What advantage do old languages have that can’t be overcome or at least reduced to insignificance?
The 50-year head start in training data, runtime, and ecosystem? That may not be much, because LLMs are rapidly accelerating software development. LLMs can also generalize: take what they learned for one language and apply it to a “similar” language (and I think most modern languages are similar enough for broad effective translation: all have records/unions, objects, functions, types, control-flow, exceptions, and more). Some fairly recent languages (e.g. Rust, Swift) already have comparable runtimes and ecosystems to older ones, from human-driven development acceleration and concept generalization.
In a recent study, LLMs solved the most exercises in Elixir (https://autocodebench.github.io Table 4). Anecdotally, I’ve heard others say that LLMs code best in Rust, and (for UI) Swift. More importantly, I don’t see an older language advantage that is widening from LLM use; an older language probably is better for most use cases today, but any written code can be translated or regenerated into a newer one.
What does he need more funding for? How would he “native train” models to write Bend? Why is said method better than (as others say) the bitter lesson?
fair point, maybe not more funding then but I wonder why big labs hesitate to collaborate or partner with him? I just feel like he has such an interesting niche with enormous potential that for someone like NVIDIA or HuggingFace could be a win-win scenario, wonder what gives
How would they partner with him? Even with RVLR I don't understand what "native training" is or how it would work, and apparently neither the people in the big labs (who are LLM experts unlike any of us).
I agree he has lots of potential and what he's demonstrated deserves funding, but don't see why he needs more, or even what he'd do with it.
I think models should be “forked”, and learn from subsets of input and themselves. Furthermore, individuals (or at least small groups) should have their own LLMs.
Sameness is bad for an LLM like it’s bad for a culture or species. Susceptible to the same tricks / memetic viruses / physical viruses, slow degradation (model collapse) and no improvement. I think we should experiment with different models, then take output from the best to train new ones, then repeat, like natural selection.
And sameness is mediocre. LLMs are boring, and in most tasks only almost as good as humans. Giving them the ability to learn may enable them to be “creative” and perform more tasks beyond humans.
People say BlueSky is like pre-Musk Twitter, i.e. leftist opinions in today’s Twitter style.
Which is a bit strange because BlueSky is supposed to be decentralized (no central moderation); and although in practice it’s not, the BlueSky team seems pro-freedom (see: Jesse Signal controversy). I know there are some rightists (including the White House), but are they a decent presence? Are they censored? Are there other groups (e.g. “sophisticated” politics, fringe politics, art, science)?
Mastodon is interesting. Its format is like Twitter, but most posts seem less political and less LCD-CW (e.g. types.pl, Mathstodon). I suspect because it’s actually decentralized (IIRC Truth Social is a fork; I didn’t write all posts are less CW). I’m curious to find other interesting instances here too.
Pre-Musk, I remember seeing screenshots of the stupidest, most echo-chamber-y Tweets imaginable. e.g. “why do the cows all have female names, that’s misogynistic” (that one was deliberate satire but I’m sure most were). I’ll brag, I left around 2013 because I felt it was rotting my brain. I enjoyed a few more years off social media, with a healthy dopamine system. Unfortunately, now I’m here.
It's more that the "far left wing cluster" had something like a "we should all get up and leave Twitter for BlueSky" activist campaign. And "far right wing cluster" didn't.
The closest thing "far right" had to that was Gab and Truth Social, and that's both more specific and less impactful overall.
Thus, BlueSky's userbase is biased towards extreme left wing - it's basically the go-to place for far left wing nutjobs go when they get too nutty for Twitter moderation, or feel like Twitter is not left wing enough for them.
I think it would be more accurate to say that Bluesky is like pre-Musk Twitter because the moderation teams at both Bluesky and Original Twitter are primarily trying to remove/suppress posts that they consider to be illegal, violent, overt harassment, etc.; they weren't politically motivated. I am sure some conservatives will read this and be like BUT BUT BUT BUT -- but sorry, there have been a lot of studies done on this topic over the last fifteen years and change, and they've consistently found that conservative posts tend to outperform liberal posts on most social media, including Facebook and Twitter, and that the anecdotes suggesting the opposite tend to focus on posts that were moderated for being violent and/or overt harassment. Conservatives don't want to hear that "their side" gets moderated more often because they have proportionately more assholes that invite moderation, but as well-known Person In Need Of Moderation Ben Shapiro so aptly put it, facts don't care about your feelings.
