The BBVA Foundation Frontiers of Knowledge Award in Information and Communication Technologies has been awarded in its 17th edition to scientists Anil K Jain and Michael Jordan for their “fundamental contributions” to machine learning, which have achieved “high-impact applications for society as a whole,” according to the jury minutes. The work of the winners has been key to ensuring that computers are capable of recognizing patterns and making predictions and, in this way, have been able to advance both artificial intelligence (AI) and biometrics.
Jain’s research has focused on pattern recognition, achieving key results so that people can be recognized through the reading of their fingerprints or face. Technology that today is incorporated by the vast majority of smartphones on the market as a security tool, and that has become, in many cases, essential for crime investigation.
Of Indian origin and current professor and researcher at Michigan State University (USA), Jain helped in the 1990s to develop a machine capable of detecting a match between two fingerprints 100 times faster than was possible. until then. Furthermore, at the beginning of the century, the scientist was a pioneer in demonstrating to what extent it is possible for the fingerprints of two people to be the same. Although it was believed to be completely impossible, the winner demonstrated that the small distortion introduced in the print when pressing the fingertip on a surface means that there is a small probability that the prints of different people will be mistakenly identified as the same one. .
On the other hand, the winner also demonstrated the stability of fingerprints over time, confirming for the first time the popular belief with solid data.
«This is a well-deserved award, because clearly Anil Jain is the father of fingerprint recognition, one of the fathers of iris recognition and, within facial recognition, he has proposed and provided solutions to border problems motivated by changes in lighting, appearance or aging,” says Professor Javier Ortega García, professor of Signal Theory and Communications and director of the School of Digital Transformation at the Autonomous University of Madrid, who has collaborated with the award-winner over several research stays carried out in his laboratory.
In parallel, and independently, Jordan’s work in the field of machine learning “provided unified algorithms for statistical and probabilistic inference, thus allowing computers to make accurate predictions from observed data,” highlights the jury. Their contributions have laid the mathematical foundations of generative artificial intelligence models, such as those used by ChatGPT, and the development of recommendation systems, such as the one applied by Amazon, for making economic decisions for both consumers and companies.
For his part, the American Michael I. Jordan, who currently works at the University of California Berkeley, has developed mathematical and computational techniques that are behind a multitude of applications of artificial intelligence. During the 1990s he was one of the pioneers in the development of the so-called variational inference methods, in which the solution to a mathematical problem that is not feasible to solve with the available computational resources is approximated, reducing it to an optimization problem. This technique is a core component of machine learning, and especially deep learning applications like ChatGPT’s generative AI.
In the 2000s, Jordan considered how to multiply the possibilities of machine learning, running the programs on hundreds or thousands of computers instead of just one. The algorithms he developed to enable the distribution of this type of computation led to the creation of the company Anyscale, whose Ray platform powers ChatGPT, numerous e-commerce companies, and many more applications of deep learning. More recently, the award winner has focused on studying the applications of machine learning to economics.
The BBVA Foundation Frontiers of Knowledge Awards, endowed with 400,000 euros in each of its eight categoriesrecognize and encourage contributions of singular impact in science, technology, the humanities and music, especially those that significantly expand the scope of what is known in a discipline, make new fields emerge or build bridges between various disciplinary areas.
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