I’m on my way home from Euroscipy and it was a blast. But that won’t stop us from awesome machine learning, right? Let’s dive right in!
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I attended my first in-person conference since the beforetimes.
Lots of mixed feelings before, including anxiety about my own talk. But it was lovely to see the people that were there. There was a really unfortunate mix-up with my time-slot, so my tutorial ended up being a talk on Thursday.
I talked about “Increase citations, ease reviews & collaboration – make machine learning in science reproducible”. In this talk I went over actual examples with notebooks how to make sure results are valid and collaboration is easy (including testing, sharing, and even ablation studies).
Pretty lofty goal, so I’m glad I made it and I hope many people find use in it.
I forgot my phone charger at home. So that means I have been relying on my fantastic power bank that I keep for these backup situations. 20,000 mAh is plenty for a few charges and while it’s pretty much drained now, it really helped to have a bit of extra juice.
I didn’t publish a lot this week, but I did present my tutorial and the material is available online. You can check out the notebooks and slides here:
I also updated my talks repo a bit.
Where is the global AI talent?
In the visualization below you can see where students come from and move to at graduation. The global AI tracker has some very insightful visualizations where current AI research is conducted nation-wise but also the split between academia and industry.