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SUMMARY:Practices of Prediction: Big Data as Foundation of Modern AI - Ami
 ra Moeding (University of Cambridge)
DTSTART:20250430T081500Z
DTEND:20250430T091500Z
UID:TALK230374@talks.cam.ac.uk
DESCRIPTION:The paper is structured by three guiding questions: First\, wh
 at (if anything) is Big Data? Second\, how has 'Big Data' changed what dat
 a is and how data functions within models? Third how has 'Big Data' impact
 ed conception of 'complex phenomena' and prediction? Around these three gu
 iding questions the paper puts forward a narrative of how Big Data could b
 ecome an approach to what we call 'Artificial Intelligence' today within r
 esearch on language processing and later image recogntion. The presentatio
 n focuses on the industrial contexts in which 'Big Data' could emerge and 
 recovers what actors saw as 'economic imperatives.' Therein\, I aim to mak
 e 'Big Data' speak within the political economy of the technology industry
 . I attempt to analyse the intellectual debates around 'probabilistic\,' '
 rational\,' or 'empirical' and 'statistical' approaches to provide a map o
 f different conceptions of 'empiricism' and 'rationalism' that functioned 
 as epistemological premises within AI research/ ML. The paper ends on a fe
 w considerations of the tech-industry today and how the industry has recon
 figured imaginaries of the future.&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
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