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Astrophysics#N-body Simulations🔬 ResearchAnalyzed: Jan 3, 2026 17:15

The Growth of Sverre's NBODY Industry

Published:Dec 30, 2025 15:40
1 min read
ArXiv

Analysis

This paper serves as a tribute and update on the evolution of N-body simulation codes, particularly those developed by Sverre Aarseth. It highlights the continued development and impact of these codes, even after his passing, and emphasizes the collaborative and open-source spirit of the community. The paper's significance lies in documenting the legacy of Aarseth's work and the ongoing advancements in the field of astrophysical simulations.
Reference

“NBODY6++GPU and NBODY7 entered the scene, and also recent new competitors, such as PETAR or BIFROST.”

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Research#llm📝 BlogAnalyzed: Dec 28, 2025 21:57

Making deep learning perform real algorithms with Category Theory

Published:Dec 22, 2025 15:01
1 min read
ML Street Talk Pod

Analysis

This article discusses the limitations of current Large Language Models (LLMs) and proposes Category Theory as a potential solution. It highlights that LLMs struggle with basic logical operations like addition, due to their pattern-recognition based architecture. The article suggests that Category Theory, a branch of abstract mathematics, could provide a more rigorous framework for AI development, moving it beyond its current 'alchemy' phase. The discussion involves experts like Andrew Dudzik, Petar Velichkovich, and others, who explain the concepts and limitations of current AI models. The core idea is to move from trial-and-error to a more principled engineering approach for AI.
Reference

“When you change a single digit in a long string of numbers, the pattern breaks because the model lacks the internal "machinery" to perform a simple carry operation.”

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Research#Graph Neural Networks📝 BlogAnalyzed: Jan 3, 2026 07:14

Dr. Petar Veličković (Deepmind) - Categories, Graphs, Reasoning [NEURIPS22 UNPLUGGED]

Published:Dec 8, 2022 23:45
1 min read
ML Street Talk Pod

Analysis

This article summarizes an interview with Dr. Petar Veličković, a prominent researcher at DeepMind, discussing his work on category theory, graph neural networks, and reasoning, presented at NeurIPS 2022. It highlights his contributions to Graph Attention Networks and Geometric Deep Learning. The article provides a table of contents for the interview, links to relevant resources, and mentions the host, Dr. Tim Scarfe.
Reference

“The article doesn't contain direct quotes, but summarizes the discussion on category theory and graph neural networks.”

PermalinkML Street Talk Pod