Swift is Open Source https://hn.unlurker.com/replay?item=10669891
Launch of Figma, a collaborative interface design tool https://hn.unlurker.com/replay?item=10685407
Introducing OpenAI https://hn.unlurker.com/replay?item=10720176
The first person to hack the iPhone is building a self-driving car https://hn.unlurker.com/replay?item=10744206
SpaceX launch webcast: Orbcomm-2 Mission [video] https://hn.unlurker.com/replay?item=10774865
At Theranos, Many Strategies and Snags https://hn.unlurker.com/replay?item=10799261
Miss it for reddit as well. Top day/week/month/alltime makes it hard to find top a month in 2018.
An extension of this would be to grade people on the accuracy of the comments they upvote, and use that to weight their upvotes more in ranking. I would love to read a version of HN where the only upvotes that matter are from people who agree with opinions that turn out to be correct. Of course, only HN could implement this since upvotes are private.
It's subjective of course but at least it's transparently so.
I just think it's neat that it's kinda sorta a loose proxy for what you're talking about but done in arguably the simplest way possible.
Why stop there?
If you can do that you can score them on all sorts of things. You could make a "this person has no moral convictions and says whatever makes the number go up" score. Or some other kind of score.
Stuff like this makes the community "smaller" in a way. Like back in the old days on forums and IRC you knew who the jerks were.
(And we do have that in real life. Just as, among friends, we do keep track of who is in whose debt, we also keep a mental map of whose voice we listen to. Old school journalism still had that, where people would be reading someone’s column over the course of decades. On the internet, we don’t have that, or we have it rarely.)
Of course in the above example of stocks there are clear predictions (HNWS will go up) and an oracle who resolves it (stock market). This seems to be a way harder problem for generic free form comments. Who resolves what prediction a particular comment has made and whether it actually happened?
Didn't somebody make an ETF once that went against the prediction of some famous CNBC stock picker, showing that it would have given you alpha in the past.
> seems to be a way harder problem for generic free form comments.
That's what prediction markets are for. People for whom truth and accuracy matters (often concentrated around the rationalist community) will often very explicitly make annual lists of concrete and quantifiable predictions, and then self-grade on them later.
What came back were the usual suspects: GLP-1 companies and AI.
Back to the "boring but right" thesis. Not much alpha to be found
Even today, "ASI will kill us all" can be a pretty divisive declaration - hardly safe and boring.
From the couple of threads I clicked, it seemed like this LLM-driven analysis was picking up on that, too: the top comments were usually bold, and some of the worst-rated comments was the "safe and boring" declaration that nothing interesting ever really happens.
IIRC, when comment moderation and scoring came to Slashdot, only a random (and changing) selection of users were able to moderate.
Meta-moderation came a bit later. It allowed people to review prior moderation actions and evaluate the worth of those actions.
Those users who made good moderations were more likely to become a mod again in the future than those who made bad moderations.
The meta-mods had no idea whose actions they were evaluating, and previous/potential mods had no idea what their score was. That anonymity helped keep it honest and harder to game.
Kidding aside, the comments it picks out for us are a little random. For instance, this was an A+ predictive thread (it appears to be rating threads and not individual comments):
https://news.ycombinator.com/item?id=10703512
But there's just 11 comments, only 1 for me, and it's like a 1-sentence comment.
I do love that my unaccredited-access-to-startup-shares take is on that leaderboard, though.
It's a good comment, but "prescient" isn't a word I'd apply to it. This is more like a list of solid takes. To be fair there probably aren't even that many explicit, correct predictions in one month of comments in 2015.
My original goal was to prune the account deleting all the useless things and keeping just the unique, personal, valuable communications -- but the other day, an insight has me convinced that the safer / smarter thing to do in the current landscape is the opposite: remove any personal, valuable, memorable items, and leave google (and whomever else is scraping these repositories) with useless flotsam of newsletters, updates, subscription receipts, etc.
Any chance you can outline the steps/prompts/tools you used to run this?
