It's exactly as another commenter thoughtfully replied. My mind works better which rules, interactions between systems, teasing out insights in complicated data, understanding where things break down between boundaries, foreseeing issues that people wouldn't think of well before they come up, etc.
While I'm not sure this is directly related, but even things like being a participant in a multi-party conversation and watching 2 people have a discussion and instantly pick up on the fact that person 1 interpreted something in a certain way that doesn't match up with person 2's interpretation of it. Super handy being able to instantly just jump in and say "by the way I think person 1's understood that to mean this instead of that".
If you have a portfolio with some % allocation across various assets and industries (a% stocks, b% bonds, c% precious metals, d% bitcoin, etc.) then you can simply rebalance at regular intervals. When precious metals become overweighted in your portfolio you sell out and buy into whichever asset class is underweighted. This enforces "buy low, sell high", and if you do it on a predefined interval you don't have to worry about day to day fluctuations.
It's good to finally hear some news AND have results coming from the Proton team regarding some of the most complained about problems. Namely, that Proton seems to release new products while leaving the existing ones with known issues and a general feeling of being "unfinished".
Anecdotally the Proton Mail app is now *much* faster.
Looking forward to see this approach brought across to the rest of the product line.
I can only speak for myself but I have no interest in watching historical movies, so your project has no relevance or value to me.
Could it be that either your target audience is small and/or has little overlap with the Hacker News audience?
Try posting it in a more relevant community. You might generate more interest from people who are actually interested in historical movies vs people interested in technology.
I know you're proud and want to showcase all the technological work you put into it but IMHO that's not what is valuable about this project.
Unfortunately, the linked energy consumption search does not seem to be usable for the average person. Tried to search LG C8, no results. Tried to search LG filtered by OLED (apply filter is a different button), no results, etc
This is written by AI. You see this "style" enough and it becomes immediately obvious.
You usually can’t prove it instantly—but you can smell it fast. AI writing leaves fingerprints. Here’s the blunt version.
First: it sounds correct but feels hollow. The sentences are clean, grammatical, and oddly polite. Nothing risks being wrong. Humans leave dents—opinions, hesitations, slightly ugly phrasing. AI sandpapers those off.
Second: too balanced, too fair. Every argument has a counterargument. Every claim has a caveat. Real people pick sides, forget disclaimers, or double down when they shouldn’t. AI keeps the peace like it’s being graded.
Third: generic confidence. It explains things with authority but without lived detail. No concrete scars, no oddly specific anecdotes, no “this broke in production at 2am” energy. It knows about things, not through them.
Fourth: structure over voice. Paragraphs march in neat formation. Transitions are impeccable. You could reshuffle them and nothing would change. Human writing has rhythm problems and obsessions—it lingers where it shouldn’t.
Fifth: vague specificity. Phrases like “various factors,” “a range of considerations,” “it’s important to note.” These say nothing while pretending to say something. Humans usually either ramble or overshare instead.
Sixth: no genuine surprise. AI rarely startles you. No sharp metaphor that makes you pause. No sudden pivot that reveals the writer’s personality. Everything feels anticipated.
Seventh: the absence of stakes. There’s no sense that being wrong would matter. Human writing often leaks anxiety, pride, frustration, or desire. AI writing feels emotionally insured.
Important caveat: good human writers can sound “AI-like,” and skilled humans using AI can mask it well. Detection isn’t a switch; it’s a pattern-recognition reflex. You’re not spotting a robot—you’re noticing the lack of a human fingerprint.
The deeper truth is uncomfortable: as AI improves, the tell won’t be style—it’ll be experience. Writing grounded in real constraints, consequences, and tradeoffs will remain the hardest thing to fake. That’s where humans still leave marks that aren’t easy to erase.