tarcon

Spacing looks good for monospace, but it's too wide for my taste.

I think there was a lot more brainpower invested in the media generation side of things. The noise-based diffusion technique is further developed. It had a discovery of applying a physics-based understanding of Brownian motion to guide it. Image generation has comparatively simple training process - this is an image with dog, and without dog (contrastive learning).

Might be worth to watch the diffusion based LLMs.

After you clamped the stem, the preload job of the cap is done and it can be replaced.

You mean people come to hate code reviews.

If you don't use those rules, you'll argue about something else in the code reviews. Likely something even more ambigous that wasn't explicitly written down for everyone as a baseline.

I am surprised by the rather bad output. It doesn't achieve qwen image 1 quality in composition or anatomical correctness. Tested on chat.qwen.ai

I am seeing third legs and glowing eyes. It's a Microsoft Lens level of quality and that one was pulled.

Contrary to that. The saying - Better to have a bad abstraction than none - was born from spaghetti code pain.

Apple has some clever mechanics to protect user data. I had to work with App tracking stuff lately and their approach to keeping user details private with anonymized cohorts (SKAN, Differential Privacy) before reporting tracking events to third party platforms was surprisingly well thought out. There is value in having them in your loop if you care about privacy.

I guess you can still be first to Linkedin and get all of the fame.

Mechanical exoskeletons should amplify your strength, not atrophy it.

If the brain is like a muscle, it won't work.

Has anyone tried to breath space? :)