On Thu, Dec 24, 2020 at 4:44 AM WriterOfMinds <[email protected]> wrote:
> Colin reminds me of Searle. I think the claim that underlies all his > arguments is "cognition cannot be achieved by algorithms." > Thanks for opening this door. The *paper* (not me) claims (with empirical evidence) that a science that assumes a claim "cognition can be achieved by algorithms in GP-computers", an equivalence of nature and abstract models not achieved anywhere else in the history of the science of natural phenomena, if it is to be fully and formally tested conclusively, must include null hypothesis testing that does not presuppose it to be true. Assuming it to be true has ambiguously failed non-stop for 65 years .... (evidence = see supplementary 1-3 for the failure details) while all along the actual empirical tests that properly prove it are simply missing. Restoration of the necessary empirical science option reveals AI as currently entirely conducted as a unique form of theoretical science. The physical activity of an entire community is indistinguishable in practice from what is called theoretical science everywhere else. Only AI does this. Neuroscience does not. It simply doesn't directly do AI at all but could if it knew what could be done (See supplementary 2-4). Section 5 details the proposed change to the testing (through introduction of the neuromorphic chip and its empirical science) ... and at the end of section 5 in black and white: *"Note that none of the above discussion is intended to imply that GP-computers cannot reach equivalence with natural brain function under circumstances not yet understood. That potentiality is not the issue here and is not contested. The issue here is how neuroscience and the science of AI must be configured to empirically determine any potential equivalence and the context in which it may happen. "* If you see holes in the paper's argument then supply evidence and how it impacts the specific claims in the paper. I can react helpfully to counter-evidence, not opinions. The paper can possibly be interpreted as completing Searle's argument from a science perspective. Whether it does or doesn't is moot and for somebody else to evaluate. It changes nothing in the paper and his work did not inspire the paper. This paper was founded on evidence in the form of a measurement/detection of broken science operating at the heart of 2 scientific disciplines (neuroscience & AI) blinded to it by nothing more than discipline separation, habit and 65 years of mimicry of mentors. Who's frustrated? Get in the queue! :-) Colin > Therefore, he regards any algorithmic approach (including algorithms that > model neuronal EM fields) as a non-starter. In his mind, experiments that > measure the achievements of any algorithmic approach or brain simulation > are still not "empirical," because any algorithm (including algorithms that > simulate the brain) is a theoretical model of cognition rather than a > potential achievement of cognition. An analogy that I remember from either > him or Searle or both is, "a simulation of a rainstorm will not get your > computer wet." > > I don't agree with him, but watching all of you talk past each other is > frustrating me. > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/Tf319c0e4c79c9397-M3e26fc6ca8eaa295fdedfa0d> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf319c0e4c79c9397-M572d8d4c007158c74a6eae63 Delivery options: https://agi.topicbox.com/groups/agi/subscription
