bayindirh

I have skimmed the post but some of the things are not minimalism, but replacement of delivery mechanisms. On the other hand I'm also doing something similar in my digital life.

I have reduced my social media to two sites: Here and Mastodon (with a very limited follow circle). I don't follow tons of ad-ridden websites. I have a self-hosted RSS reader, following 10 feeds. Instead of following junk tech news, I read LWN.

Next step might be enabling antiproc on HN to reduce my time here, since I added time limits on applications on my phone and love that artificial limit.

I have limited energy and I want to focus it instead of spreading it around. Otherwise progressing beyond a certain point becomes impossible.

It's just a conscious being confined in a cluster of GPUs. How dangerous can it be, eh?

It made me reconsider what I think about mathematics in general. So, if it was junk food, it was a nutritious one at that.

I don't think so. People love to see how far they can go in some aspect sometimes. If I had the same amount of free time 5 years ago, I'd have tried the same thing with Go, because I like the language, and love the act of programming and seeing things.

Also, I also agree that people optimize without proper testing and profiling. If there's a real bottleneck here, trying to optimize it is the right call. OTOH, optimizing without profiling opens a lot of unnecessary cans.

Lastly, Go doesn't like constant allocation and deallocation of variables, that's true, but I believe knowing this and optimizing hot-loops for that goes a very long way as a start.

Humans are unsettled by fast, drastic changes since it generally signals uncertainty ahead. It's a caveman instinct signaling that someone needs to do much more to find the new normal or navigate some hardship.

RedHat and Ubuntu has kernel hot-patching. That's a case with binaries.

The whole reverse engineering and cracking scene is built upon this premise, you know.

I have Gemini because of my Google One membership. I already was on their 2TB plan and it gave me Pro level, IIRC, and it was generous. Now I'm on Ultra mostly because of Google Drive storage I get, but Gemini also gets a nice boost, as well.

I'm on $20 Claude plan, and it's also ample for my needs, for now.

People always love to think the AI race is a duopoly (OpenAI vs. Anthropic), but from what I have experienced, Gemini was always holding on its own, and I find myself using it more than Claude.

True, I use LLMs as glorified search engines to unearth material to read myself, but Gemini is much more useful if you decide to learn yourself. It also offers interesting expansions to your questions.

While I don't offload my work to LLMs (e.g.: Write this project, I'll be watching TV), I find them useful for closing my knowledge gap by collating information, and Google's Gemini is good at that.

In today’s world, this is both a few and fair use. You just need to claim that you’re going to train models for research purposes.

I don’t think plugging a laptop to an open switch port and launching a script to scrape webpages to get PDFs to an external drive is hacking per se.

If it was, impersonating home users en masse to scrape the whole web to train models would result in lifetime in prison. Now we call it fair use.

That's true, but if the LLM is calling a tool to provide the base information to extrapolate, the results will not change even if the sentence structure is never the same.

Debian has an extensive toolchain to check things. Having a set of deterministic tools which feed LLM with data can be beneficial, though.

Again, I'm not defending the LLM here, just want to show how hard the problem is to begin with.