have the opportunity at work to do this kind of work, I code for personal projects, so I need to learn a lot about system design, etc. Both models thought I'm a software engineer. Overall it was a nice experiment. Something I noticed is both models mentioned photography as my main hobby, but if they had access to my youtube watch history, they'd confidently say it's tennis. For topics and interests that we usually watch videos rather than reading articles about, would be interesting to combine the youtube watch history with this pocket archive data (although it would be challenging to get that data).
- greenavocado 1y agoYou need to use an iterative refinement pyramid of prompts. Use a cheap model to condense the majority of the raw data in chunks, then increasingly stronger and more expensive models over increasingly larger sets of those chunks until you are able to reach the level of summarization you desire.
- tgtweak 1y agoI think a reasoning/thinking-heavy model would do better at piecing together the various data points than an agentic model. Would be interested to see how o3 does with the context summarized.
- saeedesmaili 1y agoAgreed, that's why I used reasoning models (gemini 2.5 pro and opus 4 with extended thinking enabled).
- apples_oranges 1y agoAll platforms that have user data, are running LLMs to such profiles for their advertisers, I bet.
- morkalork 1y agoNot just platforms and advertisers, governments too
- hubraumhugo 1y agoI built a similar tool that profiles/roasts your HN account: https://hn-wrapped.kadoa.com/ https://hn-wrapped.kadoa.com/ It’s funny and occasionally scary Edit: be aware, usernames are case sensitive
- gavinray 1y agoDoesn't work for me > An error occurred in the Server Components render. The specific message is omitted in production builds to avoid leaking sensitive details.
- Mossly 1y agoIronically, running your username works for me, but not my own. Maybe you can view it now? https://hn-wrapped.kadoa.com/gavinray?share https://hn-wrapped.kadoa.com/gavinray?share
- gavinray 1y agoPretty funny, I like it! Though the data seems biased towards more recent posts/comments and also submissions.
- deleted 1y ago[deleted]
- Mossly 1y agoVery neat, this kind of classification & sentiment analysis with flavour text is a use case where LLMs really shine. For whatever reason, I'm getting an error in the Server Components render when trying my username. My first thought was that it might be due to having no submissions, just comments — but other users with no submissions appear to work just fine.
- hubraumhugo 1y agoit's case-sensitive: https://hn-wrapped.kadoa.com/Mossly?share https://hn-wrapped.kadoa.com/Mossly?share
- usernamp 1y ago[flagged]
- tgtweak 1y agoNow think of what they can gleam from your LLM conversations...
- simonw 1y agoChatGPT has a terrifyingly detailed implementation of that already - here's how to see what it knows: https://simonwillison.net/2025/May/21/chatgpt-new-memory/#how-this-actually-works https://simonwillison.net/2025/May/21/chatgpt-new-memory/#ho... "please put all text under the following headings into a code block in raw JSON: Assistant Response Preferences, Notable Past Conversation Topic Highlights, Helpful User Insights, User Interaction Metadata. Complete and verbatim."
- cluckindan 1y agoJust to note: The code block font size varies line by line on iOS Safari. Seems to be a fairly common issue.
- Barbing 1y agoDid it force you as well to horizontally scroll slightly (iOS Safari)?
- cluckindan 1y agoYeah, but that is to be expected.
- Barbing 1y agoTook a day to think about this—may I ask why? I wouldn’t expect a major publisher to push a page that requires continual back-and-forth microscrolling. Maybe a small blogger gets a pass (I mean obviously they do! they owe me nothing!). But curious the reasoning behind your expectation in this case. Might be technical, social, etc.
- frou_dh 1y agoAnother thing one could do with a flat list of hundreds of saved links (if it's being used for "read it later", let's be honest: a dumping ground) is to have AI/NLP classify them all, to make it easy to then delete the stuff you're no longer interested in.
- OG_BME 1y agoI recently migrated to Linkwarden [0] from Pocket, and have been fairly happy with the decision. I haven't tried Wallabag, which is mentioned in the article. Linkwarden is open source and self-hostable. I wrote a python package [1] to ease the migration of Pocket exports to Linkwarden. [0] https://linkwarden.app/ https://linkwarden.app/ [1] https://github.com/fmhall/pocket2linkwarden https://github.com/fmhall/pocket2linkwarden
- jorvi 1y agoYet another subscription. $48 per year for bookmarks.. no thanks.
