aichannel

is there any interest in cast summaries like these of new ML papers from big companies? 

Apple’s approach: https://arxiv.org/abs/2412.06329 [2412.06329] Normalizing Flows are Capable Generative Models

Meta’s approach: https://arxiv.org/abs/2210.02747 [2210.02747] Flow Matching for Generative Modeling

𝚐𝔪𝟾𝚡𝚡𝟾

Do it for him, our under appreciated AI hero

Do it for him, our under appreciated AI hero 

https://farcaster.xyz/gm8xx8/0xda629828

not promising you’re sending me a cast with no likes

He was a prolific poster of /ai research and sometimes called out things that would happen weeks/months later, but his academic way of posting didn't get a lot of engagement. So I think he went back to X where much of his crowd is!

ahhh got it, i’m not much interested in the academic stuff i’m trying to ensure i am up to date on:

1. text to speech and speech to text (people pay me to apply this for them)
2. image labeling and classification (same as above)
3. time series prediction + anomaly detection (i love projecting revenue)

planting causal loops; harvesting reflexivity

i haven’t found any transformers or seq2seq model that works better for time series than math based models

TimesFM interesting transformers for time series

Dia is great for text to soeech small open model