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MACHINE LEARNING
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Language Models: From Statistical to Transformer Models for NLP
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User testing AI photo recognition model capabilities
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The photo recognition is already working but is a bit unstable. But I feel like I am testing it with a general GPT4 while it will come with a different model which wasn't announced yet
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Neural Operators: Breakthrough Progress in Machine Learning Research
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A ton of papers on neural operators! Amazing progress!
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Neural Operators and Differential Equations Advances at ICLR2024
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Good to see differential equations and neural operators getting more popular! If you are at #ICLR2024 make sure to attend! Lots of advances in neural operators presented there. https://
x.com/Dr_NeilA/statu
/Dr_NeilA/status/1789188183105626464
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LLaMA 3 Model Outperforms GPT-4 on Classification Tasks
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A few days ago, a team released a model/product (trained on LLaMA 3) that beat GPT-4 at classification tasks for training data generation. Anyone remember the name?
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AI Researchers Cannot Discuss AGI Without Moravec’s Paradox
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ai researchers try to discuss agi without referencing moravec challenge (IMPOSSIBLE)
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Parameter Efficiency and Scaling Laws in Neural Networks
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waiting for @untitled01ipynb to make a “if you use 100% of your parameters” meme whats the intuition behind the 10x size : 2x capability ratio? feels like even if the network is sparsely connected it should scale better than that
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Emotion Classification in AI: Beyond Basic Seven Categories
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Thank you very much for the reply and links! From a data-driven perspective, the ~7 basic emotions seem to have too much variety within each class (cf. work by @LFeldmanBarrett
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Testing scaling hypothesis with internet-scale data and distribution shift
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If we had billions of dollars to spend we could test this hypothesis empirically — try to fit a big curve on *all the data* — literally everything that's on the Internet, and then test if it can adapt to things that are slightly out of distribution, like ARC tasks. Oh, wait a
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Human Intelligence: Dynamic Adaptation Beyond Static Pattern Matching
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Humans aren't parametric curves fitted to a data distribution and performing static test-time inference. The entire point of human intelligence is to let us operate in the present, which is always unlike the past.