Automating Automation – How Close are We to Artificial Intelligence Impact?
Tarselli, Mike, Potier, Yohann and Fletcher, Allan (2019) Automating Automation – How Close are We to Artificial Intelligence Impact? Drug Discovery World - https://www.ddw-online.com/.
Abstract
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, miniaturized 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. Our piece will briefly outline each area and offer opinions about how close we are to having artificial intelligence (AI), deep learning (DL) or machine learning (ML) influence each scientific domain.
Item Type: | Article |
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Date Deposited: | 16 Aug 2019 00:45 |
Last Modified: | 16 Aug 2019 00:45 |
URI: | https://oak.novartis.com/id/eprint/40439 |