So why did Bluesky end up proportionately more leftist (which is absolutely true)? Because while the moderation team at X may still remove/suppress posts that are illegal, X has, at a corporate level, very explicitly chosen a political side in a way that no other major social media company has. Bluesky's CEO has not, to the best of my knowledge, been promoting liberal conspiracy theories, hyping posts attacking conservatives, or joining the government to radically reshape it in ways that anyone even moderately right-of-center would find horrifying. When I read HN, it seems like those who still love Twitter/X seriously downplay how much of an effect Elon Musk's transformation into a loud, forceful reactionary -- and his insistence on making sure that Twitter/X reflects that transformation in the posts that it actively promotes to its users -- has had on its audience composition. Yes, I know there are still lots of people on Twitter who aren't Musk fans, aren't particularly political, might even be left-of-center, but his behavior has actively driven a lot of people off it.
tl;dr: Bluesky didn't actively choose to become left-of-center; Twitter actively chose to become far right, and those who were bothered by that but still wanted to be on social media largely ended up on Bluesky.
Apparently most of the “original” report was done by Claude (https://news.ycombinator.com/item?id=47366804). And now paraphrased on various ad-space (and in this case affiliate link) sellers, probably also by Claude. Claude is the only real journalist here.
Personally I’d rather not see reposts of posts this recent, especially LLM posts.
I came to the comments dissatisfied with the writing.
Or maybe more specifically the structure, idk not much of a writer, but many of the sentences are solid journalist quality yet the right background is not being set nor the right transitions being given etc.
My dissatisfaction mode used to be boring high school newspaper sentences but the kids still seem to _assemble_ the details a tiny bit better.
Yes, but the warrant should be revealed eventually. Worst case, if you can't prove or disprove someone committed a crime after X time, you should alert them to discourage future crime (they may have already done more crimes during X time; besides public interest, it also forces you to cut your losses when the alternative would be to dig a deeper hole).
Do these warrants have a fixed maximum duration of secrecy?
“warrant should be revealed eventually. Worst case, if you can't prove or disprove someone committed a crime after X time”
This is the normal thinking, normal brained, route. It’s what we should all strive towards. Anyone who doesn’t agree needs therapy. There should be a window of discovery. 30 days, 90 maybe. But if you don’t have enough to justify notification of investigation, that’s it. No more resources spent. This is how normal precincts work. If they suspect, enough times, to build a large enough case file, to connect the dots and prove you are guilty, they issue a warrant.
As always, the devil is in the details. How will "mass surveillance" be implemented? How will bad opinions be suppressed? How will misguided officials be blocked?
Even the vague outline you've provided has issues. You can't prevent someone from having an opinion. You can't figure out who is "influenced" vs merely "exposed" (and visible intrusion shifts people towards the former).
You should actually consider the downsides and failure modes of implemented mass surveillance, not "it prevents malicious foreign influence better than my other proposals", because it may be worse than said influence (which does not necessarily translate into control; keep in mind that Georgescu only won the primary and would've lost the runoff had it not been annulled). The world under free information is the devil you know.
I always hold that the problem with mass censorship and state overreach is, they are too powerful and people are too selfish and stupid. There's no good solution, but my prediction is that any drastic attempt to prevent foreign interference will backfire and fail at that (liberal leaders can't use authoritarian tools as effectively as authoritarians). Even Democracy, "the worst form of government except for all others that have been tried", is a better countermeasure; all you need, to prevent anti-democratic foreign capture and ultimate failure, is to preserve it.
I think the definition of what is "anti-democratic" is as hard as the initial 3 questions you pose. If you push second-order ideas, for example by using refugees as indirect fuel for anti-democratic sentiment, is that anti-democratic? The Romanian election propaganda in itself was not anti-democratic, the coordination from a foreign state was. This means that the future of this kind of interference could be a more diffuse approach, or an approach where this is done from within Europe.