I've been building a 2nd brain type project, that plugs into all my work places and a custom classifier has been on that list that would enhance that.
If an LLM were acting as a kind of historian revisiting today’s debates with future context, I’d bet it would see the same pattern again and again: the sober, incremental claims quietly hold up, while the hyperconfident ones collapse.
Something like "Lithium-ion battery pack prices fall to $108/kWh" is classic cost-curve progress. Boring, steady, and historically extremely reliable over long horizons. Probably one of the most likely headlines today to age correctly, even if it gets little attention.
On the flip side, stuff like "New benchmark shows top LLMs struggle in real mental health care" feels like high-risk framing. Benchmarks rotate constantly, and “struggle” headlines almost always age badly as models jump whole generations.
I bet theres many "boring but right" takes we overlook today and I wondr if there's a practical way to surface them before hindsight does
LLMs have seen huge improvements over the last 3 years. Are you going to make the bet that they will continue to make similarly huge improvements, taking them well past human ability, or do you think they'll plateau?
The former is the boring, linear prediction.
Also, the boring consistent progress case for AI plays out in the end of humans as viable economic agents requiring a complete reordering of our economic and political systems in the near future. So the “boring but right” prediction today is completely terrifying.
So the correctness of boring predictions is unsurprising, but also quite useless, because predicting the future is precisely about predicting those events which don’t follow that pattern.
Going against the grain and turning out right is far more valuable than being right consistently when the crowd is with you already.
By 2065, we should be in possession of a proof that 0+0=0. Hopefully by the following year we will also be able to confirm that 0*0=0.
(All arithmetic here is over the natural numbers.)
Would the commenter above mind sharing the method behind of their generalization? Many people would spot check maybe five items -- which is enough for our brains to start to guess at potential patterns -- and stop there.
On HN, when I see a generalization, one of my mental checklist items is to ask "what is this generalization based on?" and "If I were to look at the problem with fresh eyes, what would I conclude?".
In personal situations there's clearly a self fulfilling prophecy going on, but when it comes to the external world, the predictions come out pretty accurate.
> (Copying my comment here from Reddit /r/rust:) Just to repeat, because this was somewhat buried in the article: Servo is now a multiprocess browser, using the gaol crate for sandboxing. This adds (a) an extra layer of defense against remote code execution vulnerabilities beyond that which the Rust safety features provide; (b) a safety net in case Servo code is tricked into performing insecure actions. There are still plenty of bugs to shake out, but this is a major milestone in the project.
https://news.ycombinator.com/item?id=10654216
The Cannons on the B-29 Bomber "accurate account of LeMay stripping turrets and shifting to incendiary area bombing; matches mainstream history"
It gave a good grade to user cstross but to my reading of the comment, cstross just recounted a bit of old history. The evaluation gave cstross for just giving a history lesson or no?
I begrudgingly accept my poor grade.
Looking at the comment reviews on the actual website, the LLM seems to have mostly judged whether it agreed with the takes, not whether they came true, and it seems to have an incredibly poor grasp of it's actual task of accessing whether the comments were predictive or not.
The LLM's comment reviews are of often statements like "correctly characterized [program language] as [opinion]."
This dynamic means the website mostly grades people on having the most confirmist take (the take most likely to dominate the training data, and be selected for in the LLM RL tuning process of pleasing the average user).
Link to LLM review: https://karpathy.ai/hncapsule/2015-12-02/index.html#article-....
So the LLM is praising a comment as describing DF as unforgiving (a characterization of the present then, not a statement about the future). And worse, it seems like tptacek may in fact be implying the opposite of the future (e.g., x will continue to crash when it was eventually fixed.)
Here is the original comment: " tptacek on Dec 2, 2015 | root | parent | next [–]
If you're not the kind of person who can take flaws like crashes or game-stopping frame-rate issues and work them into your gameplay, DF is not the game for you. It isn't a friendly game. It can take hours just to figure out how to do core game tasks. "Don't do this thing that crashes the game" is just another task to learn."
