Portugal news – Portuguese tech company Unbabel won the European Commission Large AI Grand Challenge 2024.
Four innovative AI startups in Europe won the European Commission Large AI Grand Challenge in a ceremony held in Brussels. The four AI startups will share a total prize of 1 million euros and an allocation of 8 million GPU hours on two of the world-leading EuroHPC JU supercomputers, LUMI and LEONARDO. The awarded supercomputing time will be essential for developing their large-scale AI models over the next 12 months and will enable them to reduce training times from years to weeks. Following this period, the winners are expected to release their developed models under an open-source license for non-commercial use or publish their research findings.
The competition led by AI-BOOST was developed in collaboration with the European Commission and the EuroHPC Joint Undertaking. As announced by President von der Leyen in January 2024, the Large AI Grand Challenge was the first step in a comprehensive package of measures to support European AI startups and SMEs.
Here are the AI startups that won the European Commission Large AI Grand Challenge 2024:
1 – Lingua Custodia from France
French AI tech startup Lingua Custodia is a fintech company specializing in AI and Natural Language Processing (NLP) for the finance sector, aiming at enhancing the fintech sector operations with solutions designed to achieve speeds five times faster than current systems.
2 – Unbabel from Portugal
Portuguese AI tech startup Unbabel is a language technologies company headquartered in Lisbon, combining AI and human translation for multilingual support, encompassing all 24 official EU languages.
3 – Tilde from Latvia
Latvian AI tech startup Tilde has expertise in language technologies, offering machine translation and AI-powered chatbots, targeting Balto-Slavic languages spoken by 155 million individuals within the EU and candidate countries.
4 – Textgain from Belgium
Belgian AI tech startup enables companies and governments to gain insights from unstructured data through predictive text analytics and focuses on the analysis of hate speech, an area of significant concern that has historically received limited attention.