https://sander.ai/2023/07/20/perspectives.html Perspectives on diffusionSander DielemanJuly 20, 2023 “Diffusion models appear to come in many shapes and forms…. these various perspectives each reveal new connections and are a breeding ground for
What I Read: shape of AGI
https://windowsontheory.org/2023/07/17/the-shape-of-agi-cartoons-and-back-of-envelope/?1 The shape of AGI: Cartoons and back of envelopeBoaz BarakJuly 17, 2023 “AIs are not “silicon humans.””
What I Read: Disagreement Modelling
https://koaning.io/posts/large-disagreement-models/ Large Disagreement ModellingVincent D. Warmerdam2023-05-26 “So instead of fully relying on a large language model, how might we use it effectively in existing pipelines?”
What I Read: artificial intelligence really hard
https://thegradient.pub/why-transformative-artificial-intelligence-is-really-really-hard-to-achieve/ Why transformative artificial intelligence is really, really hard to achieveArjun Ramani and Zhengdong Wang26.Jun.2023“1. The transformational potential of AI is constrained by its hardest problems
What I Read: When NumPy slow
https://pythonspeed.com/articles/numpy-is-slow/ When NumPy is too slowby Itamar Turner-TrauringLast updated 27 Jun 2023, originally created 27 Jun 2023 “What should you do when your NumPy-based code is too slow?”
What I Read: missing data mechanisms
https://cameronpatrick.com/post/2023/06/untangling-mar-mcar-mnar/ Understanding missing data mechanisms using causal DAGsCameron PatrickJune 28, 2023 “Correctly analysing datasets that have missing data requires extra care and consideration to produce correct results.”