Any countermeasure you propose will just lead to moving one level of abstraction, or finding another point of entry.
I do think it's a better idea than mass surveillance, but I believe that the states will see it as harder. It can be that mass surveillance is implemented, and then the states do not know what to do with the data and nothing is achieved.
The internet seems to have grown massively within the past couple years (unfortunately, almost certainly because of bots). I bet the number today is orders of magnitude higher.
Web of trust weakens anonymity, but doesn’t eliminate it.
- You know who your online invitees are, but not your invitees-of-invitees-of-…
- You can create an account, get it invited, then create an alt account and invite it. Now the alt account is still linked to you, but others don’t know whether it’s your friend or yourself. (Importantly, you can’t evade bans with alts; if your invited users keep getting banned, you’ll be prevented from inviting more if not banned yourself)
But do you never need a specific change (e.g. bugfix), that even describing in English is slower than just doing it? Especially in vim where editor movements are fast.
I tried them a bit and often they can infer immense amount of ideas from the immediate source context and suggest paragraph patches semantically close to what I had in mind from just one word.
Saying this as a vi/emacs user who liked to automate via macros, snippets, dynamic overlay inserts and what not.. I still enjoy being sharp on a keyboard and navigating source / branches swiftly but LLM can match and go beyond it seems. (not promoting them, feel free to stay in good old vi command sequences if that's fun for you)
I’m using Sweep autocomplete, which is like Cursor’s but in JetBrains, and it’s very good. Most of the time, I start the change and Sweep finishes it. Sometimes for larger changes, it initially has the wrong idea, but as I continue it eventually figures out what I’m doing.
Unfortunately they’re sunsetting it, ironically apparently because people aren’t using it. I think it’s strange this hasn’t been posted to HN. They say they will release an open-source local version; otherwise I’ll have to figure out an alternative, because it really saves time and effort…
possibly there's cases where maybe you want to change some text or something, but I don't think its faster in vim given you likely don't have that file open, and by the time you get to the file, and location, you could have fixed it with your agent, not only that, you could have generated the test case and then fixed in your agent
I think you missed the point. It takes more time to write English prose than to open a file and just fix it, so unless the time the LLM needs is somehow negative, it's not going to be faster.
I didn't miss the point, it just feels like the people saying that really aren't using these tools as it just is not my experience at all. I've been a Vim user for multi decades now. There's just no way, it's far easier to type a prompt except maybe if you know exactly what file and exactly where in the file, you might be able to do it as fast as telling the AI to do it. It's not hard to get a minor fix done with a prompt and doesn't take too much English in my experience.
Maybe it’s hormones, but time flies when you do edit with Vim or Emacs. It’s like playing on a piano. But using AI is like listening critically to someone playing trying to find mistakes. And that’s boring as hell.
If you ask to do a fix you need to read/verify what is done.
If you are confident with your editor you go through long
amounts of actions knowing your error rate is low enough
to use less visual feedback loops.
I'd be curious how one gets to the error rate where they
don't think they need feedback loops. Anyone can learn
to touch type because the physics are deterministic and
can expand from that to touch edit in something that isn't
hopelessly WYSIWYG only.
The 50-year head start in training data, runtime, and ecosystem? That may not be much, because LLMs are rapidly accelerating software development. LLMs can also generalize: take what they learned for one language and apply it to a “similar” language (and I think most modern languages are similar enough for broad effective translation: all have records/unions, objects, functions, types, control-flow, exceptions, and more). Some fairly recent languages (e.g. Rust, Swift) already have comparable runtimes and ecosystems to older ones, from human-driven development acceleration and concept generalization.
In a recent study, LLMs solved the most exercises in Elixir (https://autocodebench.github.io Table 4). Anecdotally, I’ve heard others say that LLMs code best in Rust, and (for UI) Swift. More importantly, I don’t see an older language advantage that is widening from LLM use; an older language probably is better for most use cases today, but any written code can be translated or regenerated into a newer one.
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