The avenues of artificial intelligence and machine learning research are expanding rapidly and widely. Meta says it plans to fine-tune its AI discoveries by analyze the structure and networks of the human brain, which hopes to better map deep learning algorithms by modeling them on the neural activities of real human cells. Meanwhile, at Google, one of Google’s top engineers said he’s convinced a chatbot he’s been working with gained human-like interest.
What does it all mean? And what could it mean for AI applications in healthcare?
We recently spoke with Chirag Shah, an associate professor in the School of Information at the University of Washington. With expertise including interactive and referral systems, Shah – read recent HITN articles on Google’s LaMDA – talked about recent advances in computational models and research techniques, and discussed some of the challenges, opportunities, and risks as AI thrives in the healthcare sector. health care.
Shah’s work at UW and his specific areas of research
Where healthcare is now with AI & ML – and where it’s headed
Where do you expect us to be in 5 or 10 years?
How is AI and similar to – and different from – the human brain
Ethical concerns facing healthcare AI implementations, now and in the future
Enableable Advanced AI & ML Opportunities
More info about this episode:
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Metaverse and virtual reality are firmly established in the field of healthcare
New York State Office on Aging deploys AI robots as companions for older adults
Research: AI deep learning model can predict race from image results
AI-powered app evaluates MRI data to help analyze dementia
Google and DeepMind face legal claim over unauthorized use of NHS medical records
Nuance, Institute of Health Management launches artificial intelligence collaboration
Research says spotting bias in AI requires a holistic approach
What future for AI in healthcare?