Note: I am paraphrasing the LLM review, as the website is also poorly designed, with one unable to select the text of the LLM review!
N.b., this choice of comment review is not overly cherry picked. I just scanned the "best commentators" and tptacek was number two, with this particular egregiously unrelated-to-prediction LLM summary given as justifying his #2 rating.
https://karpathy.ai/hncapsule/2015-12-03/index.html#article-...
phire
> “Oculus might end up being the most successful product/company to be kickstarted… > Product wise, Pebble is the most successful so far… Right now they are up to major version 4 of their product. Long term, I don't think they will be more successful than Oculus.”
With hindsight:
Oculus became the backbone of Meta’s VR push, spawning the Rift/Quest series and a multi‑billion‑dollar strategic bet.
Pebble, despite early success, was shut down and absorbed by Fitbit barely a year after this thread.
That’s an excellent call on the relative trajectories of the two flagship Kickstarter hardware companies.It is unfortunate that the questions of "how well did the LLM do?" and "how does 'grading' work in this app?" seem to have gone out the window when HN readers see something shiny.
Some of the issues could be resolved with better prompting (it was biased to always interpret every comment through the lens of predictions) and LLM-as-a-judge, but still. For example, Anthropic's Deep Research prompts sub-agents to pass original quotes instead of paraphrasing, because it can deteriorate the original message.
Some examples:
Swift is Open Source (2015)
===========================
> “It could become a serious Javascript competitor due to its elegant syntax, the type safety and speed.”
> Great news! Coding in Swift is fantastic and I would love to see it coming to more platforms, maybe even on servers. It could become a serious Javascript competitor due to its elegant syntax, the type safety and speed.
How to be like Steve Ballmer (2015)
===================================
Most wrong
----------
> corford (grade: D) (defending Ballmer’s iPhone prediction):
> Cited an IDC snapshot (Android 79%, iOS 14%) and suggested Ballmer was “kind of right” that the iPhone wouldn’t gain significant share.
> In 2025, iOS is one half of a global duopoly, dominates profits and premium segments, and is often majority share in key markets. Any reasonable definition of “significant” is satisfied, so Ballmer’s original claim—and this defense of it—did not age well.
> And in a funny sort of way he was kind of right :) http://www.forbes.com/sites/dougolenick/2015/05/27/apple-ios...
> Android: 79% versus iOS: 14%
> volandovengo (grade: C+) (ill-equipped to deal with Apple/Google):
>
> Wrote that Ballmer’s fast-follower strategy “worked great” when competitors were weak but left Microsoft ill-equipped for “good ones like Apple and Google.”
> This is half-true: in smartphones, yes. But in cloud, office suites, collaboration, and enterprise SaaS, Microsoft became a primary, often leading competitor to both Apple and Google. The blanket claim underestimates Microsoft’s ability to adapt outside of mobile OS.
> Despite his public perception, he's incredibly intelligent. He has an IQ of 150.
>
> His strategy of being a fast follower worked great for Microsoft when it had crappy competitors - it was ill equipped to deal with good ones like Apple and Google.
[Let's Encrypt] Entering Public Beta (2015)
===========================================
- niutech: F "(endorsed StartSSL and WoSign as free options; both were later distrusted and effectively removed from the trusted ecosystem)"
> There are also StartSSL and WoSign, which provide the A+ certificates for free (see example WoSign domain audit: https://www.ssllabs.com/ssltest/analyze.html?d=checkmyping.c...)
>
> pjbrunet: F (dismissed HTTPS-by-default arguments as paranoid, incorrectly asserted ISPs had stopped injection, and underestimated exactly the use cases that later moved to HTTPS)
> "We want to see HTTPS become the default."
>
> Sounds fine for shopping, online banking, user authorizations. But for every website? If I'm a blogger/publisher or have a brochure type of website, I don't see point of the extra overhead.
