He was very active in compiling the PASCAL Visual Object Challenge which was one of the inspirations for ImageNet.
RESEARCH
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LLMs Reproducing Failed 1968 Planning Methods, Not True Planning
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@BobbyGRG It's reproduced a planning method from 1968; Nils Nilsson's book "Problem Solving Methods for AI", on 2nd most trivial possible planning problem. All thought it would scale–didn't for deep reasons. LLMs simulating 50+ year old failed planning methods is not planning. -
LLMs Lack Emergent Reasoning, Success Is Lucky
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Many people are trying to make excuses for why this trivial problem trips up LLMs. Occam's razor should remind you that there is no emergent reasoning in LLMs. Instead it gets lucky (and it is astonishing that it works so well–that says something deep about our language)
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Mixture-of-Agents Architecture Enhances Language Model Capabilities
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Mixture-of-Agents Enhances Large Language Model Capabilities Wang et al.: https://
arxiv.org/abs/2406.04692 #ArtificialIntelligence #DeepLearning #MachineLearning -
Eigenvectors and Principal Components for Dimensionality Reduction
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Eigen vectors helps in identifying the directions of highest variance in the data, which are then used to construct principal components. These principal components allows you to represent the data in a lower-dimensional while saving as much meaningful information as possible.
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Implementing PCA Class with NumPy and Initialization Setup
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First Import numpy and define a class named "PCA" to encapsulate the operations. In the __init__ constructor let's initialize the number of components to reduce to, which is n_components, and similarly create placeholders for mean and eigenvectors.
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Principal Component Analysis PCA Explained and Implemented in Python
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Princiapal Component Analysis (PCA) clearly explained and implemented from scratch in Python:
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Eastern Version of Noam Shazeer’s AI Architecture Innovation Arc
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this is the eastern version of the noam shazeer arc inventing a 10x better transformer architecture and not telling anyone until yesterday in the pursuit of providing ai gf
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Cleanlab: Essential ML Training Data Quality Tool
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Cleanlab is a must ML training process
Thanks for sharing
