T-5: The AI Brain

Modern AI has leveraged the best of modern developments. As parts of the world become increasingly connected, collected data grows. As electronics become smaller and faster, compute centers become more powerful. With this in mind, the algorithms and methods of developing intelligent systems can be implemented.

• Machine Learning

• Classification

• Deep Learning

• Artificial Neural Networks/Generative AI

• Memory and recall methods

• and the list grows

Cloud resources are increasing with increasing capability, both in compute power and storage. This enables the use of the maturing AI techniques to greatly improve over previous versions. And these are the techniques at the cognitive center and decision making processes of the AI brain. To learn more, several educational sites have emerged, such as:

https://machinelearningmastery.com/start-here/

The number and depth of tools supporting the AI brain, commonly known as machine learning (ML), are growing by leaps and bounds. Growing number of compute resources based on massively vectorized compute nodes have become available. Even the emerging ideology of a strong AI, where the AI brain becomes self-aware, show signs of becoming real.

And what about this fantastic and near mythical technology known as quantum computing? It really is well-suited for some forms of AI algorithms, but is not yet widely utilized. So for now, the concern for quantum computing is the same for any method of problem solving for a self-learning machine. The boundaries for the training set must be well defined.

T-5 days