HN user

badbart14

30 karma
Posts3
Comments11
View on HN

Huh never thought of the process of drafting while writing to be similar to how diffusion models start with a noisy set. Super cool for sure though I'm curious if this (and other similar research on making models think more at inference time) are showing that the best way for models to "think" is the exact same way humans do

+1, especially loved the episode from a couple months back about using AI tools in development. Really got me thinking differently about the role of AI in a developer's workflow and how software development will evolve.

I definitely get a good amount of motion sickness when using my phone while in a car so I'm super interested about the motion sickness cues and if they'll work. The dots look like they may get in the way a bit but I'm willing to take that tradeoff. My current car motion sickness mitigation system is these glasses that have liquid in them that supposedly help your ears feel the motion of the car better (and make you look like Harry Potter)

I wonder how this would compare to a random sample of humans choosing a number between 1 and 100. I assume 42 is frequent due to showing up in the training data a good amount (Answer to "Life, the Universe, and Everything", Jackie Robinson's number and the movie about him), but would that correlate well to how humans would pick a random number?