Bzogramming

Bzogramming explores the intersections of programming language design, both applied and theoretical, with elements of neuroscience, complexity theory, and technological innovation. It delves into futuristic computing paradigms, efficiency in programming tools, the physical and conceptual limitations of computing, and the potential of integrating traditional engineering and computational approaches.

Programming Language Design Technological Innovation Theoretical and Applied Computing Neuroscience and Computing Complexity Theory Quantum Computing Graphical Programming AI and Machine Learning Trends Reversible Computing Physical Constraints in Computing

The hottest Substack posts of Bzogramming

And their main takeaways

Geometric Constraints on Computing

30 implied HN points • 29 Jan 24
🕹 Technology Computing Physics Architecture Optimization Future Trends
  1. The physical constraints of computing, such as distance and volume, significantly impact performance and efficiency.
  2. Parallelism at different scales within a program can affect latency and performance, offering opportunities for optimization.
  3. Considerations like curvature of computation, square-cube law, and heat generation play a crucial role in the design and limitations of computer chips.

Non-Newtonian Computing?

30 implied HN points • 07 Jan 24
🕹 Technology Computing Physics Cryptography Algorithms AI
  1. Physics has alternative framings like Lagrangian and Hamiltonian mechanics, which could inspire new ways of viewing computation.
  2. Reversible computing, preserving information by having bijective gates, is crucial for energy efficiency and future computing technologies.
  3. Studying constraint solvers and NP-complete problems can lead to insights for accelerating search algorithms and developing new computing approaches.

Superconductors and Such

53 implied HN points • 01 Aug 23
🕹 Technology Materials science Software Imaging Algorithms Business Models
  1. There is potential for room-temperature superconductors with simple materials like lead, phosphate, and copper.
  2. A shift back to innovation in physical technologies, like hyperspectral imaging and geometric folding algorithms, might lead to significant advancements.
  3. A reemphasis on traditional engineering fields, such as cars and rocket engines, is essential for future innovations outside of software.
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A Realistic Look at Quantum Computing

22 implied HN points • 06 Mar 23
🔬 Science Quantum Computing
  1. Quantum computers face significant engineering hurdles that limit their practical applications
  2. Quantum systems have a time-reversibility property, making them a type of reversible computer
  3. Reversible computing involves creating gates with the same number of inputs as outputs, like the CNOT gate

Algorithmic Dark Matter

15 implied HN points • 13 Feb 23
🔬 Science Computation Biology Quantum Computing
  1. In computer science, there are hidden structures and algorithms that go beyond our current understanding.
  2. New paradigms of computation may hold solutions to complex problems, such as optimization and error correction.
  3. Exploring fields like quantum computing and biochemical computation could lead to groundbreaking discoveries in algorithmic tools.

Some Brief Thoughts on Recent AI Trends

15 implied HN points • 06 Feb 23
  1. AI can still benefit from traditional algorithms like Locality-Sensitive Hashing and n-grams, despite the popularity of deep learning
  2. AI-generated images often exhibit flaws resembling those produced by algorithms like Wave Function Collapse, indicating potential for traditional techniques
  3. Hybrid approaches combining traditional search algorithms with 'outdated AI' techniques could offer competitive solutions to current neural networks

The Lure of Graphical Programming

7 implied HN points • 13 Mar 23
🕹 Technology Programming Visualization Coding Tools Innovation
  1. Visual programming languages with colored boxes and lines may not necessarily make code easier to understand.
  2. Human vision focuses on categorizing small pieces of images at a time, similar to how code should be structured.
  3. Text-based programming already utilizes spatial conveyance of meaning through features like indentation, highlighting the importance of enhancing visual tools in coding.