Can AI Teach Itself?

With each day passing, artificial Intelligence has expanded its legs to a wider range of domains. It seems to exist everywhere and is very helpful as well. Deep Learning and Machine Learning have largely contributed to the growth of Artificial Intelligence. We have up till now explored a lot in the field of supervised learning, but there is something called unsupervised algorithms as well. So let us get a better idea about these terminologies.

Supervised and Unsupervised Learning Algorithms

Supervised Learning refers to the process in which the model is provided a complete training for a particular datasheet along with the inputs as well as outputs and is then able to recognize the data for different data, after the training. For instance, we have pictures of different images of vegetables and the task of the model is to recognize them. We train the model about the color, size, shape, or even taste of the vegetable. After the training, our model is able to recognize vegetables according to the algorithm. 

Now let’s discuss the other form of learning which is Unsupervised Learning. The focus of unsupervised machine learning algorithms is to allow AI to search for patterns on its own. As the name indicates, it does not need any supervision. Now unlike the above case of vegetables, here we only provide inputs to the model and it will recognize patterns and structures itself and then provide different groups in which vegetables will be segregated on the basis of some common features indeed. 

AI vs Human Brain

Image Source: Orientsoftware.com

Unlike humans, computers have to go beyond supervised learning and aim for learning to learn, so that they gain human-like knowledge. We learn from our experiences and surroundings and on the other hand, they have to opt for the hit and trial method, predicting from patterns and observation. AI has the capabilities to process vast amounts of data and that too accurately. Our human brain can collect and store data but not as much as the machines. AI depends on efficient algorithms and is very essential. If we desire AI to be better, we have to make it more adaptive and this includes the capability of doing multi-tasks effectively. 

Teaching Itself to Teach

If you are thinking “can AI learn on its own,” then yes, AI can teach itself to learn, but to be very honest it is going to be a long way to get a perfect model which learns each and everything by its own self. Meta-reasoning and Meta-learning are two very important terms that are going to help a lot in the times to come. 

Meta-Reasoning is about logical reasoning and can help AI in drawing statistical observations. Studies are continuously being conducted in this field to bring AI and the human brain closer in terms of making realistic decisions. Meta-Learning faces the challenge of picking between large amounts of data and limited data for the model to train. Both of these help in making AI a more generalized learner. This will lead to a predictive learner as the future of AI. Systems will recognize patterns and on analyzing them, predict new patterns and observations as well.

Closing Verdict

Adapting to these new ways of learning and teaching is going to take time as scientists and researchers are working on larger scales to achieve success in this part of AI. Yann LeCun, vice president and the chief A.I. scientist at Facebook was asked whether we can make machines as smart as humans, to which his answer was nothing different. He was completely assured that it is going to happen for sure, but it is going to be a matter of time. 

We have made huge advancements in the field of technology. Who knew machines could ever think and do tasks similar to humans? But now Artificial Intelligence is no longer an unknown term to the greater world. So don’t lose hope because you never know AI will start teaching itself in no time.