Indefinite Scalability for Living Computation

Authors: David Ackley

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental for several years we ve been working on indefinite scalability, mostly in simulation. Unless stated otherwise, the material in this summary paper is drawn from (Ackley and Cannon 2011; Ackley 2013a; 2013b; Ackley, Cannon, and Williams 2013; Ackley and Small 2014; Ackley and Ackley 2015).
Researcher Affiliation Academia David H. Ackley University of New Mexico Department of Computer Science Albuquerque, NM 87131 ackley@cs.unm.edu
Pseudocode Yes Figure 2: The MFM per-tile event loop. (See text.)
Open Source Code No The paper discusses the development of the ulam programming language and its compilation but does not provide any link or explicit statement about making the source code publicly available.
Open Datasets No The paper describes simulated systems (e.g., Demon Horde Sort, self-assembling data switch) which appear to generate or process internal data, rather than using external, publicly available datasets. No dataset name, link, or citation is provided.
Dataset Splits No The paper does not mention any training, validation, or test dataset splits, as its experimental work is based on simulations of a proposed architecture rather than traditional machine learning datasets.
Hardware Specification No The paper mentions "2009-era prototype tile hardware at bottom" in Figure 1, which refers to the conceptual hardware of the Movable Feast Machine itself. It does not provide specifications (e.g., CPU, GPU models, memory) of the hardware used to run the simulations mentioned in the paper.
Software Dependencies No The paper mentions that 'ulam compiles into C++, and from there via gcc to machine code', but it does not specify version numbers for C++ or gcc, nor does it list any other software dependencies with version information.
Experiment Setup No The paper describes the functional aspects of the simulated systems and their behavior (e.g., 'average events per site'), but it does not provide specific experimental setup details such as hyperparameters, optimization settings, or other concrete configuration parameters for the simulations.