Lex Fridman interviews Dmitry Korkin on the latest episode of his podcast.

Dmitry Korkin is a professor of bioinformatics and computational biology at Worcester Polytechnic Institute, where he specializes in bioinformatics of complex disease, computational genomics, systems biology, and biomedical data analytics. I came across Dmitry’s work when in February his group used the viral genome of the COVID-19 to reconstruct the 3D structure of its major viral proteins and their interactions with human proteins, in effect creating a structural genomics map of the coronavirus and making this data open and available to researchers everywhere. We talked about the biology of COVID-19, SARS, and viruses in general, and how computational methods can help us understand their structure and function in order to develop antiviral drugs and vaccines. This conversation is part of the Artificial Intelligence podcast. 

Time Index:

  • 0:00 – Introduction
  • 2:33 – Viruses are terrifying and fascinating
  • 6:02 – How hard is it to engineer a virus?
  • 10:48 – What makes a virus contagious?
  • 29:52 – Figuring out the function of a protein
  • 53:27 – Functional regions of viral proteins
  • 1:19:09 – Biology of a coronavirus treatment
  • 1:34:46 – Is a virus alive?
  • 1:37:05 – Epidemiological modeling
  • 1:55:27 – Russia
  • 2:02:31 – Science bobbleheads
  • 2:06:31 – Meaning of life

Very often I am asked when (or whether) we will create a conscious AI.

I scratch my chin and ask “how would you define consciousness?”

The answer usually involves something about “self-awareness.”

I then point out that by that definition, your car is conscious as it has a “check engine light,” which is part of a self-diagnostic loop.

Usually, I point out that consciousness is a subjective phenomenon – it’s “I think, therefore I am” and not “You think, therefore you are.”

I am fascinated with noted physicist Michio Kaku’s explanation on why feedback loops create consciousness.

Dr. Michio Kaku is the co-founder of string field theory, and is one of the most widely recognized scientists in the world today. He has written 4 New York Times Best Sellers, is the science correspondent for CBS This Morning and has hosted numerous science specials for BBC-TV, the Discovery/Science Channel. His radio show broadcasts to 100 radio stations every week. Dr. Kaku holds the Henry Semat Chair and Professorship in theoretical physics at the City College of New York (CUNY), where he has taught for over 25 years. He has also been a visiting professor at the Institute for Advanced Study at Princeton, as well as New York University (NYU).

TED-Ed explains the science of how viruses can jump from one species to another and the deadly epidemics that can result from these pathogens.

Here’s a story that happened right here in Maryland.

At a Maryland country fair in 2017, farmers reported feverish hogs with inflamed eyes and running snouts. While farmers worried about the pigs, the department of health was concerned about a group of sick fairgoers. Soon, 40 of these attendees would be diagnosed with swine flu. How can pathogens from one species infect another, and what makes this jump so dangerous? Ben Longdon explains.

Siraj Raval has a video exploring a paper about genomics and creating reliable machine learning systems.

Deep learning classifiers make the ladies (and gentlemen) swoon, but they often classify novel data that’s not in the training set incorrectly with high confidence. This has serious real world consequences! In Medicine, this could mean misdiagnosing a patient. In autonomous vehicles, this could mean ignoring a stop sign. Machines are increasingly tasked with making life or death decisions like that, so it’s important that we figure out how to correct this problem! I found a new, relatively obscure yet extremely fascinating paper out of Google Research that tackles this problem head on. In this episode, I’ll explain the work of these researchers, we’ll write some code, do some math, do some visualizations, and by the end I’ll freestyle rap about AI and genomics. I had a lot of fun making this, so I hope you enjoy it!

Likelihood Ratios for Out-of-Distribution Detection paper: https://arxiv.org/pdf/1906.02845.pdf 

The researcher’s code: https://github.com/google-research/google-research/tree/master/genomics_ood

Big Think has a fascinating interview with Dr. Michio Kaku.

Dr. Michio Kaku is the co-founder of string field theory, and is one of the most widely recognized scientists in the world today. He has written 4 New York Times Best Sellers, is the science correspondent for CBS This Morning and has hosted numerous science specials for BBC-TV, the Discovery/Science Channel. His radio show broadcasts to 100 radio stations every week. Dr. Kaku holds the Henry Semat Chair and Professorship in theoretical physics at the City College of New York (CUNY), where he has taught for over 25 years. He has also been a visiting professor at the Institute for Advanced Study at Princeton, as well as New York University (NYU). He is the author of “The Future of Humanity: Terraforming Mars, Interstellar Travel, Immortality, and Our Destiny Beyond Earth” (https://amzn.to/2lQyjy4)