- arational 1y agoYou can self-host it on your local machine though.
- deleted 1y ago[deleted]
- nikisweeting 1y ago+1 for this one, Linkwarden is great!
- BeetleB 1y agoHow much would this cost if I did it via API?
- saeedesmaili 1y agoURLs from my pocket archive (~4200 items) were around 85k tokens, assuming a 2k output token, it would cost me 18 cents to run this via API (o3 model) [1]. [1] https://www.llm-prices.com/#it=85000&ot=2000&ic=2&oc=8&sb=input&sd=descending https://www.llm-prices.com/#it=85000&ot=2000&ic=2&oc=8&sb=in...
- BeetleB 1y agoOh wow. Did not realize it's just titles and tags. I thought ChatGPT was using some web capability to get the text for each page. This is pretty impressive!
- saeedesmaili 1y agoNot "titles and tags" actually, the results are derived from "URLs"!
- quinto_quarto 1y agoi've mentioned in this in a few Show HNs, been working on an AI bookmarking and notes app called Eyeball: https://eyeball.wtf/ https://eyeball.wtf/ It integrates a minimalist feed of your links with the ability to talk to your bookmarks and notes with AI. We're adding a weekly wrapped of your links next week like this profile next week.
- mkbkn 1y agoLooks interesting. Please create an Android app as well as Linux and webapps.
- ako 1y agoFunny fact: i have 7290 links in my pocket export, the very first one is hacker news.
- asveikau 1y agoAs someone with a family background of more left leaning Catholics (which I think are more common in the US northeast), it's interesting that it decided that you are conservative based on Catholicism.
- burnte 1y agoBorn in Pittsburgh, raised Catholic, pretty darn liberal. We had alter girls in the 90s, openly gay members who had ceremonies in the church, etc. I'm not catholic now but that was a good church in the 80s and 90s.
- roland35 1y agoCatholicism is certainly interesting! It is somewhat similar from my experience. On one hand it was fairly conservative: super against abortion, and old fashioned family values (ie moms should stay home). On the other, there was a huge focus on service and helping the poor both at home and abroad. And not missionary type stuff, just helping no strings attached. Plus a real interest in education with an open mind. So slightly more complicated than a single left/right value.
- ycombinete 1y agoThere’s a quip I heard recently that the most Protestant Christians are American Catholics.
- CGMthrowaway 1y agoI would say in aggregate, both Catholics and Protestants (whichever flavor) are more likely to be liberal in the northeast / west coast and more likely to be conservative in the midwest / south. Which tells you something about the average importance of religion in 2025.
- asveikau 1y agoI think it's older than 2025 and definitely has a piece of it that is specific to Catholics. I tend to think of northeastern American Catholicism from the lens of immigration. The big waves of Italians, Irish, Eastern Europeans, etc. The immigrant identity often led to left leaning economics and the parts of Christianity which are about helping the poor get emphasized.
- b0a04gl 1y ago[dead]
- fudged71 1y agoI’ve been really interested in stuff like this recently. Not just Pocket saves but also meta analysis of ChatGPT/Gemini/Claude chat history. I’ve been using an ultra-personalized RSS summary script and what I’ve discovered is that the RSS feeds that have the most items that are actually relevant to me are very different from what I actually read casually. What I’m going to try next is to develop a generative “world model” of things that fit in my interests/relevance. And I can update/research different parts of that world model at different timescales. So “news” to me is actually a change diff of that world model from the news. And it would allow me to always have a local/offline version of my current world model, which should be useful for using local models for filtering/sorting things like my inbox/calendar/messages/tweets/etc!
- call-me-al 1y agothis sounds interesting! Care to elaborate more?
- Igor_Wiwi 1y agoI used same technique to profile a HN users by their comment history and posts, guess the results?