>
> Update: Thanks to those who answered my question. You pointed out some things I hadn't considered. Blocking the injection of invisible trackers and javascripts and ads, if that's what this is about for websites without user logins, then it would help to explicitly spell that out in marketing communications to promote adoption of this technology. The free speech angle argument is not as compelling to me though, but that's just my opinion.
I mean, we could go on, there are many others like these.
I understand this is just a fun exercise so it’s basically what LLMs are good at - generating plausible sounding stuff without regard for correctness. I would not extrapolate this to their utility on real evaluation tasks.
I would grade this article B-, but then again, nobody wrote it... ;)
It would be very interesting to see this applied year after year to see if people get better or worse over time in the accuracy of their judgments.
It would also be interesting to correlate accuracy to scores, but I kind of doubt that can be done. Between just expressing popular sentiment and the first to the post people getting more votes for the same comment than people who come later it probably wouldn’t be very useful data.
Seriously, while I find this cool and interesting, I also fear how these sorts of things will work out for us all.
It's a shame that maintaining the web is so hard that only a few websites are "good citizens". I wish the web was a -bit- way more like git. It should be easier to crawl the web and serve it.
Say, you browse and get things cached and shared, but only your "local bookmarks" persist. I guess it's like pinning in IPFS.
It is not possible right now to make hosting democratized/distributed/robust because there's no way for people to donate their own resources in a seamless way to keeping things published. In an ideal world, the internet archive seamlessly drops in to serve any content that goes down in a fashion transparent to the user.
It's not hard actually. There is a lack of will and forethought on the part of most maintainers. I suspect that monetization also plays a role.
Keeps the spotlight on carefully protected communities like this one.
This only manipulates the children references though, never the item ID itself. So if you have the item ID of an item (submission, comment, poll, pollItem), it'll be available there as long as moderators don't remove it, which happens very seldom.
What do you mean?
Besides, in my experience, only a tiny fraction of HN comments can be interpreted as falsifiable predictions.
Instead I would recommend learning about calibration [2] and ways to improve one's calibration, which will likely lead you into literature reviews of cognitive biases and what we can do about them. Also, jumping into some prediction markets (as long as they don't become too much of a distraction) is good practice.
If you dig in, there are substantial flaws in the project's analysis and framing, such as the definition of a prediction, assessing comments, data quality overall, and more. Go spelunking through the comments here and notice people asking about methodology and checking the results.
Social science research isn't easy; it requires training, effort, and patience. I would be very happy if Karpathy added a Big Flashing Red Sign to this effect. It would raise awareness and focus community attention on what I think are the hardest and most important aspects of this kind of project: methodology, rigor, criticism, feedback, and correction.
And scroll down to the bottom.
According to the ratings for example, one person both had extremely racist ideas but also made a couple of accurate points about how some tech concepts would evolve.
I try to temper my tendency to believe the Halo effect with Warren Buffett's notion of the Circle of Competence; there is often a very narrow domain where any person can be significantly knowledgeable.
The EU may give LLM surveillance an F at some point.
Your past thoughts have been dredged up and judged.
For each $TOPIC, you have been awarded a grade by GPT-5.1 Thinking.
Your grade is based on OpenAI's aligned worldview and what OpenAI's blob of weights considers Truth in 2025.
Did you think well, netizen?
Are you an Alpha or a Delta-Minus?
Where will the dragnet grading of your online history happen next?
I'd expect de-biasing would deflate grades for well known users.
It might also be interesting to use a search-grounded model that provides citations for its grading claims. Gemini models have access to this via their API, for example.
I [as a human] also do the same thing when observing others in IRL and forum interactions. Reputation matters™
----
A further question is whether a bespoke username could influence the bias of a particular comment (e.g. A username of something like HatesPython might influence the interpretation of that commenter's particular perception of the Python coding language, which might actually be expressing positivity — the username's irony lost to the AI?).
