LaMDA & LeMoine

About LaMDA & LeMoine: The global “big-data” corpus of all words spoken by humans is — and would still be, if it were augmented by a transcript of every word uttered and every verbal thought ever thought by humans  — just like the shadows on the wall of Plato’s cave: It contains all the many actual permutations and combinations of words uttered and written. All of that contains and reflects a lot of structure that can be abstracted and generalized, both statistically and algorithmically, in order to generate (1) more of the same, or (2) more of the same, but narrowed to a subpopulation, or school of thought, or even a single individual; and (3) it can also be constrained or biased, by superimposing algorithms steering it toward particular directions or styles.

The richness of this intrinsic “latent” structure to speech (verbalized thought) is already illustrated by the power of simple Boolean operations like AND or NOT. The power of google search is a combination of (1) the power of local AND (say, restricted to sentences or paragraphs or documents) together with (2) the “Page-rank” algorithm, which can weight words and word combinations by their frequency, inter-linkedness or citedness (or LIKEdness — or their LIKEdness by individual or algorithm X), plus, most important ,(3) the underlying database of who-knows how-many terabytes of words so far. Algorithms as simple as AND can already do wonders in navigating that database; fancier algorithms can do even better.

LaMDA has not only data-mined that multi-terabyte word space with “unsupervised learning”, abstracting all the frequencies and correlations of words and combinations of words, from which it can then generate more of the same – or more of the same that sounds-like a Republican, or Dan Dennett or an AnimĂ© fan, or someone empathic or anxious to please (like LaMDA)
 It can be tempered and tampered by “influencer” algorithms too.

Something similar can be done with music: swallow music space and then spew out more of what sounds like Bernstein or (so far mediocre) Bach – but, eventually, who knows? These projected combinatorics have more scope with music (which, unlike language, really just is acoustic patterns based on recombinations plus some correlations with human vocal expressive affect patterns, whereas words have not just forms but meanings).

LaMDA does not pass the Turing Test because the Turing Test (despite the loose – or perhaps erroneous, purely verbal way Turing described it) is not a game about fooling people: it’s a way of testing theories of how  brains (or anything) produce real thoughts. And verbal thoughts don’t just have word forms, and patterns of word-forms: They also have referents, which are real things and states in the world, hence meaning. The Platonic shadows of patterns of words do reflect – and are correlated with – what words, too, just reflect: but their connection with the real-world referents of those words are mediated by (indeed parasitic on) the brains of the real people who read and interpret them, and know their referents through their own real senses and their real actions in and on those real referents in the real world –the real brains and real thoughts of (sometimes) knowledgeable (and often credulous and gullible) real flesh-and-blood people in-the-world


Just as re-combinatorics play a big part in the production (improvisation, composition) of music (perhaps all of it, once you add the sensorimotor affective patterns that are added by the sounds and rhythms of performance and reflected in the brains and senses of the hearer, which is not just an execution of the formal notes), word re-combinatorics no doubt play a role in verbal production too. But language is not “just” music (form + affect): words have meanings (semantics) too. And meaning is not just patterns of words (arbitrary formal symbols). That’s just (one, all powerful) way thoughts can be made communicable, from one thinking head to another. But neither heads, nor worlds, are just another bag-of-words – although the speaking head can be replaced, in the conversation, by LaMDA, who is just a bag of words, mined and mimed by a verbal database + algorithms.

And, before you ask, google images are not the world either.

The google people, some of them smart, and others, some of them not so smart (like Musk), are fantasists who think (incoherently) that they live in a Matrix. In reality, they are just lost in a hermeneutic hall of mirrors of their own creation. The Darwinian Blind Watchmaker, evolution, is an accomplice only to the extent that it has endowed real biological brains with a real and highly adaptive (but fallible, hence foolable) mind-reading “mirror” capacity for understanding the appearance and actions of their real fellow-organisms. That includes, in the case of our species, language, the most powerful mind-reading tool of all. This has equipped us to transmit and receive and decode one another’s thoughts, encoded in words. But it has made us credulous and gullible too.

