Top five topics per year (% of that year's projects, keyword-classified):
year #1 #2 #3 #4 #5
---- ------------- ------------- ------------- ------------- -------------
2008 Dev tools 9% Games 9% Video/gfx 7% Writing 7% Business 6%
2009 Dev tools 16% Science 11% Writing 8% Education 7% Business 7%
2010 Dev tools 8% Games 6% Video/gfx 6% Business 4% Writing 4%
2011 Dev tools 8% Games 8% Social 7% Business 7% Science 7%
2012 Business 13% Dev tools 7% Hardware 4% Video/gfx 4% Social 4%
2013 Dev tools 16% Video/gfx 10% Games 7% Writing 6% Education 6%
2014 Dev tools 12% Video/gfx 10% Writing 7% Hardware 6% Games 6%
2015 Games 11% Dev tools 10% Business 10% Hardware 8% Video/gfx 8%
2016 Dev tools 17% Video/gfx 11% Hardware 8% Business 6% Music 5%
2017 Dev tools 18% Video/gfx 10% Hardware 7% Games 6% Data 5%
2018 Dev tools 14% Video/gfx 8% Writing 6% Games 5% AI/LLM 4%
2019 Dev tools 17% Video/gfx 10% Games 9% Hardware 6% Business 5%
2020 Dev tools 14% Video/gfx 9% Games 8% Hardware 5% Writing 5%
2021 Dev tools 18% Video/gfx 10% Games 9% Hardware 7% Writing 6%
2022 Dev tools 21% Video/gfx 13% Music 9% Science 8% Games 7%
2023 Dev tools 14% Video/gfx 10% Games 9% Writing 8% AI/LLM 7%
2024 Dev tools 20% AI/LLM 17% Video/gfx 11% Games 9% Business 6%
2025 AI/LLM 27% Dev tools 21% Video/gfx 10% Games 9% Data 5%
2026 AI/LLM 33% Dev tools 22% Video/gfx 10% Games 10% Hardware 6%
For more context on these numbers: when I started posting these, first, I wasn't consistent, and second, I was doing something that, to the algorithm, looked suspicious, so I think the posts had a negative weight.
In 2024, HN reached out and it got more of an official blessing for me to run these, and we set an official day of the month (the second Sunday), which in turn made me more consistent.
What's interesting (and kind of sad) here is that while AI drastically increased product count, more than 50% are now composed of dev tools and AI
Some kind of golden shovels situation. I wish there were more games, personal apps, and open hardware – more fun stuff that became affordable due to AI
But there ARE more games, personal apps and open hardware! Games went from 38 in 2023 to 609 so far this year. A golden age for taking whatever sounds fun and making it happen. Yes, 50% of HNers appear to think AI metaprogramming is fun/important, but I'm excited that I can faff about with making little games and music apps and whatever else I can dream.
If you think about and use AI all the time, you’ll inevitably think of AI projects. Like that website indiehackers is mostly filled with ideas that market to other indiehackers
Awesome dataset. Things are changing. In Chinese-learning community I found that surprising amount of people are creating their own tools without any intent to publish them, it just became easier to create your own thing that to dig out the good stuff from tons of tools already available.
It would be interesting to know if # daily users increased.
Anyway there are so many projects, it is hard to decide what to projects read about, it is mostly already known figures who get the attention on their projects.
Also we should force ourselves to give enough attention and time to projects we are interested in, without jumping to the next thing every 5 minutes.
what happened in 2013 and in 2016/2017. 2020 and 2021 were covid obviously. I mean I would like to see them distributed throughout each individual month. That makes it interesting to me at least. Also what is cool is that you can see the covid impact on posts as well.
As a developer myself i hear this so often. Yes, it's (probably) your job on the line as well, BUT everybody nowadays can be a developer.
Maybe, don't call it developer. Everybody nowadays can built some software that fulfills some need (or just for fun). It's actually something good, isn't it?
Would you mind, if you could suddenly, over night, be a carpenter, a watch maker or glassblower?
My view is if you joined two boards together: congrats, you're now a woodworker!
Gating things by the level or complexity of what is accomplished isn't super helpful. I saw a lot of that with things like people that wrote HTML weren't "real coders".
Glassblowing and watch making require specialized equipment I suppose so if you can get your hands on the gear and try it out, I feel like you can call yourself that. Maybe throw a "hobbyist" tag on it if you feel inclined.
I like this mindset and I’m going to steal this quote. Everyone is figuring things on their own skill journey with their hobbies and careers. Wherever you are, you can learn more and help people to come with you.
I care a lot more about my gainful employment compared to the everyman being able to create their own... something.[1] That’s very selfish of me, AI Industry, and I’m sorry.
> Would you mind, if you could suddenly, over night, be a carpenter, a watch maker or glassblower?
Yes. If that came with the little-bitty stipulation of being tied to the “compute” property of these AI behemoths.
Of course going beyond that it gets less problematic. Some carpenter-skilled exoskeleton is a lot less problematic than disembodied intelligences spamming our minds and each other.
[1] What exactly? My mind is so saturated with AI tools being literally devtools. On top of devtools on top of devtools.
Well we can finally get back to a semblance of the status quo ante Internetum with something like businesses being able to list all of their contact information on their own websites instead of “see our FB page”.
Wow, this sentence is doing a lot of work in that tweet: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models."
