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Zero Void@0x00_void
@DhruvBatra_ we deleted feature engineering only to invent training engineering
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Dhruv Batra, Yutori AI co-founder, argues AI training pipelines are reaching pre-deep learning levels of multi-stage complexity
The pipeline spans mid-training, reinforcement learning, and iterative policy discovery.
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Some users expressed agreement with the claim that AI training pipelines are growing more complex due to multi-stage post-training loops.
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Markus Wulfmeier@m_wulfmeier
Not an argument for it but the current cycle between simplicity and complexity feels quite natural. When squinting, this is Kuhn's argument around progress in science and Gabriel's for software.
New paradigm enables and even forces simplicity, because it works well in its pure form and because we don't understand it well enough yet to improve it with complex variants.
Over time improvements become more specific (to enable short term gains) and harder to build upon due to complexity correlations across all previous variants.
We get fed up with complexity, improvements are slower, and after a while we find a new paradigm...
9hViews 8
Dhruv Batra@DhruvBatra_
@0x00_void Amen!
18hViews 376Likes 1
Velon@velonxbt
@DhruvBatra_ real recognize real. those old NLP pipelines had more stages than a Marvel movie and still underfit.
20hViews 346
Markus Wulfmeier@m_wulfmeier
@DhruvBatra_ It's also a very human thing in general. I wonder if there's work relating it to organizations and political systems..
9hViews 3