"Artificial General Intelligence (AGI) is the supreme test of the technology scientists, and often the supreme disappointment." - paraphrasing Ansel Adams, photographer
In a complex world constantly reshaped by rapid technological advancements, Algorithmic Artificial General Intelligence (AAGI) stands as the pinnacle of human achievement—a syntetic intelligence capable of learning, reasoning, taking decisions and adapting like a human being. At The Mindkind, we are driven by a profound scientific curiosity and determination to explore the true potential of AAGI. We believe that the future lies in the seamless fusion of human creativity and machine precision, and it is our unwavering commitment to make that vision a reality.
To achieve that goal, we had to confront three significant challenges. Firstly, we lack an understanding of the brain's structure and dynamics. Secondly, current technology does not enable us to capture all the information processed by a living brain. Thirdly, each brain is unique, so we need to explore them statistically.
To overcome these constraints, we have employed a complementary approach by:
Our ETR Foundation Model is born from a profound comprehension of human subjective experiences and mental dynamics, firmly grounded in a deep neuroscientific research. It offers a solution to the four primary challenges currently facing AI:
The 'Black Box' issue arises because we don't know where or how AI-specific knowledge is stored.
Trustworthiness, or the 'Black Swan' phenomenon, is a concern with statistical models, as they can generate nonsensical responses when confronted with the unknown.
The challenge of adaptability, as it is incapable of conceptualizing and extrapolating available knowledge to address new problems.
The efficiency challenge, as it requires substantial amounts of data, time, energy, and computational resources for learning.
We have worked with some knowledge that, today, cannot be found elsewhere, to bridge the gap between the human brain, mental processes, and machine learning algorithms. By developing a robust AAGI model, we are paving the pathway to unraveling the mysteries of the human mind.
Working with a wide range of real-life experiences, disentangled to uncover the common "active principle" that lies within them all.
Building upon neuroscientific advancements which stem from both, fundamental and applied research in affective neuroscience.
Using a complex-systems approach to implement an agent-based cognitive architecture that lets us setting brain dynamics' complexity apart.
Developing technology that shorten and lighten the time and resources of learning processes.
A technology capable of initiating its own internal self-learning and behavioral processes based on its own intrinsic motivations.
The closest a technology has ever been to replicating the human mind and consciousness.
Envision your personal Artificial General Intelligence that seamlessly accompanies you in your daily interactions with the digital realm, effortlessly integrated into your life, enhancing your experiences and simplifying your tasks.
We make sense of the digital environments by bringing Avatars and NPCs to life with human-like capabilities.
Developing the first AAGI operating system that fully enables robots to assist us in tasks that were previously limited to humans.
Fully AAGI-powered autonomous space robots, initiating exploration and exploitation of extraterrestrial environments prior to human arrival.
Our human-like AI technology for autonomous machines has garnered significant recognition and public funding from EU, national and regional governments.
The latest news from TMK and the AI ecosystem.
Mario Garcés, founder and CEO of The Mindkind, a company that is developing the first human-level Algorithmic Artificial General Intelligenc
We are thrilled to announce that we have successfully advanced to Stage 2 in the highly competitive EIC Accelerator program !!!
Today we have started the first edition of the #SolvAI transdisciplinary congress, running from May 29th to 31th in #Castejón_de_Sos
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