There have been rapid advancements in technology over these past decades. With the increased acceptance of newer features and innovations, companies are competing in the technological battlefield to create the best technology for consumers. One such idea that transformed the world of technology is that of artificial intelligence, or AI. Many movies have been made that explore the limits of AI’s capabilities, and have never failed to pique the interest of the general public. Today, we see deep learning and self-learning AI — one of its most explored aspects– almost becoming a reality.
Artificial Intelligence, in one manner, works on the concept of deep learning. This refers to the algorithms that work through various data streams to find patterns. Through these patterns, they find commonalities and work on those. This way, the machine comes to know how it is supposed to react in particular situations; this is quite integral to how many sectors function. Today, different industries are adopting deep learning to gain maximum information about their consumers, led by behemoths such as Google, and Facebook. For instance, when we surf through certain products while shopping on online platforms and then open another page, we tend to see advertisements for those products– this is deep-learning in action. These systems use AI to learns our likes and dislikes and then capitalize on them. Robotics also banks heavily on AI. This sector has developed robots like Sophia, who is a humanoid and has been developed to an unprecedented extent. With these technological leaps being taken, the possible future of AI and deep learning is on everyone’s mind.
Recently, however, MIT published a study where it analysed around 25 years of research pertaining to artificial intelligence, and concluded that deep learning is coming to an end. This might seem a surprise to many, but has evidently been a lot of frenzy in the technology sector where people keep coming up with different ideas, which battle to survive. So while AI is not going anywhere, the way we use it is changing rapidly. Though deep learning is a fairly recent technique, it is actually not quite difficult to imagine its gradual fade-out. It will surely act as a base for future technologies, but, as the study says, the possibility of its obsolescence is quite real.
Where on one hand people are striving to come up with new and exciting ways to develop AI to aid human lives, on the other, there are skeptics of these developments. This reservations possibly stems from the fear of the unknown and a fear of loss of autonomy. Moreover, as technology is developing more and more quickly, the shelf-life of existing technology is shrinking rapidly. In such a situation, having to replace phones, laptops, or other gadgets every few years due to heightened planned obsolescence is not economical for most people, which also adds to this stiffness towards technological development.
It is certainly quite evident why this fervent quest of new technologies is there in the first place– to find a way to replicate human intelligence. It is a method of establishing our superiority and ensuring its continuance, a part of all our inventions and discoveries for the same purpose. This should not necessarily be considered problematic, as domination of one species by another is just the way nature functions; technology is our way of working as efficiently as possible, and allows us to overcome the obstacles natural selection puts in front of us. Thus, if things take their natural course, deep learning can indeed become a blip in the past with more robust technologies taking over instead. Anything quantitative or qualitative is hard to determine for a layman, but scientists will definitely keep a tab on the way artificial intelligence will evolve. It is just a matter of time to see what happens.
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