We will not be discussing edge computations, confidential data operators, scattered mobile searches, or similar fascinating yet not the most consciously and wide-applied (not at this moment) scenarios. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).ĭistributed AI scenarios “for the masses” Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). You can now access the application via [ What is Distributed Artificial Intelligence (DAI)?Īttempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. **Always make sure you are inside the main directory to execute docker-compose commands.** #Anonymizer universal slow code#Recommended in case you want to play with the source code and twiki it to your taste.Ĭlone the repository to your desired directory Recommended in case you just want to get the application up and running.ĭocker run -name anonymizer -publish 9091:1972 -publish 9092:52773 rlourenc/iris-csv-anonymizer:1.0 **Make sure you have Docker up and running before starting.** The application recognizes the header columns and allows the user to chose which ones to ignore. Sample CSV where Date of Birth and Sex will remain untouched, while the rest should be anonymized. Tiny web application that allows you to anonymize CSV files.
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