rcurtin_irc changed the topic of #mlpack to: mlpack: a scalable machine learning library (https://www.mlpack.org/) -- channel logs: https://libera.irclog.whitequark.org/mlpack -- NOTE: messages sent here might not be seen by bridged users on matrix, gitter, or slack
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<jonpsy[m]> <rcurtin[m]> "wow, here is some torture I..." <- How was your climbin experiece? Is that somethin you've recently picked up?
<jonpsy[m]> I remember Heiko used to climb too
<zoq[m]> Eshaan Agarwal: any update?
<rcurtin[m]> jonpsy: I've been climbing for a few years but I don't think I'm anywhere near as hardcore as zoq @marcusedel:matrix.org or Heiko... I started climbing because there was a bouldering gym in the basement of the office building I worked in, and I would go climb to blow off steam between meetings 😀
<rcurtin[m]> here's the issue I just opened about the OVH binder connectivity problems: https://github.com/jupyterhub/mybinder.org-deploy/issues/2378
<jjb[m]> ryan what’s up with `bandicoot`? Did Conrad give up on that extension due to `OpenCL` being deprecated?
<rcurtin[m]> I just left my job at RelationalAI and now I have a "sabbatical"; I was hoping to finish up a first release of bandicoot. The general concept is still very important to me: an Armadillo-like GPU matrix library. Maybe we have to switch out OpenCL for a different backend, but its current (prototype) architecture makes it pretty easy to add new backends. In fact, there is a CUDA backend already
<rcurtin[m]> So, I am planning on finishing up the basic functionality that would be necessary to call it "complete" (for some primitive version of 'complete'), and then make a release, demonstrate its usability via some benchmarks, then start plugging it in to various ensmallen and mlpack algorithms, adding more functionality as necessary