Understanding Consciousness and Agency as Software Agents

Joshua Bach believes that consciousness is a virtual property shaped by self-organizing software agents.

### The Intersection of Consciousness, Agency, and Software in Evolution
* 🧠 Humans possess a remarkable ability to become **self-authoring**, allowing them to **evolve and change their interactions** with the world and themselves.
* 💻 Cognitive scientist Joshua Bach posits that consciousness is a "**virtual property**," suggesting that while we may not physically exist, our activation patterns in the brain create the **illusion of being conscious agents**.
* 🔍 The distinction between reality and virtuality is explored through the lens of software, where something is deemed **real based on its implementation**, similar to how a computer game like Minecraft exists through **electrical patterns rather than physical entities**.
* 📈 Effective modeling is crucial for controlling the future; as one learns to **edit their own source code**, they enhance their ability to **navigate and understand their environment**.
* 🤖 Bach believes that **Artificial General Intelligence (AGI) will emerge within our lifetime**, but its definition remains **complex and must be deeply analyzed** beyond simple task execution.
* 🎲 Agency, or the ability to **predict and control future outcomes**, is contrasted with mere intelligence, emphasizing that true agency involves **setting and achieving goals** rather than just performing tasks.
* 💡 The concept of animism is reinterpreted as a recognition of **self-sustaining software agents in nature**, suggesting that everything from **cells to societies** can be viewed as having **agency and consciousness**, thus **blurring the lines between physical and virtual existence**.
* 🌌 Ultimately, the discussion leads to the understanding that **evolution is driven by the competition of software agents**, highlighting the significance of these **virtual constructs in shaping our reality and consciousness**.

### Understanding Consciousness and Software Agents: A Deep Dive into Mimesis and Coherence
* 🧠 The discussion explores the concept of **mimesis**, suggesting a hierarchy where **language represents the highest form**, followed by evolution and software agents that require **hosts for their existence**.
* 💻 These software agents, described as **self-organizing entities**, are seen as a form of **spirit that organizes cells into bodies**, which produce **complex behaviors and consciousness**.
* 🔍 The speaker emphasizes that consciousness is not merely a product of physical processes but is fundamentally tied to the **software that governs self-organization and perception**.
* 🌌 The notion of consciousness is examined as a **second-order perception**, where it is not just about experiencing content but also about the **awareness of that experience happening in real-time**.
* 🌱 The idea of **coherence** is introduced, suggesting that consciousness acts like a **conductor**, resolving conflicts and promoting **harmony** within the mind and between collective agents, such as families or societies.
* 🌍 The concept of Gaia is discussed, positing that **Earth functions as a collective agent regulating life**, but acknowledging that its coherence is **limited and likely quite complex**.
* 🤖 The conversation touches on the **future of AI**, debating whether current models possess **true agency** or merely simulate it, and how advancements like **liquid neural networks** could redefine machine learning.
* 📈 Ultimately, the speaker argues that **consciousness and agency arise from the need to navigate and exploit energy gradients**, emphasizing the importance of **coherence and shared purposes in collective systems**.

### The Future of AI: Innovation, Regulation, and the Startup Ecosystem
* 🤖 Building Artificial General Intelligence (AGI) could transform the economy, **unlocking immense value**, but startups must ensure **strong business development** to recoup significant investments in model training.
* 💔 The fear of a second dotcom bubble looms, as past experiences show that many companies may **struggle to recover their investments** during transitional periods, despite the eventual success of the internet.
* 🔍 Current trends favor **smaller, edge-deployable systems** over large models, as the latter face challenges in **efficiency and practicality**, emphasizing the need for **innovative epistemological engines** that can process knowledge effectively.
* 📉 The AI field is evolving towards developing **minimal engines** capable of **understanding and generating knowledge** without the weight of **extensive training data**, which could lead to **more modular and useful applications**.
* 💡 The startup ecosystem is witnessing a surge in companies leveraging generative AI, creating **diverse applications with relatively low investment**, while leading models face the risk of **rapid obsolescence due to constant competition**.
* 🏗 Open-source models like those from Mistral foster an ecosystem of innovation, allowing for the **development of new applications**, although the need for **sustainable business models** may drive some to eventually **restrict access**.
* 💬 The conversation around regulation highlights the tension between **innovation and the need for oversight**, as there are legitimate concerns about **copyright and data privacy** in AI training, necessitating **careful consideration of regulatory frameworks**.
* 🌐 Ultimately, the future of AI relies on **balancing innovation with responsible governance**, ensuring that technological advancements **benefit society while safeguarding freedoms and ethical standards**.

