#89 – Stephen Wolfram: Cellular Automata, Computation, and Physics
Apr 18, 2020
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Stephen Wolfram, a renowned computer scientist and founder of Wolfram Research, dives deep into fascinating topics like cellular automata and their role in understanding the natural world. He explores how simple rules can lead to unexpected complexity, and discusses the philosophical implications of computation in the universe. The conversation also touches on the challenges of conveying complex scientific ideas and the evolution of programming languages. Finally, Wolfram reflects on consciousness, ethics in AI, and the quest for a unified theory of existence.
The principle of computational equivalence suggests that even systems with simple rules can exhibit complex behavior across various computational frameworks, potentially applying to the underlying structure of physics.
The search for fundamental laws of physics is ongoing, with interest in finding the most structuralist structures that can underlie space and time, whether computational or not.
Computational irreducibility is a consequence of the principle of computational equivalence, limiting our ability to predict the behavior of complex systems and necessitating the discovery of pockets of computational reducibility.
The book explores the use of computational rules and programs, generalizing mathematical equations to describe the natural world.
The podcast highlights the significance of computational language, such as Wolfram Language, in bridging the gap between human understanding and computational thinking, enabling the connection between human objectives and the power of computation.
Deep dives
The Principle of Computational Equivalence
The principle of computational equivalence suggests that when a system follows rules that aren't obviously simple, the behavior of the system corresponds to computation of equivalent sophistication. Even systems with simple rules can exhibit complex behavior. This principle holds true across various computational frameworks, including Turing machines, cellular automata, and brains. While it is not proven to be true for the physical world, there is potential for it to apply to the underlying structure of physics. However, it remains an area of ongoing research.
Understanding the Fundamental Laws of Physics
The search for the fundamental laws of physics is ongoing. It is currently unknown whether the laws of physics can be described by simple computational structures, such as cellular automata. There is interest in finding the most structuralist structures that can underlie space and time. These structures may be computational or not, and it is currently unclear. Determining the underlying computational infrastructure of the universe is a challenging task that may require the discovery of waypoints and cognitive anchors to build a human understandable narrative.
Computational Irreducibility
Computational irreducibility is a consequence of the principle of computational equivalence. Many systems exhibit computational irreducibility, where the only way to find out what they do is to follow each step and see what happens. Our human brains are not inherently smarter than simple computational systems, such as cellular automata. If the principle of computational equivalence is correct, our computations are fundamentally equivalent. This limits our ability to jump ahead and predict the behavior of complex systems. The understanding of fundamental laws of physics relies on finding pockets of computational reducibility that allow us to recognize and understand phenomena, such as the behavior of electrons.
Generalizing Mathematical Equations
The book explores generalizing the use of mathematical equations to describe the natural world by incorporating computational rules and programs.
Surprising Complexity in Cellular Automata
The book highlights the surprising complexity found in cellular automata, such as rule 30, where very simple rules can lead to intricate and unpredictable patterns.
Transformational Ideas and Intuition Breaking Discoveries
The book presents powerful and transformative ideas that challenge preconceived notions, offering fresh perspectives on the nature of computation and its potential impact on understanding the world.
Understanding the Complexity of Rule 30
The podcast episode discusses the complexity and patterns emerging from Rule 30, a cellular automaton. Despite its simple initial state, Rule 30 produces a complex and seemingly random pattern. The speaker explores the surprise and fascination of this complexity, as it challenges the intuition that simplicity in underlying rules should lead to simple outcomes. The episode raises questions about the origin of complexity in natural processes and the ability of nature to create intricate structures from simple rules.
The Power of Computational Language
The podcast highlights the significance of computational language, such as Wolfram Language, in bridging the gap between human understanding and computational thinking. By representing computational concepts using symbolic language and encompassing a broad range of knowledge, computational language empowers humans to explore and interact with the computational universe in a high-level and intuitive manner. The integration of machine learning techniques, like image identification, with computational language enhances the exploration and utilization of computable knowledge. The episode emphasizes the importance of computational language in enabling the connection between human objectives and the power of computation.
Advancements in Software Distribution: A Discussion of Software Innovation
The podcast episode explores the evolution of software distribution and highlights the recent advancements in this field. The speaker emphasizes that there has been more innovation in the distribution of software than in the structure of programming languages over the years. Examples of this innovation include the availability of free developer versions of software engines and site licenses for mathematical programming languages at universities. The speaker also explains the concept behind Wolfram Alpha, which is a system for generating reports based on natural language questions. The episode sheds light on the extensive effort to build a comprehensive knowledge base for the Wolfram Alpha system. Overall, the discussion highlights the progress and potential future developments in software distribution.
Building a Computational Knowledge Base: Challenges and Progress
The podcast episode delves into the process of building a knowledge base for the Wolfram Alpha system. The speaker discusses the initial daunting nature of this endeavor but explains how the existence of finite knowledge resources, such as reference libraries, made it less overwhelming. The approach involved implementing different areas of knowledge and gathering input from domain experts to ensure accuracy. The episode emphasizes the importance of encoding ethics and values into computational systems, particularly in areas like content selection and contracts. The discussion touches on the potential societal implications of automated content selection and the need for multiple AI systems with distinct ethics modules to accommodate different perspectives. In conclusion, the episode explores the challenges and possibilities associated with the creation of a comprehensive computational knowledge base.
Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist who is the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram Alpha, Wolfram Language, and the new Wolfram Physics project. He is the author of several books including A New Kind of Science, which on a personal note was one of the most influential books in my journey in computer science and artificial intelligence.
This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.
Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.
OUTLINE:
00:00 – Introduction
04:16 – Communicating with an alien intelligence
12:11 – Monolith in 2001: A Space Odyssey
29:06 – What is computation?
44:54 – Physics emerging from computation
1:14:10 – Simulation
1:19:23 – Fundamental theory of physics
1:28:01 – Richard Feynman
1:39:57 – Role of ego in science
1:47:21 – Cellular automata
2:15:08 – Wolfram language
2:55:14 – What is intelligence?
2:57:47 – Consciousness
3:02:36 – Mortality
3:05:47 – Meaning of life
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