That said, I understand the concept and love what you did here. By this being exposed to the best disinfectant, I hope it will raise awareness and show how people and corporations should be careful about its usage. Now this tech is accessible to anyone, not only big techs, in a couple of hours.
It also shows how we should take with a grain of salt the result of any analysis of such scale by a LLM. Our private channels now and messages on software like Teams and Slack can be analyzed to hell by our AI overlords. I'm probably going to remove a lot of things from cloud drives just in case. Perhaps online discourse will deteriorate to more inane / LinkedIn style content.
Also, I like that your prompt itself has some purposefully leaked bias, which shows other risks—¹for instance, "fsflover: F", which may align the LLM to grade worse the handles that are related to free software and open source).
As a meta concept of this, I wonder how I'll be graded by our AI overlords in the future now that I have posted something dismissive of it.
¹Alt+0151
* ignore comments that do not speculate on something that was unknown or had not achieved consensus as of the date of yyyy-mm-dd
* at the same time, exclude speculations for which there still isn’t a definitive answer or consensus today
* ignore comments that speculate on minor details or are stating a preference/opinion on a subjective matter
* it is ok to generate an empty list of users for a thread if there are no comments meeting the speculation requirements laid out above
* etc
But it reminds me that I miss Manishearth's comments! What ever happened to him? I recall him being a big rust contributor. I'd think he'd be all over the place, with rust's adoption since then. I also liked tokenadult. interesting blast from the past.
I wonder why ChatGPT refused to analyze it?
The HN article was "Brazil declares emergency after 2,400 babies are born with brain damage" but the page says "No analysis available".
Alternate metaphor: evil catnip - https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
But yesterday's thread and this one are clearly exceptions—far above the median. https://news.ycombinator.com/item?id=46212180 was particularly incredible I think!
A personal favourite is “the contrarian dynamic”.
Do you have a list of those at the ready or do you just remember them? If you feel like sharing, what’s your process and is there a list of those you’d make public?
I imagine having one would be useful, e.g. for onboarding someone like tomhow, though that doesn’t really happen often.
The company has changed and it seems the mission has as well.
> The original “non‑profit, open, patents shared” promise now reads almost like an alternate timeline. Today OpenAI is a capped‑profit entity with a massive corporate partner, closed frontier models, and an aggressive product roadmap.
A non trivial amount of people get laid off, likely due to a finanical crisis which is used as an excuse for companies scale up use of AI. Good chance the financial crisis was partly caused by AI companies, which ironically makes AI cheaper as infra is bought up on the cheap (so there is a consolidation, but the bountiful infra keeps things cheap). That results in increased usage (over a longer period of time). and even when the economy starts coming back the jobs numbers stay abismal.
Politics are divided into 2 main groups, those who are employed, and those who are retired. The retired group is VERY large, and has alot of power. They mostly care about entitlements. The employed age people focus on AI which is making the job market quite tough. There are 3 large political forces (but 2 parties). The Left, the Right, and the Tech Elite. The left and the right both hate AI, but the tech elite though a minority has outsized power in their tie breaker role. The age distributions would surprise most. Most older people are now on the left, and most younger people are split by gender. The right focuses on limiting entitlements, and the left focuses on growing them by taxing the tech elite. The right maintains power by not threatening the tech elite.
Unlike the 20th century America is a more focused global agenda. We're not policing everyone, just those core trading powers. We have not gone to war with China, China has not taken over Taiwan.
Physical robotics is becoming a pretty big thing, space travel is becoming cheaper. We have at least one robot on an astroid mining it. The yield is trivial, but we all thought it was neat.
Energy is much much greener, and you wouln't have guessed it... but it was the data centers that got us there. The Tech elite needed it quickly, and used the political connections to cut red tape and build really quickly.
I know that "X is destroying democracy, vote for Y" has been a prevalent narrative lately, but is there any evidence that it's true? I get that it's death by a thousand cuts, or "one step at a time" as they say.
1. https://karpathy.ai/hncapsule/2015-12-08/index.html#article-...
