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Fergusonb

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Cloudflare Drop 14 days ago

Yep, I chucked it a file on my desktop: index.html present Max individual file size 25MB Total file count <2000 Total size less than 100MB

Apple's tablets are great, but I think we're just pretty close to the limit for these entertainment devices.

I have a now 7(!) year old Tab S5e that I use to consume media, and it's 5.5mm thick, with 10 hours of battery, a 1600x2560 super AMOLED, and quad firing speakers.

Nothing on the market makes me feel I need an upgrade over what was a $400 mid range tablet, because I have an incredible media experience on all my streaming apps.

They're definitely more popular right now, but they've been a winner since M1.

Great performance, quiet, efficient.

It would be tough to get a windows machine at that price that gets anywhere close on performance, especially if you consider the cost of electricity.

Great parent/grandparent machines, home servers.

Agree with everything here.

Anecdote:

I purchased an EV this year, my highest priority was range per dollar, and the vehicle I selected happened to be new because of current market conditions. (Equinox EV for under 25k otd after incentives)

Claude Haiku 4.5 9 months ago

I agree, claude is an impressive agent but it seems like it's impatient and trying to make its own thing, tries to make its own tests when I already have them, etc. Maybe better for a new project.

GPT 5 (at least with cline) reads whatever you give it, then laser targets the required changes.

With High, as long as I actually provided enough relevant context it usually one shots the solution and sometimes even finds things I left out.

The only downside for me is it's extremely slow, but I still use it on anything nuanced.

I don't know, it's nice to have icons and buttons that actually look like what they're going to do instead of amorphous blobs.

Sure it can, easiest way is to get ollama, then `ollama run gemma3n` You can pair it with tools like simonw's LLM to pipe stuff to it.

I think they are fairly interchangeable, In Roo Code, Claude uses the tools better, but I prefer gemini's coding style and brevity (except for comments, it loves to write comments) Sometimes I mix and match if one fails or pursues a path I don't like.

I've been actively developing a commercially deployed SvelteKit application, and I'd like to share some thoughts on my experience.

What initially drew me to SvelteKit was its simplicity. After setting up the project, I could work on one HTML/JS/CSS file at a time, leveraging the benefits of a modern framework without the accompanying complexity. This approach reminded me of the early days of web development, where dropping HTML files into an Apache server was all it took to get things running.

However, it's disheartening to see Svelte shifting away from that straightforward paradigm. From the outset, Rich Harris positioned Svelte's ease of use and simplicity as its key selling points. The current version of SvelteKit isn't bad per se, but I found myself preferring the earlier iterations. Back then, I didn't have to deal with constructs like `+page` for routing. I could place Svelte files wherever I wanted, and they would render seamlessly, all while enjoying the advantages of a modern framework.

This change adds layers of complexity that weren't necessary before, potentially moving away from what made Svelte appealing in the first place. I picked it up because I already knew what I needed to know.

The default model on ollama is the 7b distillation.

Its ability to solve basic math problems with reasoning is pretty cool, but other models of that size (qwen 2.5, phi4) have been generally more useful to me.

These tiny models still strike me as toys, not a whole bunch of real-world utility.

These benchmarks have even the small models absolutely demolishing Sonnet-3.5, which doesn't reflect my subjective experience.

It still seems to me that these models are 'dumb' and often don't understand what I'm asking, where claude's intuition is much stronger.

I feel r1 14b even feels weaker than qwen 2.5 14b

Primary use-case is web technology / coding. Maybe I'm prompting it incorrectly?

While this raises valid concerns, Copilot and friends can actually enhance learning by exposing devs to new patterns and approaches. They still require problem-solving and critical evaluation skills. By handling routine tasks, they free up time for higher-level thinking.

It's just another abstraction layer, like high-level languages were. Responsible use combined with continuous learning can boost productivity without sacrificing knowledge.

The impact differs between experienced devs and beginners. As these tools evolve, we'll likely develop new meta-skills around AI collaboration. Like any tool, it's about how we use it.

There's ydotool, but as far as I tested with it, the only movements that work are relative movements. You can't tell it to a click a specific x/y because it will fumble badly (Nobara / Fedora 38 )

This has been a huge problem in my social circles.

I really like my current android device, but my wife and our friends have iphones and we are all constantly inconvenienced by the messaging and other poor sharing options between platforms.

They share things without having to think about it, and I have to come up with solutions that are acceptable to them.

Between this issue and the differences in performance in the last few years, it has me thinking of moving back to team blue after 10+ years on green.

Anecdotal evidence here - I find that the API is less likely to ask questions about what you are doing and get straight to the answer.

For example, if I were to ask how to do something with burp it will just answer instead of going into the "as an AI" monologue.