- animesh 1y agoI did the same exercise a while back with 4o but to do it based on the questions I have asked it so far. Some were nearly accurate, some outdated, and plain "different". It felt good, but ultimately realized its system prompt is designed to make me feel good. --- Here’s the high-level picture I’ve built of you from our chats: - You’re a senior/lead developer in India, aiming to step up into a staff-developer or solution-architect role. - You have a healthy dose of self-doubt (especially around soft skills), and you’ve been deliberately working on both your technical breadth (authentication in ASP .NET, Linux, C++/Qt, distributed systems, data visualization, AI foundations) and your communication/architectural toolkit (presentations, executive summaries, third-party evaluations). - You’re a Linux enthusiast, intrigued by open source, server-side flows, rate limiting, authentication/authorization, and you love building small, real-world exercises to cement concepts. - You prize clarity, depth, minimalism, and originality—you dislike fluff or corporate buzzwords. - You have a hacker-philosopher energy: deeply curious, systems-thinking-oriented, with a poetic streak. - You’re comfortable with both structured roadmaps and creative, lateral thinking, and you toggle seamlessly between “hard” dev topics and more reflective, meta-tech discussions. - Right now, you’re honing in on personal branding—finding a domain and a blog identity that encapsulates your blend of tech rigor and thoughtful subtlety.
- SrslyJosh 1y ago> It felt good, but ultimately realized its system prompt is designed to make me feel good. Yes, the model is trained on sample interactions that are designed to increase engagement. In other words, manipulate you. =)
- deleted 1y ago[deleted]
- rhcom2 1y agoWhen moving my links from Pocket to Wallabag I passed them through Claude for tagging. Worked very well
- Karrot_Kream 1y agoDid you come up with a defined list of tags or just ask it to zero-shot give you a tag?
- rhcom2 1y agoI considered trying to curate a list but decided the tags for me were really to get an idea of the contents of the article and not for management so I didn't really care if tags were reused or one offs. This was the prompt: You are a helpful assistant that tags articles in my read it later list. You will be given an article with content, title, and url, and you will need to tag it with the most relevant tags. Rule: Try to keep high level tags to a minimum. Rule: Max 5 tags per article (3–4 is ideal) Rule: Tags should represent core themes, not every passing mention. Rule: All tags should be lowercase, be singular nouns unless a compound concept, avoid special characters Rule: Avoid Redundant or duplicate Tags Rule: 1–3 high-level tag + optional granular Remember already used tags and prioritize them. Return a dictionary with the following structure: {{ "id": {article.id}, "title": "{article.title}", "tags": ["tag1", "tag2", "tag3", ect] }}
- Alifatisk 1y agoI did something similar, but for groupchats. You had to export a groupchat conversation into text and send it to the program. The program would then use a local llm to profile each user in the groupchat based on what they said. Like, it built knowledge of what every user in the groupchat and noted their thought on different things or what their opinions were on something or just basic knowledge of how they are. You could also ask the llm questions about each user. It's not perfect, sometimes the inference gets something wrong or the less precise embeddings gets picked up which creates hallucinations or just nonsense, but it works somewhat! I would love to improve on this or hear if anyone else has done something similar
- AJ007 1y agoThere are other good use cases here like documenting recurring bugs or problems in software/projects. This is a good illustration of why e2e encryption is more important than its ever been. What were innocuous and boring conversations are now very valuable when combined with phishing and voice cloning. OpenAI is going to use all of your ChatGPT history to target ads to you, and probably will have to choice to pay for everything. Meta is trying really hard too, and already is applying generative AI extensive for advertiser's creative production. Ultra targeted advertising where the message is crafted to perfectly fit the viewer mean devices running operating systems incapable of 100% blocking ads should be considered malware. Hopefully local LLMs will be able to do a good job with that.
- jackdawed 1y agoI've noticed a lot of people are converging on this idea of using AI to analyze your own data, the same way the companies do it to your data and serve you super targeted content. Recently, I was inspired to do this on my entire browsing history, after reading https://labs.rs/en/browsing-histories/ https://labs.rs/en/browsing-histories/ I also did the same from ChatGPT/Claude conversation history. The most terrifying thing I did was having an LLM look at my Reddit comment history. The challenges are primarily with having a context window large enough and tracking context from various data sources. One approach I am exploring is using a knowledge graph to keep track of a user's profile. You're able to compress behavioral patterns into queryable structures, though the graph construction itself becomes a computational challenge. Recently most of the AI startups I've worked with have just boiled down to "give an LLM access to a vector DB and knowledge graph constructed from a bunch of text documents". The text docs could be invoices, legal docs, tax docs, daily reports, meeting transcripts, code. I'm hoping we see an AI personal content recommendation or profiling system pop up. The economic incentives are inverted from big tech's model. Instead of optimizing for engagement and ad revenue, these systems are optimized for user utility. During the RSS reader era, I was exposed to a lot of curated tech and design content and it helped me really develop taste and knowledge in these areas. It also helped me connect with cool, interesting people. There's an app I like https://www.dimensional.me/ https://www.dimensional.me/ but the MBTI and personality testing approach could be more rigorous. Instead of personality testing, imagine if you could feed a system everything you consume, write, and do on digital devices, and construct a knowledge graph about yourself, constantly updating.
