Why should doctors and health care practitioners learn about artificial intelligence? This is one of the main topics we dive into in this episode of the Smarter Not Harder podcast with guest, Karl Friston. 

Karl John Friston FRS FMedSci FRSB is one of the greatest scientists in history whose work has been cited over 245,000 times.

He is a British neuroscientist and theoretician at University College London. He is an authority on brain imaging and theoretical neuroscience, especially the use of physics-inspired statistical methods to model neuroimaging data and other random dynamical systems.

Karl gives us one cent solutions for the following $64,000 dollar questions: 

1. What does "I am therefore I think" mean in the context of the free energy principle? And, what do psychedelics have to do with it?

2. How does one go about inventing in tools to investigate this connection hypothesis of schizophrenia?

3. Why should doctors and health care practitioners learn about artificial intelligence? 

If you want to the answers to these questions, hold on tight, we're about to go on an extremely deep dive into these topics!

What we discuss: 

0:00:43- About Dr. Karl Friston

00:7:22- The disconnection hypothesis of schizophrenia

00:12:07- The challenges of developing tools to investigate the connection hypothesis of schizophrenia

00:24:14 The difficulties of presenting ideas that are ahead of time 

00:32:01 How Dr. Karl Friston got involved in the COVID situation

00:45:16 The free energy principle and coacervate droplets

00:59:13 Is biological life necessary for consciousness or is self evidencing enough? 

01:09:50 The different theories for explaining the nature of things

01:18:18 The uncertainty of beliefs 

01:26:03 What is the REBUS model?

01:33:16 How psychedelics can induce entropy in a controlled way 

01:46:37 The definition of Artificial Intelligence 

01:51:59 What is the embodied cognition?

01:58:06 Is curiosity necessary for the expression of the free energy principle?  

02:14:05 Learning as humans in evolution 

02:27:35 The future of machine learning models 

02:33:00 What imaging tools need to be developed for the future

02:41:31 What’s next for pharmacology

02:51:59 How we should proceed with psychedelic research

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