Searle uses a lookup table argument in the chinese room. I was making the case that lookup tables as a computational tool can be turing complete, and I&#x27;m assuming Searle covered Turing completeness in his argument.  (I read the chinese room a long time ago so even if he doesn&#x27;t cover turning machines explicitly, He has argued elsewhere, explicitly, that Turing machines and the kinds of outcomes they can produce do not get us past the problem of meaning elucidated by the Room argument.)<p>I think Aaronson demolishes the other critics arguments because he shows they focus on the lookup table and attach sentience to algorithmically complex solutions but not to exponentially complex solutions. My point is the lookup table is irrelevant, in practical terms, because the lookup table in Searle&#x27;s argument exists only as a &quot;philosophical fiction&quot; as Aaronson says.  But I was pointing out that lookup tables can be Turing complete.  And hence any Turing machine could be substituted for the mechanism in Searles&#x27;s room and thus the particular mechanism of the room&#x27;s operation is irrelevant. (in any kind of Turing completeness sense)<p>I took Aaronson as being humorous here: &quot;Yet, as much as that criterion for sentience flatters my complexity-theoretic pride, I find myself
reluctant to take a position on such a weighty matter.&quot; Because there is no obvious reason an algorithmically complex solution should somehow be sentient when an exponentially complex solution should not be. How could the lower mathematical bound confer sentience?<p>Aaronson&#x27;s paper is about the practical requirements to pass a Turing test in some given amount of time. It is a testable problem. Searle&#x27;s argument is about what it means to produce actual sentience. Aaronson does not really get into this.<p>There is an argument against Searle along the lines of &quot;what are the requirements for a machine which passes the Turing test for Searle.&quot;  And Searle&#x27;s response to these practicalities are weak, at best.  But those arguments have nothing to do with Searle&#x27;s point in the Chinese Room. Aaronson sort of reflects those critiques of Searle, but he also realizes the hand-wavy problem of meaning is something he doesn&#x27;t address.<p>Personally, I get very frustrated when people mistake the problem of sentience for the testable hypothesis of a Turing test (or any of the other &quot;practical&quot; problems).  I think the problem of sentience is a real problem, and it requires a practicable solution to produce machine sentience, machines which have and understand meaning.  So arguments against Searle&#x27;s Room that do not address how to instantiate meaning in a computer system are disappointing because they ignore his basic point. (Aaronson is making arguments about complexity and Turing tests) Ignoring the key problem is not a critique of that problem. And critiquing an argument is not necessarily a critique of the point or concept the argument elucidates.<p>Meaning is a real thing.<p>If you sit down to make a machine conscious, you have to deal with what awareness is and how meaning and representation work- at the very beginning.  And then figure out how to make computers do representational processing and instantiate awareness.<p>All of the modern approaches abandon the problem of actual sentience and the problems of meaning; because, they are hard.  Or it&#x27;s too hard to finish in the timeline of a PhD. So people do the reverse, start with the algorithms and solve a testable sub-problem and make some practical progress in computer science or in industry. (which is a good thing!)<p>Nearly everyone abandons the hard problem of meaning and how meaning works and chooses to solve a different problem.   This does not mean our solutions to those other problems are solutions to the hand-wavy problem of meaning.  It rather makes me think of people who figured how to make fake feathers and then assumed the process of making fake feathers will naturally lead to human flight.<p>I think this is a clue that the typical computer science approach, which has made great progress in what we call artificial intelligence, is maybe the wrong approach to solve the sentience problem. Not that computer science is irrelevant, but that the general computer science approach simply does not provide a path toward, or the theoretical foundation, to make computers which are aware and can generate and understand meaning.