| Popis: |
Two of the greatest pain points in Artificial Intelligence (AI)-assisted research workflows are data quantity and data organisation. Estimates place 60-80% of time in data science workflows is simply cleaning and arranging the data, dependent on researcher skill and the type of data. As AI relies on pattern recognition, the larger the dataset, the more likely the algorithm is to recognise a useful pattern. Due to organised unput via the Studies ELN and the underlying architecture of the database, extracting AI-ready data is made simple. We hold billions of dollars’ worth of data for our clients, and by working with each organisation to show them the untapped potential that existing projects already hold, then future research can be designed with these methodologies in mind to further boost research turnover and outcomes. |
