| UNAM self | @pablo |
| code | https://github.com/psuarezserrato |
| website | https://sites.google.com/im.unam.mx/pablo/home |
| lab | https://github.com/appliedgeometry |
Why are datasets crucial for algorithms?
How do we build AI training datasets?
What can data curation teach us?
What biases lurk in datasets?
Answers in this free, interactive online course by DW Akademie:
A research study on using AI coding assistants has shown that while developers believed they got a 20% productivity gain from using the tools, measurement showed a 19% decrease in productivity.
METR recruited 16 open-source devs to complete 246 real coding tasks, randomly assigning each to “AI Allowed” or “AI Disallowed.”
Devs estimated time saved with AI before & after each task, while screen recording to measured real-world AI productivity gains.
High-resolution blood oxygen level-dependent functional magnetic resonance imaging enables brain-wide mapping of activated regions during sensory stimulation in awake mice, including associated areas, for high-order sensory processing including anticipation responses.
Hey open source contributors,
I’m looking for examples of license agreements from big open source projects.
What are, according to you, the best license agreements? What is an important thing to check before signing a license agreement? What would be your advice to an organization drafting a license agreement to contribute to an #agpl3 project?
Thanks for sharing my question. This is something I will probably add in my open source teaching at university.
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Mandu 🥟