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Category: Machine Learning

ToA Episode 43: Deep Reinforcement Learning
Critical Rationalism

ToA Episode 43: Deep Reinforcement Learning

Posted on April 22, 2022April 22, 2022 by Bruce Nielson

In this video upload available on Spotify (we’ll try this once and see how it’s received), we revisit Reinforcement Learning (from way back in episode…

Why Induction *Can* be the Basis for Conjecture (Sort of) – Part 2
Critical Rationalism

Why Induction *Can* be the Basis for Conjecture (Sort of) – Part 2

Posted on November 11, 2021January 3, 2022 by Bruce Nielson

I previously posted about Deutsch’s argument to Eli Tyre about why induction can’t be the basis for conjecture. And I agreed with that argument. But,…

Theory of Anything Podcast 34: Alpha Go and Creativity
Computation

Theory of Anything Podcast 34: Alpha Go and Creativity

Posted on November 2, 2021November 1, 2021 by Bruce Nielson

In this episode, we review Alpha Go: The Movie. This is an amazing documentary worth watching before we spoil it for you in this review.…

Theory of Anything Podcast 28: Reinforcement Learning and Q-Learning
Machine Learning

Theory of Anything Podcast 28: Reinforcement Learning and Q-Learning

Posted on August 10, 2021August 9, 2021 by Bruce Nielson

Reinforcement Learning is a machine learning algorithm that is a ‘general purpose learner’ (with certain important caveats). It generated a lot of excitement with its…

Reinforcement Learning with Augmented Data
Machine Learning

Reinforcement Learning with Augmented Data

Posted on January 25, 2021January 7, 2021 by Bruce Nielson

“Reinforcement Learning with Augmented Data,” (link) by Michael Laskin, et al introduces the idea of using data augmentation in Reinforcement Learning. Data augmentation is already…

Georgia Tech’s Deep Learning Course
Artificial Intelligence

Georgia Tech’s Deep Learning Course

Posted on January 13, 2021January 13, 2021 by Bruce Nielson

I was already signed up for Computer Vision when word came that there would be a new Deep Learning class next semester. I quickly got…

Trump and Truth: Induction vs Critical Rationalism
Critical Rationalism

Trump and Truth: Induction vs Critical Rationalism

Posted on January 4, 2021January 4, 2021 by Bruce Nielson

Despite appearances, this post isn’t intended as a political post. I simply utilized the example that led to the thought that inspired the post. We…

Critical Rationalism

Blind Variation as Heuristics that May Fail?

Posted on December 23, 2020December 29, 2020 by Ella Hoeppner

Bruce and I have an ongoing discussion about our differing interpretation of Donald Campbell’s notion of “blindness”. Bruce has previously published a post explaining his…

Do Humans Have “Machine Learning Biases”?
Artifical General Intelligence

Do Humans Have “Machine Learning Biases”?

Posted on November 30, 2020January 7, 2021 by Bruce Nielson

“ImageNet-Trained CNNs are Biased Towards Texture; Increasing Shape Bias Improves Accuracy and Robustness” (link) by Robert Geirhos, et al explores two proposed theories about how…

A Review of GPT-3
Machine Learning

A Review of GPT-3

Posted on November 23, 2020November 16, 2020 by Bruce Nielson

“Language Models are Few-Shot Learners” by Brown, et al (link) was the world’s introduction to Open AI’s GPT-3, the state of the art language model…

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Exploring the theories and implications of David Deutsch’s “Four Strands” which are our four deepest scientific theories that, when taken together, are a theory of everything including philosphy, morality, and beauty.

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  • ToA Episode 43: Deep Reinforcement Learning
  • ToA Episode 42: Popper without Refutation & Resolving the Problems of Refutation (part 2)
  • Popper Without “Refutation”
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  • How to Make Popper’s Epistemology More Clear

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