I scrolled to the bottom of the hall of fame/shame and saw that entry #1505 and 3 F's and a D, with an average grade of D+ (1.46).
No grade better than a D shouldn't average to a D+, I'd expect it to be closer to a 0.25.
That's interesting. I wouldn't have thought that a decent generic forward future predictor would be possible.
They were right, Duolingo.
Forecasting and the meta-analysis of forecasters is fairly well studied. [1] is a good place to start.
>In February 2023, Superforecasters made better forecasts than readers of the Financial Times on eight out of nine questions that were resolved at the end of the year.[19] In July 2024, the Financial Times reported that Superforecasters "have consistently outperformed financial markets in predicting the Fed's next move"
>In particular, a 2015 study found that key predictors of forecasting accuracy were "cognitive ability [IQ], political knowledge, and open-mindedness".[23] Superforecasters "were better at inductive reasoning, pattern detection, cognitive flexibility, and open-mindedness".
I'm really not sure what you want me to take from this article? Do you contend that everyone has the same competency at forecasting stock movements?
This seems to be the result of the exercise? No evaluation?
My concern is that, even if the exercise is only an amusing curiosity, many people will take the results more seriously than they should, and be inspired to apply the same methods to products and initiatives that adversely affect people's lives in real ways.
That will most definitely happen. We already have known for awhile that algorithmic methods have been applied "to products and initiatives that adversely affect people's lives in real ways", for awhile: https://www.scientificamerican.com/blog/roots-of-unity/revie...
I guess the question is if LLMs for some reason will reinvigorate public sentiment / pressure for governing bodies to sincerely take up the ongoing responsibility of trying to lessen the unique harms that can be amplified by reckless implementation of algorithms.
> I was reminded again of my tweets that said "Be good, future LLMs are watching". You can take that in many directions, but here I want to focus on the idea that future LLMs are watching. Everything we do today might be scrutinized in great detail in the future because doing so will be "free". A lot of the ways people behave currently I think make an implicit "security by obscurity" assumption. But if intelligence really does become too cheap to meter, it will become possible to do a perfect reconstruction and synthesis of everything. LLMs are watching (or humans using them might be). Best to be good.
We are doing something very *very* wrong if we are operating under the belief that this future is unavoidable. That future is simply unacceptable.
To properly execute this idea rather than to just toss it off without putting in the work to make it valuable is exactly what irritates me about a lot of AI work. You can be 900 times as productive at producing mental popcorn, but if there was value to be had here we're not getting it, just a whiff of it. Sure, fun project. But I don't feel particularly judged here. The funniest bit is the judgment on things that clearly could not yet have come to pass (for instance because there is an exact date mentioned that we have not yet reached). QA could be better.
I'm not worried about this project but instead harvesting, analyzing all that data and deanonymizing people.
That's exactly what Karparthy is saying. He's not being shy about it. He said "behave because the future panopticon can look into the past". Which makes the panopticon effectively exist now.
Be good, future LLMs are watching
...
or humans using them might be
The idea that we have to behave as if we're being actively watched by the government is literally the setting of 1984 lol. The idea that we have to behave that way now because a future government will use the Panopticon to look into the past is absolutely unhinged. You don't even know what the rules of that world will be!
Did we forget how unhinged the NSA's "harvest now, decrypt later" strategy is? Did we forget those giant data centers that were all the news talked about for a few weeks?
That's not the future I want to create, is it the one you want?
To act as if that future is unavoidable is a failure of *us*
If you believe in God of a certain kind, you don't think that being judged for your sins is unacceptable or even good or bad in itself, you consider it inevitable. We have already talked it over for 2000 years, people like the idea.
God is different though. People like God because they believe God is fair and infallible. That is not true for machines nor men. Similarly I do not think people will like this idea. I'm sure there will be some but look at people today and their religious fever. Or look in the past. They'll want it, but it is fleeting. Cults don't last forever, even when they're governments. Sounds like a great way to start wars. Every one will be easily justified
I've found the opposite, since these models still fail pretty wildly at nuance. I think it's a conceptual "needle in the haystack sort of problem.
