24/04/2024
The idea of infinite texts described in stories The Garden of Forking Paths and The Library of Babel by Jorge Luis Borges, builds a compelling viewpoint, an analog to perfect language models. Truth or intention does not matter to large language models, what matters is just a narrative necessity. In some way similarly, humans use fiction to understand the word, to search for truth. We can use LLM effectively with a Human verification step, Leon Bottou concludes.
We are pleased to announce that we are starting to publish the recordings of the ML in PL 2023 conference!
First, we invite you to watch the Keynote Talk by LÉON BOTTOU: "BORGES AND AI".
https://youtu.be/OVQvK2bjh00
Many believe that Large Language Models (LLMs) open the era of Artificial Intelligence (AI). Some see opportunities while others see dangers. Yet both proponents and opponents grasp AI through the imagery popularised by science fiction. Will the machine become sentient and rebel against its creators? Will we experience a paperclip apocalypse? Before answering such questions, we should first ask whether this mental imagery provides a good description of the phenomenon at hand. Understanding weather patterns through the moods of the gods only goes so far. The present paper instead advocates understanding LLMs and their connection to AI through the imagery of Jorge Luis Borges, a master of 20th century literature, forerunner of magical realism, and precursor to postmodern literature. This exercise leads to a new perspective that illuminates the relation between language modelling and artificial intelligence.
Léon Bottou received the Diplôme d'Ingénieur de l'École Polytechnique (X84) in 1987, the Magistère de Mathématiques Fondamentales et Appliquées et d'Informatique from École Normale Supérieure in 1988, and a Ph.D. in Computer Science from Université Paris-Sud in 1991. His research career took him to AT&T Bell Laboratories, AT&T Labs Research, NEC Labs America and Microsoft . He joined AI at Meta (formerly Facebook AI Research) in 2015. The long-term goal of Léon Bottou's research is to understand and replicate intelligence. Because this goal requires conceptual advances that cannot be anticipated, Leon's research has followed many practical and theoretical turns: neural networks applications in the late 1980s, stochastic gradient learning algorithms and statistical properties of learning systems in the early 1990s, computer vision applications with structured outputs in the late 1990s, theory of large scale learning in the 2000s. During the last few years, Léon Bottou's research aims to clarify the relation between learning and reasoning, with more and more focus on the many aspects of causation (inference, invariance, reasoning, affordance, and intuition.).