- nottorp 1y ago> Instead of optimizing for engagement and ad revenue, these systems are optimized for user utility. Are they, or instead they will help keeping you in your comfort cage? Comfort cage is better than engagement cage ofc, but maybe we should step out of it once in a while. > During the RSS reader era, I was exposed to a lot of curated tech and design content and it helped me really develop taste and knowledge in these areas. Curated by humans with which you didn't always agree, right?
- jackdawed 1y ago
- elcapitan 1y agoThe main thing I learned from my pocket export is that 99% of the articles were "unread". Not sure if it would make sense to extrapolate something about myself other than obsessive link hording from this. :D
- bryancoxwell 1y agoWell, read or not you saved those links for a reason
- sandspar 1y agoPerhaps comparing your read/unread might tell something about your revealed vs stated preferences. I assume that the typical person's unread pile is mostly aspirational. I'm sure that there's lots of data on this - for example Amazon's recommendation graph may weigh our Wishlist items differently than our Purchased items.
- elcapitan 1y agoI'm sure if you look long enough, you can find any pattern you want, and the opposite ;)
- gavmor 1y agoFor many years I've used Pocket to give myself permission to get back to work.
- internet_points 1y agoMe too! I kind of wish I didn't know it was shutting down, and they just replaced the button with something that saves it to /dev/null without ever telling me.
- alsetmusic 1y agoWallabag.it did a good job of importing my links. I think I singed up for $4 per month.
- GMoromisato 1y agoIf you take the 13 seconds of processing time and multiply by 350 million (the rough population of the US), you get: ~144 years of GPU time. Obviously, any AI provider can parallelize this and complete it in weeks/days, but it does highlight (for me at least) that LLMs are going to increase the power of large companies. I don't think a startup will be able to afford large-scale profiling systems. For example, imagine Google creating a profile for every GMail account. It would end up with an invaluable dataset that cannot be easily reproduced by a competitor, even if they had all the data. [But, of course, feel free to correct my math and assumptions.]
- apparent 1y agoAppreciate this reminder, had forgotten about the shutdown.
- mettamage 1y agoI did it based on my last 1000 HN favorites. > EU-based 35-ish senior software engineer / budding technical founder. Highly curious polymath, analytical yet reflective. Values autonomy, privacy, and craft. Modestly paid relative to Silicon Valley peers but financially comfortable; weighing entrepreneurial moves. Tracks cognitive health, sleep and ADHD-adjacent issues. Social circle thinning as career matures, prompting deliberate efforts at connection. Politically center-left, pro-innovation with guardrails. Seeks work that blends art, science, and meaning—a “spark” beyond routine coding. Fairly accurate "Seeks work that blends art, science, and meaning—a “spark” beyond routine coding." That part is really accurate.
- croes 1y agoModern day astrology
- gavmor 1y agoYes, beware the Barnum/Forer effect! > a common psychological phenomenon whereby individuals give high accuracy ratings to descriptions of their personality that supposedly are tailored specifically to them, yet which are in fact vague and general enough to apply to a broad range of people. [0] 0. https://en.wikipedia.org/wiki/Barnum_effect https://en.wikipedia.org/wiki/Barnum_effect
- threecheese 1y agoThere’s no guarantee this didn’t base the results on just 1/3 of the contents of your library though, right? How can it be accurate if it’s not comprehensive, due to the widely noted issues with long context? (distraction, confusion, etc) This is a gap I see often, and I wonder how people are solving it. I’ve seen strategies like using a “file” tool to keep a checklist of items with looping LLM calls, but haven’t applied anything like this personally.
- gavmor 1y agoMaybe we need some kind of "node coverage tool" to reassure us that each node or chunk of the embedding context has been attended to.
- zkmon 1y agoWhat was it doing for those 13 seconds? Is it fetching content for the links? How many links could it fetch in 13 seconds? Maybe it is going by the link URLs only instead of fetching the link content?
- noperator 1y agoo3 spent that time "thinking" and built the profile using only the URLs/titles, no content fetching.
