Our knowledge, from the very beginning, relays on data that are the foundation of what we called experience. We build our experience by collecting data. One example is the medical science where doctors have learned by collecting data (symptoms) and put them in relation with the diseases learning how to find the right cure from the continuous observation of the evolution of these data.
Let’s think about history; we have learned to know the past of human civilization by collecting data from the most varied sources, putting them in relation to each other to reconstruct what may have happened, to understand how people lived in the most remote times, to understand the relationships and events that have occurred.
So why we call out time the big data time and talk about the big data revolution? What is changed? Today, what has changed is the amount of data we have at our disposition, opening a radically new set of opportunities.
Unlike 50 years ago, today, we have billions of data of all kinds available. This enormous amount of data is the foundation of an immense value for humanity. The relation hidden in the data represents the keys to understand links between things and situations that generates a new level of knowledge that enables us to find new ways to approach our life.
This concept is valid for medicine, architecture, social interactions, and in general for any aspect of our everyday life, including day-by-day activities.
The main question is how do we extract value from all this data?
The real problem is that data are billions of billions of billions; extracting useful information from them is not trivial, other than that, every day the amount of data grows exponentially because of the spread of the adoption of new technologies.
The answer is called Machine learning and Deep-Learning which give life to what we call Artificial Intelligence.
Through machine learning, we are going to teach machines how to learn from data. It is a statistical and probability process that relates data to effects, discovering their intrinsic characteristics, and throughout their evolution creates knowledge. The procedure is very similar to how we learn from nature.
Humans are statistical machines too, making hypotheses that arise from observation, and by predicting situations based on the probability that this will occur without experimenting, thanks to experiences.
If we drop an apple from our hand, we know that it will go to the ground; experience tells us that an object left free to move in the space will fall to the ground if there is nothing in the middle. If it will fly, we would be amazed because we expect something different.
When we see something new, that we do not know we think statistically. We make speculations based on what we know, we said it could be this, or perhaps that, associating to each hypothesis a percentage of chance.
Well, machines do the same thing. It becomes possible to amplify human knowledge and create new scenarios thanks to the data combined with a statistical learning process. We called this process Artificial Intelligence (AI). We can change every aspect of our life using AI and machine learning over data and reaching new level of knowledge bringing new capabilities in every human aspect. We have the possibility of obtaining new information and create new tools that make our life better because AI is not just a virtual assistant like Alexa or Siri; Artificial intelligence is a real revolution that we could compare to the most radical one that humankind has experienced until now.
Artificial intelligence is a serious matter that comes not from computer science but from advanced mathematics and neurosciences; Math and neurosciences are the engines and inspiration for increasingly complex and fascinating mathematical models, in short words AI is a serious, complex, and fascinating technology.
There are various types of artificial intelligence and field of research and development connected to them. Let us start with the most widespread form today the Narrow AI, this is the basic-one, it imitates or tries to imitate human capabilities.
There is a second kind of AI, is called general artificial intelligence (GAI).
GAI wants to replicate capabilities that are quite similar to human ones, including creativity and the ability to design original objects with incredibly advanced characteristics. There are many examples of creative AI in music and engineering today.
Finally, yet importantly, there is a third kind of AI called “Superintelligence”.
Superintelligence aims to be superior to human capabilities. While superintelligence is still science fiction, the other two are a reality.
Let us forget for a moment the AI and Machine Learning applications that we already know like virtual assistants, self-driving machines, and forecasting prediction, or personalized advertising, and let us think in a wider way.
Let us imagine having an AI system that is able to learn, always through data, all the characteristics of an object, and then, it can be able to put all the information in relationship with specific features that we want to have, for example, the object to be extremely light.
Today, we can ask to this AI system to redesign the object to match the goal. More in general, we can ask to the AI to project, and even invent better quality products, that can be produced with less raw material and in a more ecosustainable way.
In the same way, we can ask AI to create and project a new generation of energy-efficient buildings, at much lower costs the ordinary ones. AI can design safer and more efficient car chassis; it can design new tools with more ergonomic and original shapes that will make us do more and more extraordinary things easily. AI can also have an eye on eco-sustainability and a benefit for the planet reducing energy consumption and pollution production saving raw materials. We just have to experience this new era of humanity as protagonists led by intelligent and revolutionary use of data, keeping in mind, that it is just the beginning!
About the Author
Emilio Billi is the Co-Founder and Chief Technology Officer of A3CUBE. With nearly two decades in the IT industry, Emilio has proven knowledge of the high-performance computing and datacenter markets. He has developed and designed numerous server and supercomputing systems, including massively parallel virtualized clusters and hyperscalable storage systems as well as other high-performance interconnection and networking systems. He holds eight patents in computer architecture design and related technologies.
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