lionkor

Yes, I agree fully. And yet I can go to a doctor and get meds and I will pay no more than 15 bucks on a really bad day for some meds.

> Still majority of the Germans don’t invest their money and just let it depreciate in their savings accounts

Do you have a source on this? I live in Germany and most people I know either invest into stocks (safe, boring ones), invest into a house/apartment/land or similar, or are too broke to even save anything at all (most people).

That makes it easier to quantify. If I need to work a decent job at a decent company to have good healthcare, then a large number of people don't have good healthcare.

This is not acceptable. Healthcare should be a basic right, and a lot of European countries treat it as such (e.g. in Germany, everyone is insured, no matter their employment status, and its mandatory and equal for everyone regardless of their job).

People also can't be fired for being sick.

Are you speculating? Or what are you basing this off of? Are you saying this is the next COVID and the government will use it to crack down on protests?

Please don't use Hacker News for political or ideological battle. It tramples curiosity.

https://news.ycombinator.com/newsguidelines.html

But a TUI does the same thing except the client side doesn't need to have anything installed.

SSH into a machine and open a GUI tool. I'd love to watch you do that and enjoy 2 FPS via X11-via-ssh.

My $0.02; I use pi every day, it's always running somewhere for various kinds of tasks (no vibe coding). I run it in `sbh`, a slop cannon wrapper around `bubblewrap` that ensures that the agent only has access to things it could possibly need. The code is short and you can audit it yourself.

I run it like `sbh --net pi` or `sbh --net --docker pi` depending if I want the agent to have docker access. The result is that ~/src/my-project gets mounted as `/w/home/lion/src/my-project` and any LLM I've tried understands that this is a sandbox implicitly.

I strongly suggest everyone who uses a harness, of any kind, to copy it and edit it to better suit one's setup.

sbh: https://github.com/lionkor/sbh

For a second I was hoping that Pi users would be the kind of people to not enjoy nags about improvements.

Apart from a different terminal app, try `/settings`, find the "TUI mode" or whatever, and set it to fullscreen. It fixed all my flickering and other issues.

I love how consistent pi has been, especially in regards to not breaking ux

I might be talking out of my ass, but is it possible that there are cases being built on them? Surely any prosecutor worth anything would love to take a swing, but it takes a lot of time, effort and patience to build a case that isn't going to fall apart against these titans (that have massive political backing).

Hi, this might not be obvious to you so I wanted to explain it:

Testing on a single device, or two devices, is not enough. I'm on a laptop with 96 GB ram and a Ryzen AI 9 HX PRO 370, and it's running at 3 FPS.

The crucial part is browser performance and network latency. You need to test across multiple browsers, but also evaluate frame times, CPU load, GPU load, etc. so you can make a reasonable estimate whether it's fast or not.

Then, when you realize that its not good enough, e.g. on firefox, you use firefox's profiler to see which parts are slow. LLMs would guess, probably, but you have to measure.

Welcome to software engineering.

It's illegal to record people in public spaces in Germany. Not sure how NL is important here, did I miss something?

Until someone steps into the sun, or smokes, or does literally anything that causes cell mutations (which is, well, almost anything).

If you want this type of language, go to OpenAI. If you compare announcements from these two, you'll see this consistently apply.

Can someone explain to me why nuclear HAS to be profitable?

Well yes but as soon as you log this on the backend, you have telemetry, no?

It's already impossible for end users to read the thinking output of OpenAI's models.

Its at the very top, when you move the slider :)

I find that subagents usually burn more tokens and take longer, and produce about the same quality. A real killer use-case is using a VERY cheap subagent to do a lot of work, or reviews. Don't be fooled into thinking that a "scout" subagent will gather enough info for a "coder" agent to just start working.

I urge everyone to compare this announcement with Anthropic's announcements. From the post above:

> On FrontierCode, which evaluates whether coding agents produce changes ready to merge into real codebases, GPT‑6 Sol improves substantially over GPT‑5.6 Sol, and is able to match Claude Fable 5.1 xhigh at much lower cost.

