Oct 29, 2019
In terms of consistency, repeatability, known errors and sheer volume, there exists perhaps no better collection of data for computer learning than that emerging from automated processes.
Many common lab procedures now run in parallel, miniaturised experiments – DNA synthesis, target screening, organoid culture, genetic analysis, organic reactions, safety assays – which are poised for extensive curation and algorithm development over the next 10 years.
This article briefly outlines each area and offers opinions about how close we are to having artificial intelligence (AI), deep learning (DL) or machine learning (ML) influence each scientific domain.
Original article by Dr Michael A. Tarselli, Dr Yohann Potier and Dr Alan E. Fletcher
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