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218 search results for: algorithm

21

5G connecting constellations

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A space-based solution to connect remote regions is soon to become reality. But using low-orbiting satellites as telecommunications relay stations means certain functionalities of current terrestrial solutions have to be reinvented. Their constant movement is the reason. For the BPI 5G NTN mmWave project, Télécom Paris scientists are tackling this technical challenge, by developing new algorithms and performance models in order to assess the limitations of the system and then optimize it.

22

The Cybaile Chair, securing AI tools for healthcare

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Thanks to AI tools, it is now possible to identify signs of disease in medical images in a robust and secure way. However, developing such tools requires access to large volumes of sensitive health data. How can we protect this data, and the tools that use it? These are the questions that Cybaile, the industrial chair in cybersecurity, AI and trust in healthcare, is trying to answer.

23

The AI Act makes an entrance

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The AI Act was adopted on June 13, 2024 with the aim of regulating artificial intelligence within the EU. The Act classifies AI systems by their level of risk, and imposes strict restrictions on technologies that pose significant threats to security and individual liberties. How does this differ in comparison to existing frameworks and how will it be implemented? An analysis from Winston Maxwell and Anne-Sophie Taillandier, two AI experts.

24

Elsa Dupraz, 2024 IMT-Academy of Science Young Scientist Prize

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Channel coding is the focus of Elsa Dupraz’s research, a key process for improving information transmission in telecommunications. While the technique’s effectiveness in this field is well known, the researcher is also exploring novel applications, such as data compression and DNA storage. Her research, at the intersection between several disciplines, has fostered multiple collaborations and earned her the 2024 IMT-Academy of Science Young Scientist Prize.

25

What are neural networks?

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Neural networks are AI models designed by machine learning. They are inspired by the workings of the human brain and allow machines to carry out different tasks autonomously. Using large quantities of data as examples, they can be trained in image recognition or text analysis. Beyond their predictive performance, a number of scientific challenges still need to be resolved, concerning the understanding of their limits, reliability of their use, and their acceptability, in addition to ethical issues such as energy consumption. Stephan Clémençon, a researcher in artificial intelligence at Télécom Paris, explains more.

26

Protecting sensitive sites: AI in radar systems

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Radar systems are safe and durable, and used for both detection and surveillance. However, they deliver signals, not images, which can be difficult to interpret. Using artificial intelligence to complement current algorithms offers a technological solution to this problem. The RadaR-IO laboratory, shared by IMT Mines Albi and the company EPSI, is looking to develop and industrialize this solution.

27

High-level video surveillance for the Paris 2024 Olympic and Paralympic Games

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Security methods for the Paris 2024 Olympic and Paralympic Games are relying on artificial intelligence, specifically algorithmic video surveillance. However, this technology poses a number of issues, particularly in terms of personal data protection. Claudine Guerrier, legal researcher at Institut Mines-Télécom Business School, tells us more about video surveillance using artificial intelligence.

28

Behind the prompts: the unsuspected risks of generative AI

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The EU recently adopted the AI Act, which establishes a legal framework for the safe and ethical use of AI. But what about generative AI? At Institut Mines-Télécom Business School, a researcher and her PhD student are studying the risks associated with generative AI, particularly ChatGPT, based on real-life incidents. Their work highlights major ethical issues and shows the emergence of multifaceted risks associated with the new uses of this revolutionary technology.

29

Do we still need structured information? (The answer is yes)

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Large language models (LLM) are revolutionizing the relevance of natural language comprehension and text responses. Combining them with structured data for standardized organization only improves their accuracy. It is against this backdrop that Telecom Paris researcher Fabian Suchanek and his team are continuing to develop the YAGO knowledge base.

30

The cruel dilemma of health data in the ai era: privacy or equity?

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Federated learning is a way to collaboratively train artificial intelligence models. It thus represents a possible solution to AI biases, often caused by training said models on samples that lack diversity. In the healthcare sector, these biases can lead to problems of equity between patients. The EQUIHid project explores how federated learning can help develop more equitable healthcare services.