The first AI systems that can learn
Third generation. Systems capable of learning and gradually improving their performance.
In the first decade of the 21st century, the growth in computing power allowed the idea of machine learning to be realized. The essence of the teaching idea was to analyze the data of the process under study and sort the most successful moves in order to achieve the initially designated goal.
Further, the development of this concept of machine learning began to assume the possibility of changing the parameters of the current information processing algorithm. Now the machine was able to independently create more effective strategies within the original task.
A new generation of artificial intelligence, not only skillfully improving its own algorithm, but also got the ability to predict the dynamics and parameters of the expected result. Thus, the third generation of AI has become a modernized version of the second generation. Artificial intelligence algorithms retained their flexibility and were able to change the original framework (limiting) parameters. This has fundamentally improved the quality and usability of new artificial intelligence systems.
The most innovative ideas of the past two decades
Third generation plus. Deep learning and enhanced deep learning systems are emerging
To be honest, the ideas behind deep learning and enhanced deep learning have been around since the first generation of AI. But the technical neural networks of the first generations were more like models than working prototypes. In the past (twentieth) century, the low power of computing systems did not make it possible to turn the ideas of deep machine learning into reality.
But at the beginning of the 21st century, everything changed. Thanks to new high-performance computing systems, artificial intelligence complexes have an opportunity to learn and gain experience. Working with huge databases using tools integrated into multilayer technical neural networks made it possible to translate the ideas of deep and enhanced deep learning into reality.
These processes are extremely resource-intensive and relatively slow, but this is undoubtedly a serious step forward even compared to the third generation.
What is the difference between the third generation and the third generation plus?
To illustrate the differences, let's take a look at how Google's latest translation system works, which can be called an example of a third-generation plus.
In the newest translator, Google engineers have completely abandoned the detailed analysis of the formal rules for constructing linguistic constructions, focusing on a simple comparative analysis of ready-made natural language variants.
Working with huge databases and applying comparative analysis of the finished texts of the original language, Google has managed to achieve phenomenal translation accuracy and efficiency. Instead of trying to understand logical connections and interpret the meaning and meaning of the original text, Google works with translated material on the principle of a black box, relying only on the statistically most popular analogies.
Thus, the third generation plus strives to solve analytical tasks by searching for meaningful analogies in a large amount of information.
Something similar is used by DeepMind when creating a specialized artificial intelligence "Alpha Go" capable of successfully fighting a live player in the game of Go. DeepMind engineers have created a system that can use two neural networks at once. Both technical neural networks work on the principle of deep learning (third-generation plus). One neural network analyzes the position, and the second one analyzes the strategy used in the protocols of previous games. Together, these neural networks act as an enhanced deep learning system.
Best available
The third generation plus with enhanced deep learning algorithms is now the most advanced and real working artificial intelligence system.
Let's talk about what lies ahead
In the following articles, we will talk about what awaits the artificial intelligence industry in the near and distant future.
We will talk about fundamentally new fourth-generation AI systems.
What it will be, how it will be built, and, most importantly, how these new systems of the fourth generation will be fundamentally different from the current models of AI of the third and third plus generations.