klotz: computer science*

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  1. A connection between descriptive set theory and computer science has been discovered, allowing problems in one field to be rewritten and solved in the other by Anton Bernshteyn.

    Problems in descriptive set theory (measuring infinite graph colorings) are mathematically equivalent to problems in distributed algorithms (efficient network coloring).
  2. A new paper by SFI Professor David Wolpert introduces a mathematically precise framework for the simulation hypothesis, challenging several long-standing claims and opening up new questions about simulated universes.
  3. Descriptive set theorists study the niche mathematics of infinity. Now, they’ve shown that their problems can be rewritten in the concrete language of algorithms.
  4. Researchers at MIT’s CSAIL are charting a more "modular" path ahead for software development, breaking systems into "concepts" and "synchronizations" to make code clearer, safer, and easier for LLMs to generate.

    MIT researchers are proposing a new software development approach centered around "concepts" and "synchronizations" to address issues of complexity, safety, and LLM compatibility in modern software.

    Concepts are self-contained units of functionality (like "sharing" or "liking") with their own state and actions, whereas synchronizations are explicit rules defining how these concepts interact, expressed in a simple, LLM-friendly language.

    The benefits include ncreased modularity, transparency, easier understanding for both humans and AI, improved safety, and potential for automated software development. Real-world application: has been demonstrated by successfully restructuring features (liking, commenting, sharing) to be more modular and legible.

    Future includes concept catalogs, a shift in software architecture, and improved collaboration through shared, well-tested concepts.
  5. A recent study shows that one large language model (LLM) demonstrates impressive linguistic analysis abilities, rivaling those of human linguistics graduate students. Researchers tested LLMs on complex linguistic tasks, including recursion and phonological rule inference, revealing that OpenAI’s o1 model performed significantly better than others, challenging conventional views on the limits of AI in understanding language.
  6. A new paper demonstrates that the simplex method, a widely used optimization algorithm, is as efficient as it can be, and explains why it performs well in practice despite theoretical limitations.
  7. Alan Turing and John von Neumann saw it early: the logic of life and the logic of code may be one and the same. This article explores the idea that life, at its core, might be computational, drawing parallels between DNA, computation, and the work of Turing and von Neumann.
  8. In cellular automata, simple rules create elaborate structures. Now researchers can start with the structures and reverse-engineer the rules.
  9. The story of ERNIE, a computer built by Thomas Flowers to generate random numbers for the UK's Premium Bonds lottery, evolving from neon-lamp based randomness to quantum technology.

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