From cars to medicine, digital platforms and Cognitive IT are everywhere.
It is thanks to the exploitation and modelling of data that ground-breaking platforms such as Uber or Airbnb came into being. It is also thanks to this use of data that “traditional” professions and sectors are gradually going through a transverse digital transformation process. Vehicles, through the autonomous car; medicine through the development of ultra-personalised molecules for individual treatment; and tomorrow, meteorology will for example be capable of predicting fog around an airport. Artificial intelligence engines capable of assimilating enormous quantities of data are already making huge leaps forward.
However, the Big Data revolution has not yet shown its full potential, first of all owing to a lack of maturity: Very few structures employ Data Analysts or Chief Digital Officers capable of processing and deriving value from the data. The second reason is the lack of computing power for real-time processing of the torrent of data generated by our activities, every day…
The second wave that awaits us will concern intelligence, or more precisely the ability of objects to act. The visible facet of this second wave is the robot, its ability to move around our world, then to interact with humans, including by means of speech. We are just a few years, perhaps a few months away from silicon brains capable of passing the famous Turing test.
The exponential growth in data is in particular driven by smart objects, with more than 50 billion of them populating the world in 2020. By that time-frame, 40,000 billion billion data will be generated… More than there are stars in the Universe!
First challenge: be able to interconnect and derive value from data in the coming years
We will have to collect these data and then be able to count, identify and isolate them, but also connect them to each other at any moment, and place the various objects in a given order. This is the first challenge. To meet it, machines of exceptional power – supercomputers – are required, along with a new generation of software, working differently from the computers we have been using for the past 30 years and which are based on batch processing. The days when computer operators had time to save data, restore them or restart processing in the event of a breakdown are over. Systems are now real-time or quasi-real-time and learn independently.
Second challenge: data security
The second challenge will be to secure these data, whether personal or industrial, belonging to Governments, local authorities or public institutions. Legal frameworks are gradually being reinforced for this purpose.
The 21st century will be the century of digital trust
Faced with this two-fold challenge, there is only one possible answer: to build lasting digital trust, together. First of all trust in our technological ability to exploit millions and then billions of billions of data per second, something that the Bull Sequana supercomputer is already doing. Then, trust by the citizens in the management of personal data, including that generated by the internet of things, with cybersecurity lying at the heart of our commitments and our operational excellence.
More broadly, together with CEA, we are planning for the future: that of the quantum computer, on which our engineers are already working closely with those at CEA, and “quantum-safe” cryptography. By 2030, new inventions will be appearing in all sectors, creating jobs and sustainable growth, far from the long-term stagnation that is feared by some. The 21st century will thus be the century of real-time data exploitation and the construction of digital trust, which are the two sides of the same coin.