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Stephen Wolfram's Picks of Cellular Automata from the Computational Universe

Wolfram・146 minutes read

The speaker delves into the significance of blockchain and NFTs for storing history, exploring computational contracts and unique ownership in a decentralized system, showcasing NFTs' capabilities on various blockchains. They experiment with cellular automata for NFT creation, focusing on visual patterns, and naming while reflecting on the unpredictability and potential of different automata.

Insights

  • The speaker is delving into the significance of blockchain and NFTs, aiming to explore their role in storing history and the past, highlighting the strength of blockchain in maintaining a consistent ledger for future value.
  • NFTs offer unique ownership and computational contracts, enabling complex interactions and virtualized identities, showcasing transaction data and the potential for secondary markets with specific contractual terms.
  • Computational contracts, broader than smart contracts, represent real-world knowledge in a computational language, encrypting NFTs, controlling visibility, and enabling future interactions, with a focus on validating NFT claims.
  • Cellular automata, used for NFT creation, generate complex patterns from simple rules, showcasing computational irreducibility and aesthetic content, with the speaker experimenting with different rules and patterns for visual outcomes.

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Recent questions

  • What is the significance of blockchain technology?

    Blockchain technology offers a decentralized and autonomous system with a consistent ledger, ensuring past integrity for future value. It plays a crucial role in storing history and preserving events, serving as a permanent legacy on the blockchain.

  • How do NFTs differ from fungible tokens?

    NFTs provide unique ownership and computational contracts, unlike fungible tokens. They allow for complex interactions, virtualized identities, and the representation of real-world knowledge in a computational language.

  • What is the role of computational contracts in NFTs?

    Computational contracts, broader than smart contracts, encrypt NFTs, control visibility, and enable future interactions. They facilitate the maintenance of achievements, certifications, personal history, and contractual terms in the NFT ecosystem.

  • How are NFTs used to verify ownership and identity?

    NFTs serve as a means to verify ownership, rights, personal identity, and achievements, transferable to others. They record creation moments, encapsulate detailed information, and maintain a permanent legacy of events on the blockchain.

  • What is the process of minting NFTs on the Cardano blockchain?

    The process involves selecting unique cellular automata patterns, running them for varying steps, and analyzing the results. The speaker creates NFTs with specific rules, evaluates visual patterns, and names them based on their appearance and characteristics.

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Summary

00:00

"Exploring Blockchain, NFTs, and Computational Contracts"

  • The speaker, known for discussing physics and computational language, is embarking on their first public NFT live minting, delving into the significance of blockchain and NFTs.
  • Their interest lies in various forms of computation, including blockchain's unique autonomous computation, leading to a blend of future technology and historical preservation.
  • The live minting event is experimental, with potential failures, aiming to explore blockchain's role in storing history and the past.
  • Blockchain's strength lies in its consistent ledger, requiring past integrity for future value, making it a decentralized and autonomous system.
  • The speaker's interest in history and computational contracts stems from a deep understanding of computation in physics and the universe.
  • Blockchain's autonomous computation parallels the universe's computational maintenance, albeit on a smaller scale.
  • NFTs, unlike fungible tokens, offer unique ownership and computational contracts, allowing for complex interactions and virtualized identities.
  • Computational contracts, a broader concept than smart contracts, enable representation of real-world knowledge in a computational language.
  • The speaker demonstrates blockchain data analysis using Wolfram Language, showcasing NFT statistics on the Ethereum blockchain.
  • The speaker explores the concept and form of NFTs, highlighting their unique nature and computational contract capabilities.

16:42

Unveiling the Power of NFTs

  • NFTs showcase transaction data, revealing input data and event lists associated with specific transactions.
  • Input data is displayed as bytes, potentially holding interesting information.
  • NFTs can store an ID number linked to a piece of art, with some containing more detailed information.
  • NFTs on the Tezos blockchain feature emoji representations of images.
  • NFTs serve as a means to verify ownership, rights, or personal identity, transferable to others.
  • NFTs on blockchains record creation moments, becoming a permanent legacy of events.
  • NFTs can encapsulate achievements, certifications, or personal history, maintained on the blockchain.
  • Computational contracts can encrypt NFTs, control their visibility, and enable future interactions.
  • NFTs can have secondary markets, potentially allowing sales with specific contractual terms.
  • Validating NFT claims involves ensuring accuracy through models, machine learning, and trust chains.

