Gamer, rider, dev. Interested in anything AI.
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?
Dirt bikes get WD40 on the chain every ride. Just keeps the water off.
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.
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.