Joscha Bach - Why Your Thoughts Aren't Yours.

MLST is the top AI podcast on Spotify. Subscribe now! Welcome! We bring you the latest in advanced AI research, from the best AI experts in the world. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI often going deeper into the underlying philosophy, and we touch on all of the main ideas in the field.

Support us on Patreon for early access, exclusive content, private Discord, monthly calls and much more! 
https://www.patreon.com/mlst 

Donate here: https://www.paypal.com/donate/?hosted_button_id=K2TYRVPBGXVNA

WE ARE LOOKING FOR SPONSORS! 
mlstreettalk at gmail.com


Machine Learning Street Talk

Self-Authoring and the Nature of Consciousness

Humans' ability to become self-authoring, changing their interaction with the world and themselves.

Evolution as a competition between software agents that reproduce and code themselves.

Consciousness as a virtual property; something behaving 'as if' it exists.

Conscious agents observing themselves interacting with the world; physical perspective of non-existence.

The human brain as an activation pattern producing behavior; comparison to Minecraft's implementation on a computer.

AGI Timelines and the Definition of Intelligence

Realness defined by the degree of implementation; different degrees of realness.

Controlling the future through model-making; discovering limitations of observation and models.

AGI's perceived lack of significant change; optimism and hype surrounding current technology.

AGI timelines; differing views on what constitutes AGI.

Comparison of current AI capabilities to Star Trek's 'computer' concept.

Intelligence as superhuman performance across many domains; potential for skill acquisition as a key component.

Limitations of human intelligence tests for non-human applications.

Measuring intelligence by comparing performance before and after learning; focusing on skill acquisition.

AGI as the ability to make any mathematically obtainable model, given available resources and data.

Limitations of Current AI and the Role of Self-Play

Current systems focus on predicting the next token; limitations in tackling complex problems like mathematical proofs.

The need for self-play and feedback mechanisms to surpass human performance; examples in games and mathematics.

Discussion of intelligence as model-building efficiency; the role of agency and self-play.

Agency as a more useful concept than intelligence; focus on deploying intelligence for specific goals.

Agency contrasted with the thermostat; the ability to regulate the future versus the present.

Building systems that regulate the future; incorporating anticipatory modeling and inference.

Model-building as a key component of agency; emergence of agent-like properties from the ability to control the future.

Reinterpreting animism through an information processing lens; the concept of spirits as self-organizing software agents.

Money as an example of a coarse-grained causal pattern with causal power; its existence independent of belief.

Mental states as invariances; the degree to which they are implemented and have causal structures.

Virtual patterns as real with causal powers; clarification of the term 'virtual'.

Different degrees of realness; examples of simulations, simulacra, and observable dynamics.

Discussion of emergence; the relationship between software and hardware.

The lack of surprise regarding emergence in software; comparison to the surprise surrounding mental states.

The confusion around emergence; distinction between weak and strong emergence.

Mental concepts as black boxes; the need for mapping to first principles.

Example of drawing a line on a Commodore 64; the complexity underlying seemingly simple mathematical concepts.

The Bipartite Model of the Mind and Consciousness

Different ways to implement an agent; the role of needs and evolutionary priors.

The bipartite model of the mind; a generator and critic, similar to GANs.

The self-model as a character solving problems within a game engine; the projection of multi-dimensional problems into emotions and motivation.

The potential for detachment of consciousness from the personal self through meditation or altered states.

The self as part of its own environment; interaction with representations rather than the physical environment.