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Benefits and challenges of using automated data annotation solutions

Automated data annotation uses an existing model to generate the annotations you need for your data. Such a model may be trained on generic data such as everyday objects or domain-specific data such as medical data. To get good quality annotations, it is important to select an appropriate model trained on datasets similar to your data. visit https://www.tictag.io/ for more<br>

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Benefits and challenges of using automated data annotation solutions

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  1. Benefits andchallenges ofusingautomated data annotation solutions WHATISIT? Automateddataannotationusesanexistingmodeltogeneratetheannotationsyou need foryourdata.Suchamodel may betrainedongenericdatasuchas everyday objectsordomain-specificdatasuch as medicaldata.Togetgoodquality annotations,itisimportanttoselectanappropriatemodeltrainedondatasetssimilar to yourdata. BENEFITS?

  2. Automatedannotationsystemswerecreated toovercomelimitationsofmanual annotation,mostnotably inannotationworkforcemanagementandannotation speed.Therefore,mostofits benefitscomefromeaseofuseandtheopportunity to foregohumanannotations. Speed Oneofthecommonneeds forArtificial Intelligenceteamsis tobe able to annotatealargeamountofdatainashorttime.Beingable to annotatedataquickly increasesArtificialIntelligencedevelopmentspeedandhelpsinmeetingbusiness deadlines.Unlike manualannotationwhereannotationsneed tobetrainedonthe datadomain,automatedsolutionscanstartgeneratingannotationswithlittleramp uptime.Furthermore,thespeedofannotationitselfisalso expected tobe faster becauseitis poweredby ArtificialIntelligencerather thanmanuallabour. ConsistencyHumanannotatorsmay makemistakesduetofatigueorsimplybe inconsistentintagging. Whenthedatasetislargeandmore annotatorsarerequired toannotatethedata,suchaproblemis expectedtobecompounded.Conversely,an automated dataannotationsolutionisexpectedtogeneratethesameannotation giventhesamedata,makingthedatasetmoreconsistentandusablefortraining yourownArtificialIntelligencemodels. CHALLENGES?

  3. Althoughautomatedsolutionshavebenefits,there arealso certainchallengeswhen usingthem. VariableAnnotationQualitySincealarge partoftheaccuracyofanArtificial Intelligencemodelcomes fromhavingaccuratedatasets,itisimportantthatthe annotationsareofhighquality.Whenusinganexistingmodelto annotateyourdata automatically,thequality oftheannotationsmay differbased onhowpowerful the modelisand howsimilarits trainingdataistoyourdataset.Ifyourdatasetis significantlydifferent,then the quality ofthe annotationmaybereduced. Difficultyof CustomizationWhenchoosingtouseanautomatedsolution,itis important tobeawareofthepotential,orlackthereof, forcustomisingtheexisting model.Iftheautomatedsolutiondoesnot providesufficiently highquality annotations, effort musteitherbespentoncustomisingtheexistingmodelto generatebetterannotationsortheremustbehumaninterventiontocorrectthelow qualityannotations.Ifcustomising themodelisnot anoption,thentheadditional humanlabour costwillbeanongoingconcern. MaintenanceEffort Iftheexistingmodelcanbecustomised foryourneeds,itisimportantto beawareof the maintenancecostofthecustomisation.Inordertogenerateannotationsfornew andpreviously unseendataaccurately,the automatedsolutionmustbeupdatedto meetthenewrequirements.Atsomepoint,youmay evenhaveto decidewhetherit isstillnecessary tohaveseparatemodels fordataannotationandprediction.

  4. CONCLUSION Inconclusion,althoughautomatedsolutionsprovidebenefits,especially forcost- consciousteams, itisimportant tokeepinmindthechallengeswhenusing them. Tictag isabletoachieveaccuracyandconsistencyexceedingthat ofautomated systems,allwhileusingacrowdworkforceto meetyourturnaroundrequirements. Reachoutto ustofind outwecanworkwithyoutomeet yourdataannotation needs. Sourced fromhttps://www.tictag.io/post/benefits-and-challenges-of-using-automated- data-annotation-solutions

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