Ahh that sucks. It's been a very mild summer up here with almost no "hot" days. I think 28C is about as much as we're seeing lately.
The advancements in this space have moved so fast, it's hard to extract a predictive model on where we'll end up and how fast it'll get there.
Meta releasing LLaMA produced a ton of innovation from open source that showed you could run models that were nearly the same level as ChatGPT with less parameters, on smaller and smaller hardware. At the same time, almost every large company you can think of has prioritized integrating generative AI as a high strategic priority with blank cheque budgets. Whole industries (also deeply funded) are popping up around solving the context window memory deficiencies, prompt stuffing for better steerability, better summarization and embedding of your personal or corporate data.
We're going to see LLM tech everywhere in everything, even if it makes no sense and becomes annoying. After a few years, maybe it'll seem normal to have a conversation with your shoes?
I'm not sure either, Win 10/11 are pretty quick to get going and Ubuntu is not much longer than that. If I have to hard reset the mbp for work, it's a nice block of slacker time :)
For the really old stuff, I used to do NetBSD. I'm sure their 32bit x86 support is still top notch.
Halls of Torment. $5 game on steam that is like a Vampire Survivors clone, but with more rpg elements to it.
These are amazing. Dell, Lenovo and I think HP made these tiny things and they were so much easier to get than Pi's during the shortage. Plus they're incredibly fast in comparison.
I've got a background in deep learning and I still struggle to understand the attention mechanism. I know it's a key/value store but I'm not sure what it's doing to the tensor when it passes through different layers.
Subscribed. That last episode of AAA was heartbreaking.
We used to ride the heavy dual sports through pretty much everything, but this mud hole got him good. He ended up trying to wedge out with a dead tree, but it knocked his chain off, making the situation much worse. Eventually we pulled it out with a z-line and got the chain back on.
If you're in a situation like this, and shit ain't moving no matter what you do, lie the bike over on it's side (yes in the mud) and pull the front and rear until you're on something more solid. Your paint will not thank you, but it's better than leaving it there to get recovery tools.
Are those tires stock? Almost look like dual sport tires I had on my older KLR.
Any data sets produced before 2022 will be very valuable compared to anything after. Maybe the only way we avoid this is to stick to training LLMs on older data and prompt inject anything newer, rather than training for it.
Step 1) Have a bike that women want to talk about. I think that's about it.
When I had a CRF250L, I'd regularly have women come up and ask how heavy it is, because they're thinking of buying one. I'd put the bike on the ground and show them how to lift it. So... weirdest thing is dropping my bike intentionally to let women pick it up for me.
Ryzen 5900X, 64 gig DDR4-3200, 2tb ssd,10tb hdd and an RTX2070. Hosting Stable Diffusion, various llama.cpp instances with python bindings, jellyfin, sonarr, multiple modded minecraft servers, and a network file share.
