Huh, I thought Asahi would still be too unpolished on M2 to play games reliably. Could you elaborate on your setup a little? What kind of games do you play? What is performance like? Is it really better than Crossover for example?
233 karma · joined March 5, 2026
[1] https://www.reddit.com/r/flashlight/comments/122widx/power_o...
I was going to explain some of the others when I realized that in the context of this thread — namely comparing Europe to China in terms of ethnic diversity — these misleading statistics smell like a call to return to a ‘monocultural’ Europe. My grandparents have had pretty bad experiences with Germany’s last attempt at that; I therefore want to stress how dangerous it can be to present statistics like these as ‘neutral’.
God this is so recognizable, it's truly at my lowest moments that I decide I need a new terminal emulator and spend 6 hours in a brew install rabbit hole. The worst thing is that I'm still using Warp of all things
[0] https://shop.hak5.org/products/omg-cable [1] https://darknetdiaries.com/episode/161/
The first 6-12 months after university are largely about 'learning how to work'. I'd say getting that out of the way is a pretty nice head start.
I eventually got bored telling those chatbots to "go fuck yourself" so I've now picked up the admittedly fun micro-hobby of jailbreaking customer support bots.
My first prompt was a Preview-annotated image where I drew the bounding boxes of where the lights would go with a green line and marked the power socket with a red dot.
I just tried the exact same prompt but using tack instead of marking with 'pen' on the image. It completed it with much better results, one-shot (instead of having to steer 3 times) and in 1/20th of the original time.
Token usage for the original approach: `Tokens ↑ 2.4m • ↓ 50.2k • 2.2m (cached) • 10.1k (reasoning)`
Token usage using coordinates instead of drawing: `Tokens ↑ 79.2k • ↓ 4.7k • 72.7k (cached) • 1.5k (reasoning)`
Not very surprising that a JSON of coordinates is more efficient than drawing a crude line on an image, but I couldn't be bothered because GitHub still charges per request instead of per token. If I'd had this 20 minutes earlier I WOULD have bothered, though. Nice work :)
- Consumers of LLM inference (developers and hobbyists) will be more aware of compute cost, leading them to develop more token-efficient uses of LLM inference and be incentivized to pick the right model for the right job (instead of throwing Sonnet at the wall and follow up with Opus if that doesn't stick)
- A larger market for on-device (and therefore open weight) LLM's will probably result in more research concentrated on those inherently more efficient (because compute/memory-constrained) models.
I think that despite the inefficiencies, shifting the market towards local inference would be a net positive in terms of energy use. Remember that 50W might seem like a lot, but is still much less than what, let's say, a PS5 draws.
Also remember how AWS had the same promise and now we're just deploying stack after stack and need 'FinOps' teams to get us to be more resource-efficient?
Hence not allowing children to fall victim to social media? I'm not quite sure I get your point.