I can't recall or point out exactly when, but there is a stark before/after moment where the opinions of anything pg went from "Interesting and maybe true in some ways" to what we see today, lots of knee-jerk reactions and hardly any comments about the actual content.
Hazarding a guess, I think the moment Altman became the CEO and later during COVID, the sentiment seemed to have been shifting towards what we see today. But this is all based on hazy memory, rather than looking at the data. I'm sure there is a blog post waiting to be written about analyzing the sentiment of comments to PGs articles on HN, and you'll see a shift somewhere.
The sycophancy on HN is starting to break down because there is a higher proportion of users sceptical towards the outputs of the VC and wider investment world than ones who believe they're potential beneficiaries of it.
Tech industry people are becoming less interested in HN as a warm handshake into the startup world because, frequently, they're disgusted by it. And this reflects on the sentiments people post on PG's articles.
Increasingly if those at YC want the same kind of low-bar praise they got before, they will need to get it from machines.
Hard disagree. This submission is still being highly upvoted, while another recent post[1] on the harms caused by Graham’s fellows[2], with a fairly tame comment section, has been flagged. That is a constant on HN. It’s not a fluke, it’s as predictable as the sunrise and getting more pronounced.
I’m sure we’re both biased in our perceptions. Mine is that HN in general (certainly more than any other website) used to worship[3] everything he wrote, together with others like Musk, until things started to really go to shit and many eyes have been opened to the effects of the unfettered greed of rich tech guys out of touch with reality.[4]
[1]: https://news.ycombinator.com/item?id=49411762
[2]: A better English word is escaping me.
[3]: That word I choose hyperbolically but deliberately. It definitely was not “interesting and maybe true in some ways”, it was much more hardcore than that.
[4]: That is not “knee-jerk” but a slow realisation still ongoing.
I guess it depends on what submission you look at, previous comment of mine solely based on memory. Now I went to https://news.ycombinator.com/from?site=twitter.com/paulg, clicked "More" a bunch of times, and seems my memory was more or less correct, none of the submissions I clicked on are "pg worship" (hyperbolic or not). Just one example: https://news.ycombinator.com/item?id=19418701
Maybe you need to enable "Show Dead" or something? Pgs articles on HN definitely never was free of any critique in the HN comments, just like any article. Although I do agree with you that it used to be different than it is today, and same with Musk too, and Altman, and probably more individuals, where they were lauded before but now pretty much just mentioning them poisons the conversation.
That post has barely any points and comments. It’s not a good indicator of general sentiment, it’s just an indicator of people who were on HN at that time.
> Maybe you need to enable "Show Dead" or something?
I have it enabled.
> Pgs articles on HN definitely never was free of any critique in the HN comments, just like any article.
Of course. I very explicitly wrote “in general (certainly more than any other website)”. That does not mean “always”, or “never”. HN is not a hive mind, there’s never going to be 100% agreement. The general trend is what’s being discussed, and we both agree that in general the sentiment on Graham used to be higher. We’re just disagreeing (we may be able to find ourselves agreeing through tough thorough thought, though[1]) on where exactly it is now and how to interpret it.
[1]: Sorry, can’t believe there was a real organic opportunity to use that sentence, had to take it.
Hard agree! Though the discussion was short, I thank you for it. Good start of the week, I wish you a good one.
The above is, after all, the whole genesis of the word 'hacker'. We should celebrate that.
I tried to modify the embedding output of bert to make it generate box embeddings instead of point ones. At the time I had access to university provided A100 gpus but even with all that a training run took half a day. Models these days I don't think I can train it in any reasonable time with that much compute.
(As a TML person, I'm obviously biased, but I couldn't resist because of "tinkering").
TBF it's hard to imagine a real architecture change that wouldn't require a ton of compute, but you could certainly fine tune and play with different recipes, loss functions, etc. And Claude can carry you a lot of the way through doing this.
One fun task is to invent a tool and then train a small model to use it. You could export that small model and run it locally for free forever to do your thing. I think this is what a lot of Software Engineering will look like later.
There are a lot of other high level abstractions here to look at. Prime Intellect has one.
The other thing to play with is self-hosting small models, but IMO most of the interesting stuff is actually related to multi-gpu or multi-node inference so there's not necessarily a ton to learn here.
Vacuum tube computer: https://www.youtube.com/watch?v=KAlnJnYt5do
Making vacuum tubes in a garage: https://www.youtube.com/watch?v=-UEfqAWb3fE
"Barely?"
It's insane to lump vacuum tubes together with servers with 1 MB RAM. My first PC, which I used for a decade, had 640KB RAM. And that was an upgrade from 512 KB RAM. My other PC had only 128KB RAM. None of these were considered the equivalent of (by then long dead) vacuum tubes in their day.
You can get a lot done in 1 MB.
Don't many of the commercial ones prevent you from using them to build LLMs?
I would say the reason for the negativity is not because it's a bad idea for a project, or that doing projects in general is a bad idea (it's not!), it's because it's a very specific thing that is not for everyone. The best thing about computing is the low barriers to entry. You can basically work on anything that takes your fancy. So those who are interested in ML will be drawn to learn about LLMs. They don't need anyone to tell them to do it. Telling everyone to do it reminds me of the "just learn to code" stuff of a decade ago. No, please don't, please find something you enjoy.
No. But funnily enough that is a promise by some of the AI cretins and their boosters. Oh yeah best case scenario you learn how to build LLMs for us. We’ll employ you. And then ultimately that just becomes training data for the LLMs to do it themselves.
But why are people cynical? they ask.