Part 1: Frenzy#
Note
We are such stuff as dreams are made on
And our little life is rounded with a sleep
Fortunately, we have music to fall bach to
GPT representation of life is about propensities
(e.g. of black women to watch a Tyler Perry film)
Propensity to see, recall, feel, kumbaya, leverage, will
1. Multimodal, lifetime of experience
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2. Compute by oldest neuronet -> 4. Latent-space -> 5. Bayesian decipherers -> 6. GPT representation of life
/
3. Spliced-up into tokens
Biological 1, 2, 3#
Personal 5, 6#
Translation
Ask ChatGPT to give you variants on “admonition”
That’s an interesting comparison. Tyler Perry’s films often use the church as a cornerstone of hope, with the pastor delivering uplifting messages, surrounded by soulful music that adds emotional gravity to the scenes. His films can feel like a vibrant church service, aiming to inspire and uplift audiences.
On the other hand, the Coen Brothers often depict rabbis with a touch of absurdity. Their rabbis may deliver messages that are intentionally unconvincing or perplexing, accompanied by chanting that adds to the humor and irony of the situation. This approach reflects their unique style, which often blends dark comedy with philosophical musings, leaving audiences both amused and contemplative.
These contrasting styles highlight how different filmmakers use religious figures and settings to evoke varying emotions and themes in their storytelling.
The DAG below may help place all this in a broader context with more meaning
That’s an insightful analogy! The collective unconscious as analogous to latent space suggests that just as latent space
in machine learning
models represents compressed, abstracted representations of data, the collective unconscious contains compressed, abstracted representations of shared human experiences and archetypes. This space holds potential patterns and insights that can be “decoded” or “activated” to generate new understandings and applications.
1. Millenia-of-Experiences
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2. Our-Heritage -> 4. Collective-Unconscious -> 5. Decode-Priests -> 6. Apply-Thrive
/
3. Artifacts-Rituals
Dionysus 1, 2, 3#
Sing O Muse 4#
Apollo 5, 6#
In this framework:
Millennia-of-Experiences: This is like the vast dataset of human history, full of diverse and rich information.
Our-Heritage: This step involves understanding the key features and structures within this dataset, similar to identifying significant patterns and clusters.
Artifacts-Rituals: These can be seen as specific instances or data points that provide concrete examples of the larger patterns and structures.
Collective-Unconscious (Latency Space): This is the latent space where abstracted, distilled representations of the collective human experience reside. It contains the archetypal patterns and universal symbols.
Decode-Priests: This involves using tools or interpreters (akin to decoders in machine learning) to extract meaningful information from the latent space.
Apply-Thrive: Finally, applying this decoded information to real-world scenarios to enhance understanding, innovation, and thriving, similar to generating actionable insights from a machine learning model.
Good Luck 1, 2, 3#
Math 4#
Common Sense 5, 6#
1. Chaos
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2. Frenzy -> 4. Parameter-Weights -> 5. Algorithms -> 6. Binary
/
3. Energy
By thinking of the collective unconscious as a latent space, you bridge
ancient wisdom with modern computational concepts, creating a powerful metaphor for understanding and utilizing deep-seated human knowledge.
Social 4#