I wonder if advancements in text watermarking will actually help create watermarks for e.g. sensitive or classified governmental/corporate documents. Would allow for instant identification who leaked a certain document if you could trace the watermark back to user accounts.

Does CICERO reflect on its own actions or intentions? Or would you say it has the capacity for self-reflection?

What's it like doing a PhD during these years of incredibly rapid AI development? I would imagine it must be hard keeping up with the pace of change, or even just feeling secure in your work not being obsolete/outdated before it's even published!

I suppose the point is either that the mean size of galaxies is larger than the median size of galaxies, or else that larger galaxies have more planets in them and therefore more odds of any observer being from a larger galaxy.

I don't use python so no need! I just remember being quite confused when I was learning sklearn and realised saving models or pipelines was weirdly complicated compared to R.

More generally speaking I suppose the RDS data format is pretty great to work with within R.

Yes! I knew there was another standard but I couldn't for the life of me remember the name.

Perhaps it's also just a matter of the Python crowd doing a bit more complicated stuff than the R crowd. For me the models tend to be quite straightforward RF or related models (like I said; tidymodels), but the demand is much more on the correct pipeline with pre- and postprocessing. Things become a bit less easy to store once you go into deep neural networks I'd imagine.

It's so strange the python ML community has still not found a suitable model format, despite years and years of effort. What even happened to efforts like PMML?

Meanwhile I'm quite happy with the R infrastructure with storing tidymodels pipelines.