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How physics advanced generative AI
- billconan 3y agoIt is possible that the idea of highlighting this connection was emphasized for marketing purposes in order to generate interest and excitement around the development of these models. When I first learned about diffusion models, I immediately drew a connection to denoise auto encoders, as both attempt to recover underlying information from noisy data. However, the differences between the two models are not discussed in articles about diffusion models. From my perspective, it appears that denoise auto encoders may have played a role in inspiring the development of diffusion models.
- SleekEagle 3y agohttps://sander.ai/2022/01/31/diffusion.html https://sander.ai/2022/01/31/diffusion.html The differences are thoroughly discussed here. From my point of view, while there is this surface-level similarity, the training process for diffusion models is directly a result of the mathematical framework on which they are defined which is distinct from denoising autoencoders. I'd suggest reading the above blog if you are interested, it is thorough!
- billconan 3y agoThank you for sharing! I didn't know about this post. I will read it.
- SleekEagle 3y agoMy pleasure, enjoy!
- gregorymichael 3y agoThe graphics in this post are top notch. Nice work.
- SleekEagle 3y agolol this one was a little rough https://lh3.googleusercontent.com/Ezv0DiB8vu5GJM5nQGm9aapsq0o6xS5aoqbig0loo310wjNCLrKulhTu7IoicLMPtdaQ-C1ME3_PveR5uCmLAjSB2qBHV-oqE5QiuIf0u6uEuJjszZB_HNs2PjC2vi2YQmItxs0yIPWrrGOSn3_ZxNI https://lh3.googleusercontent.com/Ezv0DiB8vu5GJM5nQGm9aapsq0... but thank you! I'm glad you enjoyed
- mxwsn 3y agoThis title is confusing due to the automatic removal of "How". Should be "How physics advanced generative AI".
- dang 3y agoRehowed. Thanks!