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Many thanks to NIH Clinical Center and Dr. Ron Summers for providing the CXR8 (Now CXR14) dataset that enabled the CLiP Challenge for #RANZCRASM21 - tune in to #RANZCRASM21 to hear his talk now on datasets in Radiology.

#RANZCRASM21 AI session 2 moderated by Jarrel Seah coming up shortly with Oliva Reeves from the TGA Australia talking about regulation of software medical devices and @DrLukeOR talking about biases in AI. #ArtificialIntelligence #radiology

Excellent talk from @DrLukeOR in the #RANZCRASM21 AI Session 2 with a great explanation of shortcut learning and hidden stratifcation in AI algorithms. #ArtificialIntelligence

#RANZCRASM21 AI Session 3 with Dr Jarrel Seah (Jarrel Seah) talking about the impact of radiologists' accuracy using the annalise.ai system and #MGHImaging Professor Gonzalez, pomerad and Jen-Tang Lu #DeepSPINE solution

#RANZCRASM21 AI Session 4 will include RANZCR 2021 CLiP Kaggle Challenge with international speakers including Kaggle Challenge winners Bo Liu (Bo) and Hiroshi Yoshihara (Rabotni(kuma|熊)), Maggie Demkin (Maggie Demkin) from Kaggle and A/Prof George Shih from MD.ai

#RANZCRASM21 Join Jennifer Tang live now at AI Session 4 talking about one of the most important steps in AI development - curating and developing datasets!

#RANZCRASM21 Tune in to AI Session 4 to hear Kaggle Grandmaster Bo Liu Bo talk about his incredible first-place winning approach to the inaugural RANZCR CLiP Challenge!

#RANZCRASM21 Now live at AI Session 4 - Kaggle's own Phil Culliton and Maggie Demkin with Jennifer Tang! #Kaggle

#RANZCRASM21 Join us live at AI Session 4 and watch Dr George Shih from MD.ai give his talk on bias and fairness in machine learning, and most importantly, bananas.

We’re launching Harrison.rad.1 – a new AI model to make healthcare more accurate and accessible. Specialised in radiology tasks, Harrison.rad.1 represents a major breakthrough in applying AI to help bridge the global healthcare workforce gap. We’re making Harrison.rad.1

Everyone including Andrej Karpathy is asking which other domains are verifiable and whether reasoning extends beyond those. Computer use seems like a reasonably verifiable task. Is anyone trying end to end RL on computer use?

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