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Meeting #3

Friday, 2/25/2022

Table of Contents

  1. Agenda
  2. Deliverables
    1. Presentation Guidelines & Objectives
  3. Notes
    1. Discussion
    2. Groups
    3. Journal Club Possibilities

Meeting recording available here.


  1. Housekeeping 5:10-5:20
  2. Agenda
  3. Journal Club Announcement
  4. Social Media
  5. Discord Tutorial - Joining as a Member
  6. Discussion Questions 5:20-5:50
    • Key components of thought
    • How much do you trust your brain?
    • Perception and truth
    • What do trees feel? - Is Siri intelligent?
  7. Card Games - resolving the spoons tournament 5:50-6:00
  8. Presentation Groups and Work Time 6:00-6:30
  9. Ideas for Journal Club 6:30-6:50


Have a presentation ready with your group for next week (Meeting 4)!

Based on the form interest, the following research groups have been created:

Biologically Informed/Plausible NetworksDrew, Chanh
Reinforcement LearningVarun, Aditya, Timothy
Neuromorphic Computing HardwareYegor, Chris
Swarm Intelligence/Robots/Coded AgentsAry, Jason, Chaytan
Meta-Modeling and Self-Aware NetworksSabrina, Marlene, Andre
Neuroscience of Predictive Coding & MemoryJanna, Jay, Alec

Next meeting, each group will give an informal presentation sharing their research. If you want to be involved in another topic, let us know and we’ll add you!

Presentation Guidelines & Objectives

You will research a given topic in small interdisciplinary groups, then give a small presentation on what you learned. The idea is to discover what experts are doing in your topic/field, and where our team may be able to add value through our own project.

Use whatever form of creating slides works best for you - Canva, Google Slides, PowerPoint - your choice.

Touch on the following questions, not necessarily in this order:

  • How does this topic relate to the idea of intelligence
    • Does it have neuroscience ties? Computer science ties? Other related fields in which it is relevant? (These ties are not requirements for the topic, just an open question.)
  • What are some interesting recent papers, projects, or advances in this topic?
  • What are at least 2 project ideas or directions that would build upon the progress of this field?
  • Any libraries/technologies required/could help with implementation?
  • What do we need to know more about to better understand this topic?


  • Discord tutorial - make sure to go to #role-react and click the brain emoji to be given the Member role.
    • Clicking the Member role button unlocks presentation group channels where you can collaborate with your group members.
    • Generally, make sure to stay on top of #announcements channel.
    • All meeting notes, zoom recordings, slides, and more are on the website:
  • Journal Club - scheduled for Monday, 5-6 PM, Sieg Hall 332 (see schedule page for most up-to-date information).
  • Interested in helping us out with social media? Message us!


Should we trust our brain?

  • Shepard’s Tone - the perception of continuously increasing/decreasing pitch.
    • Optical (and audio) illusions as examples that we do not perceive reality or objective truth
  • Do you trust your brain?
  • Success rate of information being given.
  • Whenever possible - try to offload everything from the brain - memory, etc.
  • Complementary relationship between human and machine properties
  • Rely on data and things other than our brain - Hume and induction
    • Is maximum likelihood estimation the best we can do? If we have only ever seen white swans then must we logically assume all swans are white?
  • Preciseness of measurement.
  • Abstract and precise truths. Humans are generally good at abstract truths (e.g. “the United States is a country”); machines are generally good at precise truths (e.g. “it is 23.4837… degrees Celsius”, “12345 + 98374 = 110719”).
  • Metaphorical truth - something that is not necessarily true but is useful.
  • Attaching emotions to events - instinctive judgements.
  • Outliers
    • Is our idea of reality constructed by majority? What if the outlier is ‘correct’? How do we choose whether to include outliers or not? What about the gradient of outlier-ness - i.e. which data points are ‘more typical’ than others?
    • Idea that the more independent observations of the same phenomena occur the more likely to be true?
      • Example of DNA and transcribing proteins being analogous to computing and executing programs, these phenomena independently emerged, so does that evidence an objective reality
      • What about all the people that report seeing elves when they take DMT (independently reporting same hallucinations)? What is their ‘truth’/’experience’?
      • Standpoint epistemology - see Harding, “Rethinking Standpoint Epistemology: What is ‘Strong Objectivity’?”
  • Should we trust AI? Can we trust AI?
  • Court cases - how emotions can bias the truth, skewing events, etc.
  • Voices in your head - who is write? Who knows about what we think?
  • Both cells and CPUs share similar features that have been independently developed.
  • Godel’s incompleteness theorem
    • If math - perhaps the most ‘objective’ system known to humanity - is incomplete, what is objective? Can anything beyond the complete calculation of the universe be objective (and no model capable of ‘pure’ objectivity)?
    • Objectivity is still based in general consensus, math founded on the idea that we can all come to a common representation of what ‘one’ object is / we can all count the same
  • Aristotelian models - we like discrete representations and dislike fuzzy understandings.
  • Legal and symbolic systems - Not a mistake that legal systems have been mentioned as examples for truths (e.g. abstract truths), they are designed to classify the world into good / bad
  • Can we measure brain waves and neural activity during computation of something “objective” like “1+1” - how similar are the computations as a metric for ground truth?
  • Hierarchical model of perception in both neuroscience and neural networks: as information is processed by different modules of the brain, higher order abstraction and meaning emerges.
  • If we can’t perceive something, that doesn’t make it wrong/nonexistent/incorrect.
    • Cats can see wavelengths of light we don’t have perception for
    • How can you compare intelligence when the sensory inputs aren’t even the same
    • Survival as a rough metric for how accurately our perception matches some underlying reality?


  • Everyone has been assigned a group. The group will conduct independent research and present on their research.
    • Goal: understand where the field is, how it relates to AGI, and how we can contribute with possible projects
  • Initial documents and communications are happening in the drive and in the discord.
    • See #announcements for further details

Journal Club Possibilities

I2 - Fusing neuroscience and AI to study intelligent computational systems. Contact us at