11–20 of 45 posts
Apple AI team keeps going against the bitter lesson and focusing on small on-device models. Let's see how this would turn out in longterm.
"""The bitter lesson""" is how you get the current swath of massively unprofitable AI companies that are competing with each other over who can lose money faster.
Apple AI team keeps going against the bitter lesson and focusing on small on-device models. Let's see how this would turn out in longterm.
somewhat hard to say how the cards fall when the cost of 'intelligence' is coming down 1000x year over year while at the same time compute continues to scale. the bet should be made on both sides probably
Forgotten from like 2021? NVAE[1] was a great paper but maybe four years is long enough to be forgotten in the AI space? shrug 1. NVAE: A Deep Hierarchical Variational Autoencoder https://arxiv.org/pdf/2007.03898
A more accurate headline would be - Apple starting to create images using 4 year old techniques.
This subject is fascinating and the article is informative, but I wish that HN had a button like "flag", but specific for articles that seems written by AI (well at least the section "How STARFlow compares with OpenAI’s 4o image generator" sounds like it)
I find it fascinating that Apple-centric media sites are stretching so much to position the company in the AI race. The title is meant to say that Apple found something unique that other people missed, when the simplest explanation is they started working on this a while back (2021 paper, afterall) and just released it. A more accurate headline would be - Apple starting to create images using 4 year old techniques.
> short: both Apple and OpenAI are moving beyond diffusion, but while OpenAI is building for its data centers, Apple is clearly building for our pockets.
Forgotten from like 2021? NVAE[1] was a great paper but maybe four years is long enough to be forgotten in the AI space? shrug 1. NVAE: A Deep Hierarchical Variational Autoencoder https://arxiv.org/pdf/2007.03898
They are both variational inference, but Normalizing Flow (NF) is not VAE.
The appendix goes on to explain, "We apply simple volume-preserving normalizing flows of the form z′ = z + b(z) to the samples generated by the encoder at each level".
I find it fascinating that Apple-centric media sites are stretching so much to position the company in the AI race. The title is meant to say that Apple found something unique that other people missed, when the simplest explanation is they started working on this a while back (2021 paper, afterall) and just released it. A more accurate headline would be - Apple starting to create images using 4 year old techniques.
A glance through the comments also shows HNers doing their best too. The mind still boggles as to why this site is so willing to perform mental gymnastics for a corporate.
I find it fascinating that Apple-centric media sites are stretching so much to position the company in the AI race. The title is meant to say that Apple found something unique that other people missed, when the simplest explanation is they started working on this a while back (2021 paper, afterall) and just released it. A more accurate headline would be - Apple starting to create images using 4 year old techniques.