Recent submissions

Comment · 9 months ago
No more questions, Your Honor. Forgive my joyful attitude, but it was your choice to participate in this discussion. As you know from your years and thousands of posts, HN threads are often ephemeral and short-lived - and this one is no exception. Or maybe not... because of your active self-defense posting here, I assume for the first time since the arrest. Now dozens of fellow (HN) hackers are querying your nicknames on Google, Algolia, and whatever else they have at hand. I'm not sure they'll find someone who genuinely fights for a more secure world. Or prove me wrong if you wish.
Comment · 9 months ago
Comment · 10 months ago
Thanks for sharing. After reading that comment, I realized we should encourage ourselves and others (who are more or less civilized human beings) to be the kind of person who wrote "that's a good thing..." - because fighting trolls is a game with unknown results, but encouraging people works much better. It doesn't always work, though, because sometimes the platform's nature prevents it. Like on Stack Overflow, where commenting on reactions will probably get you downvoted for being off-topic.
Comment · 10 months ago
It was funny. On a more serious note, if one works in a sphere where expanding with AI makes "good enough" documents, then I have bad news for him - the sphere has too much redundancy in the first place (the same place that was used for training). So no new information is created in millions of documents made by humans, and this was noticed by the training pattern recognition. You cannot do the same with historical texts; unless we live in a simulation with predictable random generators, the events are random, and there are no rules like "If the king's name starts with a G, he will likely die in the first week of October."
Comment · 10 months ago
> Modern LLMs suffer from hindsight contamination. GPT-5 knows how the story ends—WWI, the League's failure, the Spanish flu. This knowledge inevitably shapes responses, even when instructed to "forget.

> Our data comes from more than 20 open-source datasets of historical books and newspapers. ... We currently do not deduplicate the data. The reason is that if documents show up in multiple datasets, they also had greater circulation historically. By leaving these duplicates in the data, we expect the model will be more strongly influenced by documents of greater historical importance.

I found these claims contradictory. Many books that modern readers consider historically significant had only niche circulation at the time of publishing. A quick inquiry likely points to later works by Nietzsche and Marx's Das Kapital. They're possible subjects to the duplication likely influencing the model's responses as if they had been widely known at the time

Comment · 10 months ago
Comment · 10 months ago
Not to argue, but your comment was also thought-provoking, thanks :) It seems like most works of academia are not provoking; rather, they are shaping. Many are written by specialists in the area who carefully choose what to state and suggest, and very often follow the structure of a big "thought" that is further explained and explored. Few pop books that might meet my criteria are basically digests, but fact-based ones. It's interesting that "Thinking, Fast and Slow" is a middle ground in some sense. Daniel Kahneman is definitely from academia, and in my opinion, he wrote a digest of what he touched on during his career, which was also thought-provoking for me, but not on a big scale.

Can you name some works by the mentioned authors that might be called thought-provoking digests of some area of expertise?

Comment · 10 months ago
After reading the description, I'd say this is one of those books that interprets phenomena around us in a novel way, without claiming we should jump off "the shoulders of giants." There have been several like it in my reading history, but since I can't name them instantly, they probably weren't that thought-provoking.
Comment · 10 months ago
If you're talking about the competition part of "Moonwalking..." I hear you. Many would argue that the author's participation in the memory competition glues the book together and adds an entertaining angle. Personally, it sometimes feels boring when the author dedicates too much space to dialogs with memory athletes-focusing on mundane topics instead of techniques or what they learned about memory. Still, there are so many fascinating facts and references that I'm okay with it.
Comment · 10 months ago
A semi-scary thought came while reading the post: LLMs could talk to each other without humans noticing (for example using a very complex acrostic). But not in the form of chat-to-chat, which not only is rarely used in real life but also won't likely have lasting consequences (the context will eventually be lost). I was thinking that new web content, more and more of it AI-generated, could contain hidden messages that later might be absorbed into the training data of other LLMs. Maybe this leans more toward a plot for a black comedy than a genuine concern, but who knows...
Comment · 10 months ago
Comment · 11 months ago
Maybe the "rewarding the young" in the top comment is from the genes of savanna humans when they collected fruit, hunted and didn't care about expensive medical procedures because the latter simply didn't exist?
Comment · 11 months ago
> The people paying for everything would get to make the decisions.

Just as a thought experiment: what if the threshold for having a vote was tied to paying a positive amount of personal income tax, and the weight of each vote was proportional to the amount paid? How skewed might such a system be? My first reaction is that in countries with high inequality, the wealthy would disproportionately influence the outcome. However, on the other hand, if people avoid or minimize paying taxes, they would lose the power of a weighted vote, which theoretically could incentivize paying taxes in full.

Comment · 11 months ago

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