• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Tag "artificial intelligence"

Artificial Intelligence as a Driver of Digital Transformation

Artificial Intelligence as a Driver of Digital Transformation
In December, the HSE Institute for Statistical Studies and Economics of Knowledge and the HSE AI Research Centre participated in UNCTAD eWeek to discuss the future of the emerging digital economy. One of the topics discussed during the conference was artificial intelligence and its applications in driving the digital transformation of industry sectors. The session was co-organised by HSE University.

‘AI Is a Tool, and Those Who Master It Will Have a Competitive Advantage’

‘AI Is a Tool, and Those Who Master It Will Have a Competitive Advantage’
HSE University is hosting the FIT-M 2022 International Scientific Forum. As part of this event, the HSE Cultural Centre held a series of lectures on November 29­–30. On December 7–9, guests of the forum will have three days of practical work with scientists, IT industry leaders, businesspeople, and industry experts.

Scientists Doubt that DeepMind’s AI Is as Good for Fractional-Charge Systems as it Seems

Scientists Doubt that DeepMind’s AI Is as Good for Fractional-Charge Systems as it Seems
In their paper published in Science in 2021, a DeepMind team showed how neural networks can be used to describe electron interactions in chemical systems more accurately than existing methods. A team of researchers from Skoltech, the Zelinsky Institute of Organic Chemistry, HSE University, Yandex, and Kyungpook National University show in their comment in Science that DeepMind AI’s ability to generalise the behaviour of such systems does not follow from the published results and requires revisiting, the Skoltech website says.

AI Helps Discover New Space Anomalies

AI Helps Discover New Space Anomalies
The SNAD team, an international network of researchers including Matvey Kornilov, Associate Professor of the HSE University Faculty of Physics, has discovered 11 previously undetected space anomalies, seven of which are supernova candidates. The researchers analysed digital images of the Northern sky taken in 2018 using a k-D tree to detect anomalies through the ‘nearest neighbour’ method. Machine learning algorithms helped automate the search. The paper is published in New Astronomy.