A good test is to find some thread where there's a disagreement and have it try to analyze the discussion. It will usually strongly misrepresent what was being said, by each side, and strongly align with one user, missing the actual divide that's causing the disagreement (a needle).
It requires that the discussion has nuance, to see the failure. Gemini is, by far the, worst at this (which fits my suspicion that they heavily weighted reddit posts).
I don't think this is all that strange though. The human, on one side of the argument, is also missing the nuance, which is the source of the conflict. Is there a belief that AI has surpassed the average human, with conversational nuance!?
reading from the end isn't really useful, y'know :)
Shades of Roko's Basilisk!
Now let's make a Chrome extension that subtly highlights these users' comments when browsing HN.
s/"free"/stolen/
The bit about college courses for future prediction was just silly, I'm afraid: reminds me of how Conan Doyle has Sherlock not knowing Earth revolves around the Sun. Almost all serious study concerns itself with predicting, modelling and influence over the future behaviour of some system; the problem is only that people don't fucking listen to the predictions of experts. They aren't going to value refined, academic general-purpose futurology any more than they have in the past; it's not even a new area of study.
it's great that this was produced in 1h with 60$. This is amazing to create small utilities, explore your curiosity, etc.
But the site is also quite confusing and messy. OK for a vibe coded experiment, sure, but wouldn't be for a final product. But I fear we're gonna see more and more of this. Big companies downsizing their tech departments and embracing vibe coded. Comparing to inflation, shrinkflation and skimpflation/ enshittification , will we soon adopt some word for this? AIflation? LLMflation?
And how will this comment score in a couple of years? :)
I took the narcissistic approach of searching for myself. Here's a grade of one of my comments[1]:
>slg: B- (accurate characterization of PH’s “networking & facade” feel, but implicitly underestimates how long that model can persist)
And here's the actual comment I made[2]:
>And maybe it is the cynical contrarian in me, but I think the "real world" aspect of Product Hunt it what turned me off of the site before these issues even came to the forefront. It always seemed like an echo chamber were everyone was putting up a facade. Users seemed more concerned with the people behind products and networking with them than actually offering opinions of what was posted.
>I find the more internet-like communities more natural. Sure, the top comment on a Show HN is often a critique. However I find that more interesting than the usual "Wow, another great product from John Developer. Signing up now." or the "Wow, great product. Here is why you should use the competing product that I work on." that you usually see on Product Hunt.
I did not say nor imply anything about "how long that model can persist", I just said I personally don't like using the site. It's a total hallucination to claim I was implying doom for "that model" and you would only know that if you actually took the time to dig into the details of what was actually said, but the summary seems plausible enough that most people never would.
The LLM processed and analyzed a huge amount of data in a way that no human could, but the single in-depth look I took at that analysis was somewhere between misleading and flat out wrong. As I said, a perfect example of what LLMs do.
And yes, I do recognize the funny coincidence that I'm now doing the exact thing I described as the typical HN comment a decade ago. I guess there is a reason old me said "I find that more interesting".
[1] - https://karpathy.ai/hncapsule/2015-12-18/index.html#article-...
With that context, if someone were to read your comment and be asked 'does this person think the product's model is viable in the long run' I think a lot of people would respond 'no'.
The LLM isn't misinterpreting the text, it's just representing people who misinterpreted the text isn't the defense you seem to think it is.
Compared to what happens next? Does tptacek's commentary become market signal equivalent to the Fed Chair or the BLS labor and inflation reports?
For instance, one of the unfortunate aspects of social media that has become so unsustainable and destructive to modern society is how it exposes us to so many more people and hot takes than we have ability to adequately judge. We're overwhelmed. This has led to conversation being dominated by really shitty takes and really shitty people, who rarely if ever suffer reputational consequence.
