arXiv:2601.00864v1 Announce Type: cross Abstract: Graphs are commonly used in machine learning to model relationships between instances. Consider the task of predicting the political preferences of users in a social network; to solve this task one should consider, both, the features of each individual user and the relationships between them. However, oftentimes one is not interested in the label of a single instance but rather in the distribution of labels over a set of instances; e.g., when predicting […]

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Mastering unsupervised learning opens up many avenues for a data scientist. There is so much scope in the vast expanse of unsupervised learning, yet many beginners in machine learning tend to shy away from it. I’m sure most newcomers will stick to basic clustering algorithms like K-Means clustering and hierarchical clustering. Clustering is an essential technique in machine learning and is used widely across domains and industries (think about Uber’s route optimization, Amazon’s recommendation system, Netflix’s customer segmentation, […]

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arXiv:2512.24497v2 Announce Type: replace-cross Abstract: A long-standing challenge in AI is to develop agents capable of solving a wide range of physical tasks and generalizing to new, unseen tasks and environments. A popular recent approach involves training a world model from state-action trajectories and subsequently use it with a planning algorithm to solve new tasks. Planning is commonly performed in the input space, but a recent family of methods has introduced planning algorithms that optimize in the learned […]

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Missed a post last week due to the Thanksgiving long weekend :-). We had gone to San Francisco to see the city and try out a couple of hikes). Just FYI – strolling around SF is also as much a hike as any of the real trails at Mt Sutro – with all the uphill & downhill roads! As for Robotics, I am currently on Week 3 of the Mobility course, which is more of physics than ‘computer […]

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In one of the recent interviews, Elon Musk has warned humanity that artificial intelligence could lead to “civilization destruction”. While talking about AI, so advanced that it will threaten our society, to most experts seems preliminary, one thing is certain: we depend on artificial intelligence as much as AI depends on us. Artificial intelligence systems run in your phone to help you capture better pictures, find relevant materials online, and optimize your storage space. But it all comes […]

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When I started writing about AI in 2019, my first article was dedicated to what machine learning is and how it works. It explained the difference between weak and strong (or general) AI and mentioned that we have no idea how to create the latter. Well, in 2023, maybe we actually (finally!) do. I’m talking about multimodal learning. Don’t get me wrong – multimodal learning wasn’t a new concept already in 2019. Back then, TechRepublic called it the […]

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Diverse explanations or theories of consciousness are arrayed on a roughly physicalist-to-nonphysicalist landscape of essences and mechanisms. Categories: Materialism Theories (philosophical, neurobiological, electromagnetic field, computational and informational, homeostatic and affective, embodied and enactive, relational, representational, language, phylogenetic evolution); Non-Reductive Physicalism; Quantum Theories; Integrated Information Theory; Panpsychisms; Monisms; Dualisms; Idealisms; Anomalous and Altered States Theories; Challenge Theories. There are many subcategories, especially for Materialism Theories. Each explanation is self-described by its adherents, critique is minimal and only for clarification, […]

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