Cartesia co-founder Albert Gu challenges the assumption that Transformers are universally effective across all raw input modalities without specialized preprocessing.
“People think that like you can throw a transformer at like anything and it just works. Actually it doesn't really like if you try to throw it at like the raw pixel level or the raw sample level and in audio waveforms I think it doesn't work nearly as well.”
quote is from the automated transcript, cleaned for reading:
filler sounds and stutters are removed, nothing is rephrased. names can be misheard
(the analysis reads context, assessments check outside sources). how →
More from Albert Gu
Insight
Gu: High-quality speech synthesis requires multimodal foundation models
“And so actually to really get, like, perfect even just TTS or, like, speech-to-speech you actually really need to have, like, a model that has, More understanding, like at least of the language, but kind of like, it's not really an isolated component anymore. …”
Albert GuJun 27, 2024▶ 24:27No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
AssertionSupported
Gu: Optimal hybrid models use a 10:1 ratio of SSM to attention
“People have found that the optimal ratio tends to be mostly SSM layers with a little bit of attention. So maybe a ratio of like 10 to one, I know of at least Probably like five groups that have independently verified that this is kind of the optimal ratio of t…”
Albert GuJun 27, 2024▶ 11:30No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
AssertionSupported
Gu: Mamba successfully applied state-space models to language modeling
“Recently proposed a model called Mamba which was kind of brought these to language modeling and showed really good results there.”
Albert GuJun 27, 2024▶ 2:24No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
Insight
Gu: State Space Models can be applied to almost all data types
“So it really can be applied to pretty much everything. So just like kind of Transformers, these are applied to everything. So can these sort of models over the course of research over a few years, we kind of realized that there are different advantages for dif…”
Albert GuJun 27, 2024▶ 6:51No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
Insight
Gu: Aesthetic elegance was the primary driver behind inventing State Space Models
“People ask me, like, how do I treat my research problems, and my, I can't explain. My answer is just aesthetic. It's just like, there's something that I find elegant, and we're aesthetically pleasing about things, and to me, that's almost the most important th…”
Albert GuJun 27, 2024▶ 29:30No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
AssertionSupported
Gu: Early SSMs excelled at raw signals but lagged Transformers on text
“The first types of models we were looking at were really good actually at modeling kind of these raw waveforms raw pixels, things like that, but not as good at modeling text, and transformers are way better there.”
Albert GuJun 27, 2024▶ 7:49No Priors Ep. 70 | With Cartesia Co-Founders Karan Goel & Albert Gu
Made with StarZero
Turn any episode into a week of clips.
This entire site, over 100 episodes transcribed, diarized, checked and made playable,
runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the
moments worth sharing, cuts them, captions them, and reframes them for every feed.
We use essential cookies to make the site work. With your permission we
also use analytics cookies (Google Analytics and Mixpanel) to understand
usage and improve StarZero. See our Cookie Policy.