
What we’re about
Philosophy Café in Rochester, NY is a group that reads philosophy texts and meets to discuss them.
All are welcome! Our meetings are open to “beginners” and “experts,” alike. No prior experience with philosophy is required or expected. If you have an interest in philosophy, we’d love for you to join us!
We meet on the second Saturday of each month at 11:15 a.m., unless indicated otherwise.
A typical meeting starts with a short, general introduction of the topic and the readings, and then we break into small groups (3-5 people) to discuss. At some point, we re-mix the small groups so we each get to talk with and hear from different people. And at the end, we sometimes bring everyone back together as a big group to share observations that came out of the small group discussions.
More info: [PhilosophyCafe.net](https://philosophycafe.net)
Upcoming events
2

David Chalmers: The Hard Problem of Consciousness
Equal Grounds, 750 South Ave, Rochester, NY, USHi Folks,
Please join us for a group discussion on David Chalmers’ influential 1995 paper Facing Up to the Problem of Consciousness.
📖 About the Text
Originally published in the Journal of Consciousness Studies, this paper introduces the famous “hard problem” of consciousness. Chalmers argues that while science can explain functions like attention and behavior, it struggles to account for the felt quality of experience (qualia). He suggests consciousness may require a nonreductive explanation, perhaps treating experience as fundamental.
📚 Reading & Participation
We will break out into two groups, one group for those who have read the full paper as found here:
https://consc.net/papers/facing.pdf
A second group who haven't read the full paper, but will discuss the ideas as summarized with AI here:
https://drive.proton.me/urls/6CBE6DJHM4#OL0wkA4B2LjO
💬 Discussion Format
- We will separate into the two groups, one who read the full paper vs one who read the AI summary version
- We will further break down to groups of 4 if needed
- We will discuss a theme as presented in the AI summary document for around 30 minutes in our groups
- We will rotate groups if we have enough people and time for rotations
Bring your curiosity, openness, and willingness to grapple with one of philosophy’s deepest puzzles.
📍 Location
Please RSVP to get the location. I've set the RSVP limit to 20 but it will be essentially first come first served depending on how many seats we can find together, so arrive on time to help you get a seat. If you cannot make it please update your RSVP to no to open up space for other people.
🌐 Event Details
All are welcome. No prior background in philosophy required. Please RSVP in order to attend as this allows us to manage numbers and lets other attendees know who to expect to see.
🪶 Questions or Feedback?
If you have questions or feedback, feel free to reach out to me on Meetup.
Kind Regards,
Ryan14 attendees
Hierarchical Predictive Processing: How Daydreaming Reality Saves Energy
Dept. of Physics (UR), 284 Hutchison Rd, Rochester, NY, USYour brain's sensory systems take in roughly 11 million bits of information per second, but conscious awareness handles only about 50. What happens to the rest? It turns out your brain isn't passively recording reality—it's actively hallucinating it, using predictions to fill in what it expects to see, hear, and feel. The sensory data serves mostly as error correction.
This is the core insight of Hierarchical Predictive Processing (HPP), a framework emerging from the work of Andy Clark, Karl Friston, Anil Seth, and others that reconceptualizes the brain not as a passive perceiver but as a prediction machine continuously generating hypotheses about the world and updating only when those hypotheses fail.
The implications are striking: consciousness may be a "controlled hallucination" where your brain's best guess about reality becomes your subjective experience. But this isn't a flaw—it's an engineering solution to an impossible problem. No finite system can process practically infinite information. Prediction compresses the computational load, but it comes at a cost: the brain must choose what to predict, what to ignore, and when prediction errors matter enough to update the model.
While standalone, this meetup adds to our previous discussions on Kahneman's dual-process theory, and emergent complexity. Where Kahneman described what the brain does (fast intuition vs. slow analysis), predictive processing explains why and how—and reveals that the separation may be less clean than System 1/System 2 suggests. The (relatively) simple rules of coordination between neurons form the basis for emergent complexity and sparse computation which leads to consciousness with a mere 20 watts. This does have its drawbacks, as made explicit by the No Free Lunch theorems.
Join us to explore how the brain constructs reality, why perception sometimes fails spectacularly, and what happens when the prediction machinery operates under different conditions.
Necessary viewing to attend this meetup: Why Your Brain Blinds You For 2 Hours Every Day — Kurzgesagt (12 min)
Deeper videos / text (optional):
- Recommended TED Talk: Your Brain Hallucinates Your Conscious Reality — Anil Seth (17 min)
- How Your Brain Alters Your Reality (W/ Anil Seth) | TED
- It's Bayes All The Way Up — Scott Alexander (Slate Star Codex blog, 2016)
- The Experience Machine: How Our Minds Predict and Shape Reality by Andy Clark (2023 Pop Sci)
Technical references:
- Whatever next? Predictive brains, situated agents, and the future of cognitive science | Behavioral and Brain Sciences | Cambridge Core, Andy Clark (2013)
- Thermodynamics of Prediction | Phys. Rev. Lett. Still et. al (2012)
- No free lunch theorems for optimization | IEEE Journals & Magazine Wolpert & Macready (1997)
- Surfing Uncertainty by Andy Clark (2016 textbook)
- The Predictive Mind — Jakob Hohwy (2013 textbook)
Format: After an intro summary by the hosts, we will breakup into rotating groups and discuss with the aid of a handout (https://bit.ly/4shZmiE). We will regroup for the conclusions.
4 attendees
Past events
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