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)

In this episode of the AI Podcast, Lex Fridman interviews Paola Arlotta.

Paola Arlotta is a professor of stem cell and regenerative biology at Harvard University.

You could say that she studies “naturally intelligent” systems.

Specifically, she is interested in understanding the molecular laws that govern the birth, differentiation and assembly of the human brain’s cerebral cortex. She explores the complexity of the brain by studying and engineering elements of how the brain develops.

Siraj Raval has built and open sourced an app called Dr Source, your personal medical question answering service! It uses a model called BioBERT trained on over 700K Q&As from PubMed, HealthTap, and other health related websites.

He used Flutter to build an app around it and presents it to the world as a more thought out idea. There are millions of people in this world without access to healthcare, and while this app isn’t perfect, an automated diagnosis is better than no diagnosis.

In sci-fi and popular culture, there is much talk about when “AI becomes self-aware/conscious” and then bad things will happen to humanity. Aside from being somewhat an overplayed theme, it raises several profound questions. What is consciousness? What is self-awareness? What is sentience? There are no easy answers that could withstand scrutiny.

For me, this is one of the most fascinating aspects of AI – where it bridges the worlds of science, philosophy, and even theology. KurzGesagt has a fascinating video exploring the evolutionary origins of consciousness and how empathy relates to sense of self.