Foundation Models as the New Papyrus
Background on Papyrus
Papyrus, derived from the plant Cyperus papyrus, was a cornerstone of ancient Egyptian civilization. Its use as a writing material dates back to the First Dynasty, around 2900 BCE, with the earliest preserved texts found from circa 2560-2550 BCE at Wadi al-Jarf (The Metropolitan Museum of Art) (Encyclopedia Britannica). This plant, abundant in the Nile Delta, was not only used for writing but also for making various everyday items such as boats, baskets, mats, and sandals (Ancient Egypt Online) (World History Encyclopedia).
Papyrus offered several advantages over other materials like clay tablets and animal skins. It was lightweight, flexible, and easier to store, making it an ideal medium for recording information (Encyclopedia Britannica). The production process involved cutting the pith of the papyrus stalk into thin strips, which were then laid in layers, pressed, and dried to form durable sheets (The Metropolitan Museum of Art). This method, initially kept secret, allowed Egypt to dominate the production and trade of papyrus, exporting it widely throughout the ancient world (Ancient Egypt Online) (Encyclopedia Britannica).
Papyrus played a significant role in preserving knowledge. It was used for various texts, including religious documents like the Book of the Dead, which were placed in tombs to guide the deceased in the afterlife (The Metropolitan Museum of Art). Additionally, early Christian texts, including parts of the New Testament, were written on papyrus in codex form, which allowed easier reading and handling compared to scrolls (World History Encyclopedia).
Similarity Between Foundation Models and Papyrus
Learning Curve and Ubiquity: Foundation models in AI, like the advent of papyrus, are transforming how we handle information. Initially requiring specialized skills (For example, prompt engineering), these technologies are becoming more accessible. Future generations will need no technical expertise and more emphasis on critical thinking and humanities. Just as papyrus became an everyday material, generative AI will likely become an integral part of daily life (Encyclopedia Britannica) (Ancient Egypt Online).
Proprietary vs. Open Source Development: The production of papyrus was a closely guarded secret, much like some leading proprietary foundation models today. However, the trend towards open-source AI models mirrors the eventual widespread availability of papyrus. This openness fosters innovation and widespread adoption, much like how papyrus facilitated the spread of knowledge across ancient civilizations (Encyclopedia Britannica) (The Metropolitan Museum of Art).
Bridging Civilizations: Papyrus served as a bridge between cultures, adopted by the Greeks after Egyptians and extensively used in the Roman Empire, enabling the exchange of ideas and knowledge (Encyclopedia Britannica) (Ancient Peoples). Similarly, foundation models in AI embed and disseminate cultural and societal knowledge globally. They enhance communication and understanding across different cultures, much like papyrus enabled ancient civilizations to share their wisdom and literature. The Greeks and Romans, for instance, utilized papyrus for their administrative records, literature, and scientific texts, which helped preserve and transmit the knowledge of earlier civilizations to subsequent generations (Encyclopedia Britannica) (Ancient Peoples).
Conclusion
Foundation models in AI are poised to be as transformative as papyrus was in ancient Egypt. They are changing how we store and share knowledge. Initially proprietary, these technologies are becoming more open, fostering innovation and broader adoption. By understanding the historical significance of papyrus, we can better appreciate the potential impact of AI on modern society, emphasizing the importance of open use in the long term. Just as papyrus carried the wisdom of ancient civilizations, foundation models will carry the collective intelligence of our time into the future.
Further read
From Infinite Improbability to Generative AI: Navigating Imagination in Fiction and Technology
Human vs. AI in Reinforcement Learning through Human Feedback
Generative AI for Law: The Agile Legal Business Model for Law Firms
Generative AI for Law: From Harvard Law School to the Modern JD
Unjust Law is Itself a Species of Violence: Oversight vs. Regulating AI
Generative AI for Law: Technological Competence of a Judge & Prosecutor
Law is Not Logic: The Exponential Dilemma in Generative AI Governance
Generative AI & Law: I Am an American Day in Central Park, 1944
Generative AI & Law: Title 35 in 2024++ with Non-human Inventors
Generative AI & Law: Similarity Between AI and Mice as a Means to Invent
Generative AI & Law: The Evolving Role of Judges in the Federal Judiciary in the Age of AI
Embedding Cultural Value of a Society into Large Language Models (LLMs)
Lessons in Leadership: The Fall of the Roman Republic and the Rise of Julius Caesar
Justice Sotomayor on Consequence of a Procedure or Substance
From France to the EU: A Test-and-Expand Approach to EU AI Regulation
Beyond Human: Envisioning Unique Forms of Consciousness in AI
Protoconsciousness in AGI: Pathways to Artificial Consciousness