If we build our mediums of discourse with more reputational awareness using approaches like this, we can better explore the frontier of sustainable positive-sum conversation at scale.
Implementation-wise, the key question is how do we grade the grader and ensure it is predictable and accurate?
https://news.ycombinator.com/item?id=46222523
LLM can't grade reliably human text. It doesn't understand it.
It does seem better than just upvotes and downvotes though.
I cannot believe this is just put out there unexamined of any level of "maybe we shouldn't help this happen". This is complete moral abdication. And to be clear, being "good" is no defense. Being good often means being unaligned with the powerful, so being good is often the very thing that puts you in danger.
I would read his "Best to be good." as a warning or reminder that everything you do or say online will be collected and analyzed by an "intelligence". You can't count on hiding amongst the mass of online noise. Imagine if someone were to collect everything you've written or uploaded to the internet and compiled it into a long document. What sort of story would that tell about who you are? What would a clever person (or LLM) be able to do with that document?
If you have any ideas on how to stop everyone from building the torment nexus, I am willing to listen.
1. Don't build the Torment Nexus yourself. Don't work for them and don't give them your money.
2. When people you know say they're taking a new job to work at Torment Nexus, act like that's super weird, like they said they're going to work for the Sinaloa cartel. Treat rich people working on the Torment Nexus like it's cringe to quote them.
3. Get hostile to bots. Poison the data. Use AdNauseum and Anubis.
4. Give your non-tech friends the vague sense that this stuff is bad. Some might want to listen more, but most just take their sense of what's cool and good from people they trust in the area.
While I don't have a general solution, I do believe that the solution will need to be multi-faceted and address multiple aspects of the technologies enabling this. My first step would be for society to re-evaluate and shift its views towards information, both locally and internationally.
For example, if you proposed to get rid of all physical borders between countries, everyone would likely be aghast. Obviously there are too many disagreements and conflicting value sets between countries for this to happen. Yet in the west we think nothing have having no digital information borders, despite the fact that the lack of them in part enables this data collection and other issues such as election interference. Yes, erecting firewalls is extremely unpalatable to people in the west, but is almost certainly part of the solution on the national level. Countries like China long ago realized this, though they also use firewalls as a means of control, not just protection (it doesn't have to be this way).
But within countries we also need to shift away from a default position of "I have the right to say whatever I want so therefore I should" and into one of "I'm not putting anything online unless I'm willing to have my employer, parents, literally everyone, read it." Also, we need to systematically attack and dismantle the advertising industry. That industry is one of the single biggest driving factors behind the extreme systematic collection and correlation of data on people. Advertising needs to switch to a "you come to me" approach not a "I'm coming to you" approach.
Don't know why that just popped into my head.
Anyway, back to work trying to make my millions using Opus and such.
[0] https://old.reddit.com/r/funny/comments/1pj5bg9/al_companies...
We can't start clutching our pearls now as if programmatic mass surveillance hasn't been running on all cylinders for over 20 years.
Don't get me wrong, we should absolutely care about this, everyone should. I'm just saying any vague gestures at imminent privacy-doom thanks to LLMs is liable to be doing some big favors of inadvertently sanitizing the history of prior (and still) egregious privacy offenders.
I'm just suggesting more "Yes and" and less "pearl clutching" is all.
Governments around the world have profiles on people and spiders that quietly amass the data that continuously updates those profiles.
It's just a matter of time before hardware improves and we see another holocaust scale purge facilitated by robots.
Surveillance capitalism won.
* Nvidia GPUs will see heavy competition and most chat-like use-cases switching to cheaper models and inference-specific-silicon but will be still used on the high end for critical applications and frontier science
* Most Software and UIs will be primarily AI-generated. There will be no 'App Stores' as we know them.
* ICE Cars will become niche and will be largely been replaced with EVs, Solar will be widely deployed and will be the dominate source of power
* Climate Change will be widely recognized due to escalating consequences and there will be lots of efforts in mitigations (e.g, Climate Engineering, Climate-resistant crops, etc).