Meno male che ormai la comunita’ inizia a dire che non e’ vera intelligenza, senza vergognarsi di fare affermazioni fuori dal mainstream tecno-utopico
“statistics do amount to understanding” spero per lui che la sua facoltà di comprensione sia più di una mera correlazione statistica…
“Stochastic parrots” e’ bellissima.
Source : Mindmatters
Chatbots: Still Dumb After All These Years
In 1970, Marvin Minsky, recipient of the Turing Award (“the Nobel Prize of Computing”), predicted that within “three to eight years we will have a machine with the general intelligence of an average human being.”
Fifty-two years later, we’re still waiting.
The fundamental roadblock is that, although computer algorithms are really, really good at identifying statistical patterns, they have no way of knowing what these patterns mean because they are confined to MathWorld and never experience the real world.
As Richard Feynman famously explained, there is a fundamental difference between labeling things and understanding them: [My father] taught me “See that bird? It’s a brown-throated thrush, but in Germany it’s called a halsenflugel, and in Chinese they call it a chung ling and even if you know all those names for it, you still know nothing about the bird–you only know something about people; what they call that bird. Now that thrush sings, and teaches its young to fly, and flies so many miles away during the summer across the country, and nobody knows how it finds its way,” and so forth. There is a difference between the name of the thing and what goes on.
Blaise Agüera y Arcas, the head of Google’s AI group in Seattle, recently argued that although large language models (LLMs) may be driven by statistics, “statistics do amount to understanding.” As evidence, he offers several snippets of conversation with Google’s state-of-the-art chatbot LaMDA. The conversations are impressively human-like, but they are nothing more than examples of what Gary Marcus and Ernest Davis have called an LLM’s ability to be “a fluent spouter of bullshit” and what Timnit Gebru and three co-authors called “stochastic parrots.”