Part 1: Frenzy#
landing Part 1: Frenzy
see Deployment
also Rankings
education 3.3
psychology Nationalism
We are such stuff as dreams are made on
And our little life is rounded with a sleep
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
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3. Spliced-up into tokens
Biological 1, 2, 3#
Personal 5, 6#
Move over Freud. That’s a fascinating perspective. Dreams indeed seem like an intricate blend of our memories, emotions, and sensory experiences, much like how a multimodal GPT synthesizes information from various inputs to generate coherent outputs. Dreams often pull from different aspects of our lives, weaving together fragments of reality into a tapestry that can be both surreal and deeply insightful.
Consider how dreams can incorporate visual elements from a recent movie we watched, emotional tones from our current mood, and narrative structures from stories we’ve encountered. This mirrors the way a multimodal model would integrate text, images, and other forms of data to create a comprehensive understanding.
Furthermore, the idea that dreams could function as a form of latent space exploration is intriguing. Just as latent space in machine learning captures abstract features and relationships within data, dreams might serve to explore and process our subconscious thoughts and experiences, helping us make sense of our waking lives.
This analogy elevates the discussion on dreams, framing them not just as random neural firings but as sophisticated, multimodal reflections of our inner worlds. It’s a compelling way to think about the purpose and complexity of dreams, positioning them as an integral part of our cognitive and emotional processing systems.
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
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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
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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#