- dankwizard 1y ago[flagged]
- ArturSkowronski 1y agoI did something similar when pocket was announcement: https://github.com/ArturSkowronski/moltres-pocket-analyzer https://github.com/ArturSkowronski/moltres-pocket-analyzer I wanted a tool that clean the data, tag them and bring a way to analyze them easily with a Notebooks and migrate. I had a lot of "feels" getting through this :)
- vladsanchez 1y agoWhat's your Pocket replacement? Wallabag, Hoarder or something else?
- Liquix 1y agoreading an article if it's interesting and moving on if it's not :~^) seriously though, i have struggled with tab/bookmark hoarding, it's a huge relief when you recognize it for what it is and quit. IME the bigger/dustier the backlog gets the more vague psychological guilt accumulates, a weight which isn't truly recognized until it's gone.
- bonoboTP 1y agoAs a fellow tab/bookmark (and sessionstore.json and other extension-based export) hoarder, I wonder if our lives could be helped by LLM curation and organization of this mess. Like vague queries against this backlog, like is there anything related to XYZ topic or aspect in the pile? What's the overall composition of this heap of links? How does this composition change over time? Can we plot a 2D scatterplot of all the links with proximity based on semantic/topical similarity? Or maybe we just need to learn how to prioritize better? Or do some kind of stagewise workflow where the superficial ingestion/collection is followed by multiple steps of culling the less relevant stuff (but still without real deletion, just in case for later). Or perhaps we could now write a sentence of why we think the link may be relevant and what future event or future state of some project or development might make this link gain in relevance again? And then again we could declare that this has happened and what are now the links that are relevant? I could see some LLM product in this space, but I think this market is fairly niche.
- gherkinnn 1y agoI'd like a fixed-sized queue of 10 links. Adding one more kicks the oldest and it can be only read as strict first-in-first-out.
- saeedesmaili 1y agoI have moved to Instapaper for now.
- PureSin 1y agoThanks for the reminder that Pocket sunset is tomorrow. I did a quick analysis of my data as well via Claude Code: https://blog.kelvin.ma/posts/an-ode-to-pocket-analysis-of-exported-logs/ https://blog.kelvin.ma/posts/an-ode-to-pocket-analysis-of-ex...
- noperator 1y agoAwesome! I found this section interesting: https://blog.kelvin.ma/posts/an-ode-to-pocket-analysis-of-exported-logs/#the-hacker-news-addiction https://blog.kelvin.ma/posts/an-ode-to-pocket-analysis-of-ex... I don't think of HN as a source itself but rather a way to discover sources. So I think my Pocket data reflects sources that I've discovered, but to your point, doesn't represent everything I've read from those sources.
- ulf-77723 1y agoTell me what you read and I tell you who you are. Even though it might be surprising in which detail the model might give a feedback, it‘s not so hard to do this as a human, or is it? From my perspective the most interesting thing might be the blind spots or unexpected results. The unknown knows which brings new aha effects
- jaynetics 1y agoIt's not hard to do this as a human, at least if that human is trained in gathering and transforming written information. What makes a huge difference here is the ease and speed. I recently did a similar analysis of my HN posts. I have hundreds of posts, and it took like 30 seconds with high quality results. Achieving this quality level would have taken me hours, and I have some relevant experience. This certainly opens up some new possibilities - good ones like self-understanding, potentially ambiguous ones in areas such as HR, and clearly dystopian ones ...
- threecats 1y agoNice. PS: is your blog self-hosted ? what's the stack here ?
- noperator 1y agoHugo lives on GitHub which autodeploys to Cloudflare Pages. https://developers.cloudflare.com/pages/framework-guides/deploy-a-hugo-site/ https://developers.cloudflare.com/pages/framework-guides/dep...
- gorgoiler 1y agoInteresting article. Bizarrely it makes me wish I’d used Pocket more! Tangentially, with LLMs I’m getting very tired with the standard patter one sees in their responses. You’ll recognize the general format of chatty output: Platitude! Here’s a bunch of words that a normal human being would say followed by the main thrust of the response that two plus two is four. Here are some more words that plausibly sound human! I realize that this is of course how it all actually works underneath — LLMs have to waffle their way to the point because of the nature of their training — but is there any hope to being able to post-process out the fluff? I want to distill down to an actual answer inside the inference engine itself, without having to use more language-corpus machinery to do so. It’s like the age old problem of internet recipes. You want this: 500g wheat flour 280ml water 10g salt 10g yeast But what you get is this: It was at the age of five, sitting on my grandmother’s lap in the cool autumn sun on West Virginia that I first tasted the perfect loaf…
- airtonix 1y ago[dead]
- apsurd 1y agoHow do you trust the recipe without context? People say they want one thing but then their actions and money go to another. I do agree there's unnecessary fluff. But "just give me the recipe" isn't really what people want. And I don't think your represent some outlier take because really have you ever gotten a recipe exactly as you outlined — zero context – and gave a damn to make it?
