This glossary includes all relevant terms and definitions used across the various packages within the neurons.me ecosystem.
all.this: A comprehensive framework within the neurons.me ecosystem, facilitating the standardization and structuring of web elements and data for neural network processing.
API (Application Programming Interface): A set of rules and protocols that allows different software entities to communicate with each other within the neurons.me ecosystem.
Bias: A neuron's attribute in a neural network that allows the network to represent patterns that do not pass through the origin.
cleaker: A security-focused utility, providing encryption and decryption services to safeguard data within the neurons.me ecosystem. It Hashes Digital Instances for creating DIDS. Its role is to function as a Digital Identifier (DID) creator; make cleaker accept an object (like a .me profile) and return a unique DID for it.
Convolutional Neural Network (CNN): A class of deep neural networks, most commonly applied to analyzing visual imagery, available within the neurons.me framework.
DataFormatter: Refers to a set of tools or modules within the all.this ecosystem designed to prepare and format data for neural network processing. Specific formatters like this.text or this.img provide functionalities tailored to text and image data, respectively.
Epoch: One full training cycle on the entire dataset, used in the context of training neural networks within neurons.me.
i.mlearning: A module dedicated to structuring datasets for machine learning, streamlining the data preparation process for training within the neurons.me environment.
Layer: A collection of neurons that process information in a neural network, structured in a way to facilitate complex data operations in neurons.me.
Lisa: Emerging from the collaboration and integration of multiple monads, Lisa represents the totality or the networked whole within the neurons.me framework. It signifies the unified system where individual monads come together, managed and networked through utilities like netget, to create a sophisticated, distributed intelligence or application.
monad: The monad of which we shall here speak, is nothing but a simple substance, which enters into compounds. In the context of neurons.me, a monad is defined as a basic, self-contained unit of functionality. It embodies the principle that even the simplest components possess their own intrinsic properties and capabilities. Monads are akin to building blocks within the ecosystem, each contributing unique functions and attributes.
MonadLisa: MonadLisa stands as the quintessential embodiment of the neurons.me technology, serving as the central platform where the diverse modules and utilities of the neurons.me ecosystem converge. It is not just a product but a demonstration of the modularity and integration capabilities inherent in the neurons.me framework.
netget: A networking utility that enhances data retrieval and communication capabilities within the neurons.me framework utils, ensuring efficient data exchange and processing as well as setting up gateways and managing networks. Acting as the network management tool within the neurons.me ecosystem, netget plays a pivotal role in connecting and managing the monads. It facilitates the communication, coordination, and data exchange among the monads, enabling the formation and functioning of Lisa.
Neural Network: Computational models inspired by the human brain's structure and function, used within neurons.me to process complex data inputs.
Neuron: In the context of neurons.me, a neuron is a basic computational unit of a neural network, capable of processing and transmitting information through its connections to other neurons. See more in NeuralNetwork.
neurons.me: Represents an entire ecosystem of technologies developed under this brand. As the overarching umbrella, neurons.me encapsulates a family of tools, frameworks, and libraries, all designed to interoperate and contribute to the broader vision of advanced neural network modeling and data processing.
neurons.me npm package: is a specialized library within the broader neurons.me ecosystem, meticulously crafted to work in conjunction with the all.this dataformatters and various utility modules under the neurons.me umbrella. This package is specifically tailored to facilitate the creation, management, and training of neural networks, providing a robust foundation for developers to build upon.
PixelGrid: A module within the all.this ecosystem that standardizes image data into a grid format, enhancing image processing and analysis.
Tetragrammaton: Within the neurons.me ecosystem, Tetragrammaton serves as a critical utility designed to orchestrate the interaction and functionality of monads. Drawing inspiration from the concept of simplicity and unity, Tetragrammaton ensures that these individual components (monads) can be seamlessly integrated to form a more complex, interconnected system—referred to as Lisa.
Training Set: A dataset used to train neural networks in neurons.me, enabling the models to learn and adapt based on provided inputs and outputs.
Utils: In the context of the neurons.me ecosystem, "Utils" refers to a suite of utility libraries designed to offer specialized functionalities and support various aspects of neural network operations and data handling. These utilities are not data formatters but are essential tools that provide specific use cases or functionalities to enhance the efficiency and capabilities of the neurons.me platform.
neurons.me - all.this - cleaker - v.path -netget -i.mlearning - Tetragrammaton -
Each utility is designed to interoperate seamlessly within the neurons.me ecosystem, providing targeted functionalities that complement the data formatting and neural network modeling processes.
v.path: A utility within the neurons.me ecosystem that manages and tracks memory path usage, applying network-wide memory management methods.