I continue to appreciate OpenAI's attempt at some honesty here, showing that they are capable enough and have skilled engineers to a point where they can recognize that slop is hated for good reason, and that there is a real issue. Compare this to anthropic, where e.g. in the Opus 5.5 announcement[1] one of the first points on the page is

> One tester completed a 680,000-line code migration in less than a day—work that would have taken an engineering team weeks. It’s good at finding and fixing inefficiencies in software: when we asked it to cut load times across every page of a web app, Opus 5.5 succeeded 39 of 40 times, while Opus 5 made smaller improvements that also altered the app’s behavior. A different tester had several Claude models build a game from a single prompt; Opus 5.5 scored higher than any other model on the strength of its graphics and polish.

This is the kind of shit that is the very reason why I stick to OpenAI and deepseek. OpenAI is simply more honest and reasonable about their models' capabilities, while delivering models that still have solid value.

Notice how the OpenAI announcement doesn't make use of anecdotes.

[1]: https://www.anthropic.com/claude-opus-5-5

In most humans, yes, because we are terrible at memorizing millions of codebases. For LLMs, we need to apply our understanding of them before making statements like that. An LLM can "memorize", and has "memorized"/been trained on tens of thousands of chess engines. Writing a chess engine, or even deriving a chess engine from the rules alone, does not constitute a deep understanding of, and more importantly, the ability to apply, the rules, at all.

When humans do this, they inadvertently learn something, too, but when an LLM reproduces or derives and implementation of a chess engine, it in no way implies that the LLM can follow the rules in its own "train of thought" and consistently apply the rules in its "head".

Let's say you want to evaluate my algebra skills. You make me solve some algebra challenges. If I then whip out a computer and write a calculator, or take some sticks and stones and take a couple hours to build an abacus, and then solve the algebraic challenges, this would not constitute a good solution, and would defeat the entire point of the test. If, instead, I do the algebra in my head or on paper, it might seem like there's no difference, but you can derive all sorts of information from that.

For example, you could time it, check for recurring errors I make, for interesting mistakes like mistaking 7 and 1 for one another due to bad hand-writing, etc.

If that was the goal, then me writing a calculator or crafting an abacus defeats the point of the test. Yes, me writing a calculator shows that I'm intelligent, and I understand the algebraic rules, but if the test is about applying the rules, I have not passed.

In the very same way, an LLM writing a chess engine to solve a chess benchmark that is all about LLM's reasoning capability is complete bogus and defeats the entire point.

With that approach, the benchmark falls apart. Of course it can write a chess engine, because it learned on lots of stolen source code of chess engines. This has nothing to do with the LLM's ability to reason.

Writing a well understood engine for a super popular problem does not count as reasoning about the problem.

The question is to what end? This is a benchmark task, because playing chess, or solving other well-understood problems is more of a party trick than it is useful.

If you let the LLM write a chess program, which it can ONLY do because there are already so many chess programs out there, then the benchmark becomes about recall of popular program source code, not chess.

My read is that the improvements in quality are due to excessive use of "thinking" tokens (so, higher quantity and brute force), so I agree with that.

If you want creators to get paid, pay them (channel memberships, patreon, click on their sponsor links and buy something). No need to subject yourself to ads.

Ads don't just steal your time either, they invade your head. You are influenced by them and you have no choice as long as you watch them.

Who's funding this? The people getting scammed, usually.

Same here, but I want to add that you can easily do this for all apps BUT one or two. For example, I have my messaging and personal emails allowed to send me notifications, because almost all messages I get there are important and usually urgent enough (and rare enough, or it's my partner, so either way it's not annoying).

I can really recommend an automatic watch. Go to a jewelry store, try some on in the below 300 euro category (like, 10 euro to 300 euro range), and get one. Suddenly you can leave your phone somewhere, and not panic-check the time on it and get distracted.

And they look nice, feel nice. Some of them even have a glass/crystal back, so you can watch the mechanism, relentlessly ticking on.

Get an analog automatic watch. It doesn't need to be second-accurate. Everyone else is keeping track of nanoseconds, you'll be okay not knowing.