Finite brains, infinite minds, and the great mistake of the Technological Singularity theory (Part 1)

The Technological Singularity theory is essentially based on the fact that we are going beyond Moore’s Law, creating artificial brains increasingly powerful, including in the number of neurons, superior to the human. However, as encouraging as this law is, to create such theories, physical resources are limited, just like our brain. And what if we […]

PoI (Proof of Intelligence): a new concept to validate cryptocurrencies transactions using Artificial Intelligence (Part 1)

What is the best concept to validate cryptocurrencies transactions? Proof-of-Work (PoW), Proof-of-Stake (PoS), Proof-of-Capacity (PoC), or any other? Before starting a polemic of which is the best of them, as several you will find on Internet, I would like to present a different idea, which is using an artificial intelligence system (AI), or, preferably of […]

THINK>B, a new Cognitive Architecture based on a collective intelligence and multiple propagations and dimensions mind model (Part 2)

This is a continuation (Part 2) of the THINK>B concept and Artificial General Intelligence (AGI) presentation and the Cognitive Architecture based on a collective intelligence and multiple propagations and dimensions mind model [1]. As stated before THINK>B is based on six dimensions, listed below, that can be trained by a new ANN (Artificial Neural Networks) […]

Multi-Propagation Hierarchical Turing Machine (MP-HTM): a new architecture to model reasoning (Part 1)

In this article, I will propose and describe a new architecture to model reasoning, which consists of an evolution of the Multiple Propagations Artificial Neural Networks, a new ANN model, and vision, proposed at [1][2][3]. So, let’s start by reviewing the idea of multiple propagations and MP-ANN. Artificial Neural Networks, or ANNs, help to create […]

AI.Why: A new architecture for creating AI models with interpretability from scratch (Part 1)

Despite the advance of Artificial Intelligence, mainly the technology of machine learning and deep learning, the problem that these systems can’t really explain how they got their answer is still a great challenge for this technology and its acceptance. Actually, this is currently an active area of research, named Interpretability, that some researchers call as […]