I drank the whole data lake? Don't normally post untappd checkins because boooring 🙄 but this one is just so extremely on brand https://t.co/x6XpPbowkw
GitHub Copilot is already helping developers code faster in their IDEs. But what’s next?
Our answer is GitHub Copilot X. It’s our vision for the future of AI-powered software development. Check it out ⬇️ https://t.co/3Xrn7dAPgi
I was thinking about this more and have written down some first thoughts on a solution to the structural problem of data scientists not having the right tools in play: https://t.co/ebQOzGkOWO
🔥Here it is! 🔥
After 100’s of hours of research and writing, excited to release the 2023 ***MAD*** Landscape (Machine Learning, Artificial Intelligence and Data)
A year full of drama in the ecosystem
👇👇👇
https://t.co/HQ84qIn6Tu
Uh oh, that's all my strategies apart from 'prioritisation by who will complain the quickest/most annoying-ly', which I'm guessing isn't the one either...
Bad defaults for prioritization:
* prioritization by inertia: what are you already doing
* prioritization by decibels: what's noisily claiming it's urgent
* prioritization by guilt: what did you promise you'll do
@harterrt at #StaffPlusNewYork
(Oooof now I'm introspecting.)
@51M0NW Definitely something we are grappling with at the moment. And user expectations seem to be that it is a simple thing to do, but it is really not!
We think this problem will be seen wherever users come back to #OpenData regularly to find changes. The paper talks about limitations of common solutions (e.g. the “just use git” crowd) and suggests some alternatives.
It’s open-access so give it a read! https://t.co/sIMARCEHdh