33:11

"Blockchain tech creates Cardano NFTs with Rule 30"

  • Blockchain technology is used to store the content hash of images specified by IPFS.
  • Graduation tokens are created using this technology.
  • Wallets may soon display Cardano NFTs with thumbnails for easy identification.
  • Computational experiments with NFTs are recorded on the Cardano blockchain.
  • Live minting involves selecting unique cellular automata for NFT creation.
  • Cellular automata are simple programs that update based on neighboring cells.
  • Cellular automata generate complex patterns from simple rules, like Rule 30.
  • Rule 30 showcases computational irreducibility, leading to unpredictable complexity.
  • Cellular automata patterns have been used for various artistic purposes.
  • The computational universe offers aesthetic content, like musical tunes from cellular automata.

48:58

"Exploring Computational Patterns for NFT Creation"

  • The speaker is experimenting with rules and patterns in a computational context.
  • They are testing different rules for cellular automata, running them for varying numbers of steps.
  • The speaker identifies a rule that looks promising after running it for 80 steps.
  • They mention using 450 steps as a standard for their cellular automata.
  • The speaker selects specific rules to further analyze and potentially mint as NFTs.
  • Machine learning systems have been used to identify interesting patterns.
  • The speaker discusses the process of minting NFTs on the Cardano blockchain.
  • They mention creating 20 NFTs with 20 copies each, to be made available for auction.
  • The speaker humorously references the manual and time-consuming nature of the minting process.
  • Historical anecdotes about Charles Babbage and the automation of mathematical tables are shared.

01:07:09

Historical Milestone: First NFTs Minted on Cardano

  • In 1835, the analytical engine was discussed, marking a historical point.
  • Two individuals exchanged mail messages living a mile and a half apart in London, with 14 mail deliveries daily.
  • The term "crashing waves" was chosen for the first test NFT, aiming for a non-pun name.
  • The first live minting occurred, with crashing waves as the first funded NFT.
  • The minting process involved composing sounds from the computational universe.
  • The NFT was minted on the Cardano blockchain, with a transaction ID in block number six million.
  • The blockchain transaction data included the description and cellular automaton code.
  • The NFT's content was stored on IPFS, requiring external storage for permanent storage.
  • A second NFT, named "down arrows," was minted with a unique image.
  • The process of minting NFTs involved selecting names and images, previewing, and minting them.

01:25:46

Evaluating Visual Patterns: Artistic Potential Explored

  • The speaker evaluates various visual patterns, expressing skepticism about some but optimism about others.
  • They discuss the potential of different color combinations and patterns, noting the possibility of interesting outcomes.
  • The speaker considers the vertical alignment of certain patterns, speculating on their potential interest.
  • They comment on the resemblance of a purple and green pattern to a spider, finding it visually appealing.
  • The speaker engages in a dialogue about the visual interpretations of different patterns, considering them as potential art forms.
  • They discuss the computational process behind generating these visual patterns and the randomness that emerges.
  • The speaker explores different interpretations of the visual patterns, ranging from natural forms to technological concepts.
  • They experiment with running multiple computations in parallel to explore a variety of visual outcomes.
  • The speaker evaluates the results of the computational experiments, noting patterns that are visually appealing or mundane.
  • They engage in a creative process of naming the visual patterns based on their appearance and characteristics.

