Intelligence machine learning Self-driving vehicles, medical diagnostics, and conversational assistance will all experience substantial technological advancements this decade. 2020 will mark the beginning of a new era for digital transformation.
Just a few days have passed
since the beginning of a new decade, a milestone in time, a psychological barrier that will mark the maturation of some technological advances, such as the unlimited el-salvador phone number list versatility of smartphones, something so common that we no longer remember what life was like before them. This will also be the starting point for the emergence of new advances, immersed in this era of digital and technological transformation.
When we talk about Artificial Intelligence
(AI), it is intelligence machine learning not a new topic the electric oven from a domestic brand for anyone. Furthermore, as a concept, it was coined 60 years ago and, before we could observe its applications in real life, we already had an idea of its scope, impact and challenges, in the futuristic novel ‘I Robot’, by Isaac Asimov (1950).
However, from 2020 onwards, we will witness a new level of advancement in Artificial Intelligence. At this stage, the development of Machine Learning and Deep Learning will enable the new potential of AI to be deployed across multiple industries.
One area where we will see
substantial advances thanks to AI and its turkey numbers database evolving ability to learn is in self-driving vehicles.
Vehicles will no longer react solely through their sensors, where the greatest advances seen to date have been related to increasing their quantity and sensitivity. Now, the accumulation of data that the vehicle will perform will allow it to analyze and predict in real time the behavior of other vehicles, whether autonomous or driven by people, thus being able to react efficiently, according to the need. Something similar to what we humans do, but without the risk of falling asleep or looking at our cell phones.
Another discipline that will benefit
from the rise of Artificial Intelligence will be medicine. Thanks to data analysis and deep and automatic learning, it will be possible to develop intelligence machine learning drugs and molecules at a lower cost, since the production flow will have notable efficiencies in terms of research time and clinical trials.
Furthermore, the quasi-automatic processing of large
amounts of data will allow for more accurate medical diagnoses, especially in the case of so-called “rare diseases”, those that have a minimal incidence in the population, as is the case for several million inhabitants. We will also be able to know how this diagnosis was reached and what the most appropriate procedure is for its treatment. Doctors will undoubtedly benefit greatly from this progress, but patients will benefit even more.
Finally, the last major advance I will mention and that we will experience in this new decade is related to Conversational Artificial Intelligence. Assistants like Siri, Cortana or Alexa already perform very well in terms of efficiency and response time. However, the next step is towards natural language, to generate a conversation in which it is difficult to distinguish whether you are speaking to a human or a robot.
For this, the success rate will be close
to 100% or will have errors of just a few tenths, which means that for every 100 words, the assistant will fail at one or less. In this way, instead of having to adapt our expressions to them, they will be the ones who adapt to our way of speaking, which involves voice inflections, tones, nuances, idioms, sarcasm, irony and even small changes that denote when we lie or are nervous.
And innovation will not only affect spoken language; we will also see advanced applications in written matter. In addition to making coherent, intelligent and even creative comments, new conversational devices will have the ability to write long stories. Soon we will be reading a novel, and why not a saga, written by a robot. It may not win a Nobel Prize for Literature, or at least not in this decade.
Before I finish, I must clarify
The new scopes that I have just explained for the fields of Artificial Intelligence, Machine Learning and Deep Learning, I described in a context of binary computing, with bits, zeros and ones. However, quantum computing, with qubits and a potential for data processing millions of times faster than traditional computing, is already a reality and it is only a matter of time before we start seeing its applications in everyday life.