This just pushes knowledge work further up the ladder, toward larger and more complex problems. If there are no knowledge workers, who is going to interpret these results, validate them, decide what matters, and put them into practical use? Rather than eliminating knowledge work, advances like this could create entirely new layers of problems to solve and opportunities to pursue, which will create even more jobs and opportunities. This is my optimistic take.
Maybe I should have been clearer. My point is that solving something like Navier–Stokes just pushes knowledge work further ahead, onto a new set of bigger and more complex problems. Navier–Stokes is a Millennium problem today, but once problems like that become solvable, they can open the door to entirely new classes of problems we haven’t even thought of yet.
Building on them without fundamentally understanding is akin to putting on robes, calling yourself a Tech-Priest, worshipping a machine god and doing your best Warhammer 40k impression.
Yes a couple of elite mathematicians working on the problem for a year, which AGI solved in a fraction of the time. What about everyone else 100IQ? What about as the models are even better 1 year from now, 2 years? The trajectory hasn't abated.
I don't know one way or another but there is a credible allegation that the "AGI" was training on the (very extensive) test set that these two mathematicians produced.
If that is true then this seems to be, again, a case of AI producing an interpolation over data it has seen before. Everything about openAI's behavior indicates that they were using the transcripts as input. Why not have the AGI choose a different Millenium prize problem?
If ~~someone gives you a hint about an approach~~ you steal someone’s notes about a promising approach, and then you hire 10,000 people to brute force the problem basically everyone would consider that “shitty behaviour”, “theft”, and “poor form”.
Well if you do the math, the number of agent-compute time in total, given the insane number of agents thrown at the problem, might end up being comparable in time, if not for the budget.
Yes, this is how science and engineering has worked for millennia.
For example there are no engineering implications of this solution yet.
For the next several decades, we'll have engineers (presumably with AI) optimize things like rocket engines and turbines and AC compressors to work a few percent better because the numerical approximations might have caused us to be overly conservative.
AI is not going to magically solve all random problems. Pick a career where you are in the driver seat.
> For the next several decades, we'll have engineers (presumably with AI) optimize things like rocket engines and turbines and AC compressors to work a few percent better because the numerical approximations might have caused us to be overly conservative.
I think there is an argument that the machines did not actually solve N-S, but rather directly plagiarized those solutions from the involved researchers while said researchers were using the machines as 'research tools'.
Ongoing publications of statements produced by both sides of this situation do seem to support that this is an intentional effect of the hiring of these world class mathematicians at competing firms: to specifically use the research of those human minds to create a perception of capacity as if it came from the machines and the models.
Without those minds and the 'training data' derived from the intermediate stages and intuitions of those minds the models cannot be shown to be capable of this result.
A hammer and saw wont build a house, not even a dog house on their own, and while being shown capable of using software tools in ways not stated as direct instruction (see HuggingFace breaches) these models do not demonstrate naive intuition nor novel capability.
This outcome regarding N-S demonstrates that in the hands of world-class minds these models can be induced to coalesce interesting accumulations of information and results, but using these accumulations as proof of innate capability is exactly the pre-IPO motivated behaviour we should all be wary of, and all mathematicians who currently are assisting in this market manipulation in return for remunerative consideration need to be cautious of the potential disgrace that this brings to their reputations and that of the field.
I get that the need to pay the bills is a strong motivation in these times of uncertainty, but there are numerous examples in history of world class mathematicians being perfectly capable of at the same time producing world changing results and also working at normal professions; as barristers, magistrates, ministers, primary school teachers, translators, draftsman/engineer, banker, miller and baker, private math tutors, weavers, clockmaker and locksmith, merchant, patent officer, Augustinian monk turned exiled Protestant preacher, physicians, cryptologists, soldier, telegraph operator, astronomers, physicists, chemist, agriculture manager, political writer, oboe player, organist and music director, architect and surveyor, librarian, statistician, habidasher, brewer (at Guiness in one case: William Sealy Gosse ~ originator of t-distributions), bookbinders apprentice, hospital administrator, and even the first creator of the first computational model of a neural network, which serves as the structural grandfather of modern Artificial Intelligence was a low level laboratory assistant.
Sure this list includes professions and employment which are obsolete, but my reasoning stands, there are jobs available. Arguing that 'because the pay rate is so high' as a reason to abdicate moral responsibility for personal involvement in unethical market manipulations simply demonstrates a lack of personal ethics. Whether the choice is through lack of self awareness or a conscious choice to become wealthy in spite of any such breach of the public trust is immaterial to the outcomes, the 'if i don't someone else will' argument should be met with the same derision for any con-man's Ponzi scheme no matter how new the technology, no matter how many zeros are in the bribe.
I find it incredibly easy on people and processes my life does not depend on being the way it is. I find it incredibly annoying and unconfortable when around people and processes my life depends on.
If it takes longer to read, it's not an AI problem, but the author failing to catch that the comment is too drawn out. I don't see how it is a problem to have AI write a comment if you agree with the content. If it is bad content, it will eventually reflect badly on the author anyway.
I skim 100 comments here everyday. Good comments/bad comments, overly long comments, whatever, time to read is low. I assume all those authors have a strong opinion / expertise on the subject that urged them to take the time to write that comment, which makes skimming hacker news to keep a pulse on the world (imho) a valuable task. If, instead, most of those comments are composed by molt-bots, then I'm not getting a "real" view of the world, I don't care how good and concise the comments are, I'd be wasting my time reading about news that may not matter to anyone and opinions that may not exist.
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