01:45:21

Exploring Patterns in Cellular Automata

  • The speaker discusses the concept of formations optimized for specific purposes, mentioning a preference for Avery's creeping vines.
  • They attempt to recall the appearance of a plant, specifically wisteria, but struggle to find an image online.
  • The search for wisteria leads to discussions on its resemblance to a willow tree and the difficulty in associating its appearance.
  • The speaker explores the idea of the plant resembling blue ivy and considers the term "creeper" in relation to plants and other references.
  • Suggestions for names like "wisteria cascade" and "creeping periwinkle" are proposed and evaluated.
  • The speaker reflects on the challenge of naming things without a clear association, likening it to a class four cellular automaton pattern.
  • They continue to examine various cellular automata patterns, expressing hopes for finding interesting ones.
  • The process of selecting and naming patterns is discussed, with considerations for uniqueness and visual appeal.
  • The speaker shares personal anecdotes about recognizing faces and relates it to their ability to identify patterns in cellular automata.
  • They engage in naming discussions for newly discovered patterns, considering names like "ice queen" and "organic circuit board."
  • The speaker expresses the excitement and uncertainty of exploring cellular automata patterns, highlighting the unpredictability of their outcomes.

02:07:18

"Predicting Success in Green Cellular Automata"

  • Talent is hard to predict when young; experience is needed to assess potential accurately.
  • Selecting cellular automata early is akin to choosing show animals; predicting their success is challenging.
  • Green automata are favored; a particular one in the third batch is promising.
  • Patterns in fabrics and cultures reflect our innate attraction to certain designs.
  • Systems like cellular automata capture the complexity found in nature.
  • Various automata are likened to cityscapes, Peruvian or Mayan structures.
  • Some automata show intricate structures and potential for aesthetic appeal.
  • A diverse range of automata is selected for further processing.
  • Names like "Jungle Gym" and "Infinite Willow" are chosen for specific automata.
  • The process of minting and naming automata is completed, concluding the task.

02:34:24

"Audio pitch shifting for creative sound effects"

  • Experimenting with audio pitch shifting to create different sounds
  • Discussing the process of changing voice frequencies to produce desired effects
  • Exploring various audio effects like pitch shift, reverb, and time stretch
  • Mentioning the use of audio spectral mapping for modifying functions
  • Considering different names for creative projects like "current c carpet" and "the irreducible carpet"
  • Deliberating on historical figures like Gliemo Cardano and his potential use of Persian carpets
  • Naming creative projects like "the never-ending jungle gym" and "the infinite jungle gym"
  • Addressing character limits for project descriptions and making necessary adjustments
  • Exploring the concept of proof of space-time storage networks for blockchain storage
  • Reflecting on the sustainability and value generation in blockchain technology, proposing meaningful computational tasks for economic value

03:02:54

"Preserving Data with NP Problems and NFTs"

  • NP problems are non-deterministic polynomial time computations, like factoring, where checking prime factors is fast but finding them is slow.
  • The challenge is ensuring consistent computational work for problem-solving, avoiding fluctuations in effort.
  • The NP problem class is relevant for useful computations with consistent effort.
  • Long-term data storage requires active maintenance, like moving data periodically to ensure accessibility.
  • Cold storage methods, like etching data onto durable materials, can ensure long-term data preservation.
  • Reading stored data can be challenging over time, as seen with the Voyager spacecraft's gold disc.
  • Quartz disks with high-resolution images can store data for extended periods, like the Arch Mission project.
  • Computational contracts can run cellular automaton rules over time, potentially growing NFTs.
  • Cellular automata art generation can be complex due to the vast space of possible images.
  • The process of live minting NFTs and creating an ecosystem around long-term data preservation is being developed.

03:19:09

"Cellular Automata: Patterns, Reversibility, and Blockchain"

  • Cellular automata can have different patterns based on various starting points, even with random initial conditions.
  • In ordinary cellular automata, every cell operates according to the same rule, making it challenging to assign different rules to different starting points.
  • Multi-way cellular automata involve branching histories, akin to quantum mechanics, requiring quantum computation to determine outcomes.
  • Reversible cellular automata can go both forwards and backwards in time, starting from simple states and evolving into complex behaviors.
  • Reversibility in cellular automata is crucial for understanding the second law of thermodynamics, which states that entropy tends to increase over time.
  • Observers of evolving systems face challenges in describing irreducible computations and complex structures, especially when computations are bounded.
  • Blockchain technology, particularly Cardano, is utilized for NFTs and computational contracts, aiming to connect to various blockchains and provide diverse services.
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