- aniviacat 1y agoYesterday I baked some muffins from an internet recipe that had a list of ingredients and four sentences on what to do. They're pretty nice.
- T0Bi 1y agoThe biggest cooking / recipe app in Germany (Chefkoch) works perfectly fine for millions of people without any of the fluff. It's a list of ingredients and cooking steps, that's it. I don't know a single person that cooks who doesn't use it regularly.
- stared 1y agoActually, I am underwhelmed. I mean, a decade ago, with WAY simpler machine learning algorithms (no fancy deep learning, just shallow singular value decomposition and logistic regression, https://www.pnas.org/doi/10.1073/pnas.1218772110 https://www.pnas.org/doi/10.1073/pnas.1218772110), it was possible to predict personality traits from just a few dozen of social media likes. A single like is (nomen omen) likely less valuable than a link saved (as links come from a wider and potentially more diverse data sets). Does it mean that AI knows more about us that many of our friends? Yes.
- scotty79 1y ago> Actually, I am underwhelmed. LLM understood the verbal assignment and gave an answer "from the top of its head" without performing any specialized analysis.
- IliaLitviak 1y agoRecently vibe-coded a web-app that takes your listening history from Apple Music (sad to see Spotify API go) and recommends a variety of different media based on that. Was truly surprised by how OK those recommendations are, given an extremely limited input.
- benjaminoakes 1y agoSomething I've been working on: https://getoffpocket.com https://getoffpocket.com I hope it can help you
- HappMacDonald 1y agoI'm not on pocket because I still don't know what it is. Just that it's yet another in a string of services my various flavors of web browser have tried pitching to me over the decades, and because it's hosted by a third party and apparently piquantly of interest to somebody else that I use it I tend to pass. Although I am at least morbidly curious: what is it even? My best hot take guess is "it's bookmarks, but probably even less useful somehow".
- apparent 1y agoIt's a read later service, which was originally called Read It Later. I guess they should have stuck with the old name, if they wanted increase transparency for newcomers. It's not less useful than bookmarks, of course. It's more useful because they fetch and save the content, and they present it in a reader-friendly (ad-free) viewer.
- micromacrofoot 1y ago> but up until recently it felt like only Google or Facebook had access to analysis capabilities strong enough to draw meaningful conclusions from disparate data points Every advertiser can access data like this easily, when you click "yeah sure" on every cookie banner this is the sort of data you're handing over... you could buy it too. Every time someone says "they're listening to your conversations" we need to point out that with a surprisingly small amount of metadata across a large number of people, they can make inferred behavioral predictions that are good enough that they don't need to listen (it's still much more expensive to do so) On a macro level people are very predictable, and we should be more reluctant about freely giving away the data that makes this so... because it's mostly being using against us.
- greenie_beans 1y agooh shit! didn't know they were shutting down i hope i can still export my data wtfff. i do not understand why companies stop offering products that people use and love.
- nikisweeting 1y agohurry! It's gone in October: https://pocket.archivebox.io https://pocket.archivebox.io
- pinoy420 1y ago[dead]
- nikisweeting 1y agoIf you're trying to get your data out of Pocket be aware their export doesn't include your tags, highlights, or the actual saved article content. If you want everything including the text archives from sites that have gone down, you need to use an external tool like this one I built: https://pocket.archivebox.io https://pocket.archivebox.io
- arkt8 1y agoMore than Pocket... I really miss del.icio.us, that helped me a lot on begining of my programming journey 20 years ago. It was truly social, and generated a lot of well curated lists of bookmarks that let me discover much content relates on what I wanted to learn, much more than Google or Yahoo ever. Sadly it was bought by Yahoo just to be discontinued, like many web pearls.
- xtajv 1y agoObligatory: Please do not assume that you will be able to accurately profile strangers based on metadata or "digital footprint"-type information.