Hakkında
Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.
She received her PhD in 1990 from the University of Michigan under Douglas Hofstadter and John Holland, for which she developed the Copycat cognitive architecture. She is the author of "Analogy-Making as Perception", essentially a book about Copycat. She has also critiqued Stephen Wolfram's A New Kind of Science[3] and showed that genetic algorithms could find better solutions to the majority problem for one-dimensional cellular automata. She is the author of An Introduction to Genetic Algorithms, a widely known introductory book published by MIT Press in 1996. She is also author of Complexity: A Guided Tour (Oxford University Press, 2009), which won the 2010 Phi Beta Kappa Science Book Award, and Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).
While expressing strong support for AI research, Mitchell has expressed concern about AI's vulnerability to hacking as well as its ability to inherit social biases. On artificial general intelligence, Mitchell states that "commonsense knowledge" and "humanlike abilities for abstraction and analogy making" might constitute the final step required to build superintelligent machines, but that current technology is not close to being able to solve this problem.[4] Mitchell believes that humanlike visual intelligence would require "general knowledge, abstraction, and language", and hypothesizes that visual understanding may have to be learned as an embodied agent rather than merely viewing pictures.[
Unvan:
Prof. Dr. Yazar
Okurlar
15 okur okudu.
5 okur okuyacak.
Çizerlik Yaptığı Kitaplar
Sözler ve Alıntılar
"People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world."
Even the humans who train deep networks generally cannot look under the hood and provide explanations for the decisions their networks make. MIT’s Technology Review magazine called this impenetrability “the dark secret at the heart of AI.” The fear is that if we don’t understand how AI systems work, we can’t really trust them or predict the circumstances under which they will make errors.
It was not about AI becoming too smart, too invasive, too malicious, or even too useful. Instead, he was terrified that intelligence, creativity, emotions, and maybe even consciousness itself would be too easy to produce— that what he valued most in humanity would end up being nothing more than a “bag of tricks,” that a superficial set of brute-force algorithms could explain the human spirit.
Many people were shocked and upset when, in 1997, IBM’s Deep Blue chess-playing system defeated the world chess champion Garry Kasparov. This event so stunned Kasparov that he accused the IBM team of cheating; he assumed that for the machine to play so well, it must have received help from human experts. (In a nice bit of irony, during the 2006 World Chess Championship matches the tables were turned, with one player accusing the other of cheating by receiving help from a computer chess program.)
turing testinde jüriyi kandıran chatbot
JUDGE: What is your gender
EUGENE: I’m a young boy, if you care to know. And not very ugly, by the way!
JUDGE: what are you aware of at this moment
EUGENE: I would rather not talk about it if you don’t mind. Could you tell me what are you? I mean your profession.
JUDGE: how old are you
EUGENE: I’m a little boy 13 years old.
JUDGE: what are your qualifications
EUGENE: My qualifications? I’m not gonna tell you. Oooh. Anything else?
İletiler
Henüz kayıt yok
Yorumlar ve İncelemeler
