Iris.ai, the provider of a generative AI engine for scientific text understanding, announced it has been selected by the European Innovation Council (EIC) to receive grants and funding in a highly competitive selection process.
The Oslo, Norway-based company will receive €2.4 million ($2.6 million) of grant funding and up to €12 million ($13 million) in equity investments from the 2022 EIC Fund. Of the 1,000 qualified candidates, Iris.ai is among 78 companies chosen for funding.
Iris.ai’s AI engine addresses the problem researchers face regarding the sometimes overwhelming volume of published research: “Finding relevant research is like finding a needle in a haystack, and as a result, researchers in both academia and industry are missing relevant published papers that could advance their knowledge or are simply wasting time reading irrelevant research,” the company said in a statement.
The Iris.ai platform uses large language models specifically trained to categorize, navigate, summarize, and systemize data from academic papers, patents, and other technical or research documentation. According to the company, it is currently in use at hundreds of universities and companies, including ArcelorMittal, a multinational, Fortune 500 steel manufacturer based in Luxembourg.
The EIC is a flagship European program to identify, develop, and scale up breakthrough technologies, and has a budget of €470 million ($510 million) to fund this promising tech to support European growth.
The EIC jury decided that Iris.ai’s technology has the potential to enable breakthroughs in European research through interdisciplinary scientific discovery, commenting that Iris.ai is “a strong AI/ML European player…of utmost importance for the EU, given the evident progress in US and Chinese-driven AI developments and the potential biases that could therefore be implemented in the algorithms.”
Iris.ai says it will use the investment for its core mission of making scientific research more actionable, and that the funding will assist the company in accelerating interdisciplinary research across every field.
There is currently much hype surrounding generative AI such as Open AI’s DALL-E 2 and ChatGPT, but these larger and more general applications have a long way to go as far as accuracy is concerned. Iris.ai says its platform differs from these by providing a niche application that relies on much more specialized training, resulting in more reliable outputs.
The Iris.ai platform categorizes, navigates, and summarizes data from academic papers, patents, and other research documentation. (Source: Iris.ai)
Anita Schjøll Abildgaard, CEO and co-founder of Iris.ai, commented, “When Iris.ai was founded in 2015, few people had heard of language models. Since then, the AI ecosystem has grown exponentially, and the concept of language models is common knowledge,” she said. “However, the current generation of large language models–including ChatGPT–don’t work for science today. They hallucinate, generate mistruths, and misunderstand scientific text due to a lack of domain-specific knowledge. What we’re doing differently is we are working on factuality validation, and injection of externally validated knowledge – creating a trustworthy system that can be relied upon for analyzing scientific research. Our research efforts are considerable, compared to other startups in our field.”
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