It has also equipped us to destroy the world, and it looks like we’re well on the road to it


P.S. LeMoine sounds like a chatbot too, or maybe a Gullibot…

12 Points on Confusing Virtual Reality with Reality

Comments on: Bibeau-Delisle, A., & Brassard FRS, G. (2021). Probability and consequences of living inside a computer simulationProceedings of the Royal Society A477(2247), 20200658.

  1. What is Computation? it is the manipulation of arbitrarily shaped formal symbols in accordance with symbol-manipulation rules, algorithms, that operate only on the (arbitrary) shape of the symbols, not their meaning.
  2. Interpretatabililty. The only computations of interest, though, are the ones that can be given a coherent interpretation.
  3. Hardware-Independence. The hardware that executes the computation is irrelevant. The symbol manipulations have to be executed physically, so there does have to be hardware that executes it, but the physics of the hardware is irrelevant to the interpretability of the software it is executing. It’s just symbol-manipulations. It could have been done with pencil and paper.
  4. What is the Weak Church/Turing Thesis? That what mathematicians are doing is computation: formal symbol manipulation, executable by a Turing machine – finite-state hardware that can read, write, advance tape, change state or halt.
  5. What is Simulation? It is computation that is interpretable as modelling properties of the real world: size, shape, movement, temperature, dynamics, etc. But it’s still only computation: coherently interpretable manipulation of symbols
  6. What is the Strong Church/Turing Thesis? That computation can simulate (i.e., model) just about anything in the world to as close an approximation as desired (if you can find the right algorithm). It is possible to simulate a real rocket as well as the physical environment of a real rocket. If the simulation is a close enough approximation to the properties of a real rocket and its environment, it can be manipulated computationally to design and test new, improved rocket designs. If the improved design works in the simulation, then it can be used as the blueprint for designing a real rocket that applies the new design in the real world, with real material, and it works.
  7. What is Reality? It is the real world of objects we can see and measure.
  8. What is Virtual Reality (VR)? Devices that can stimulate (fool) the human senses by transmitting the output of simulations of real objects to virtual-reality gloves and goggles. For example, VR can transmit the output of the simulation of an ice cube, melting, to gloves and goggles that make you feel you are seeing and feeling an ice cube. melting. But there is no ice-cube and no melting; just symbol manipulations interpretable as an ice-cube, melting.
  9. What is Certainly Truee (rather than just highly probably true on all available evidence)? only what is provably true in formal mathematics. Provable means necessarily true, on pain of contradiction with formal premises (axioms). Everything else that is true is not provably true (hence not necessarily true), just probably true.
  10.  What is illusion? Whatever fools the senses. There is no way to be certain that what our senses and measuring instruments tell us is true (because it cannot be proved formally to be necessarily true, on pain of contradiction). But almost-certain on all the evidence is good enough, for both ordinary life and science.
  11. Being a Figment? To understand the difference between a sensory illusion and reality is perhaps the most basic insight that anyone can have: the difference between what I see and what is really there. “What I am seeing could be a figment of my imagination.” But to imagine that what is really there could be a computer simulation of which I myself am a part  (i.e., symbols manipulated by computer hardware, symbols that are interpretable as the reality I am seeing, as if I were in a VR) is to imagine that the figment could be the reality – which is simply incoherent, circular, self-referential nonsense.
  12.  Hermeneutics. Those who think this way have become lost in the “hermeneutic hall of mirrors,” mistaking symbols that are interpretable (by their real minds and real senses) as reflections of themselves — as being their real selves; mistaking the simulated ice-cube, for a “real” ice-cube.

Symbols, Objects and Features

0. It might help if we stop “cognitizing” computation and symbols. 

1. Computation is not a subset of AI. 

2. AI (whether “symbolic” AI or “connectionist’ AI) is an application of computation to cogsci.

3. Computation is the manipulation of symbols based on formal rules (algorithms).

4. Symbols are objects or states whose physical “shape” is arbitrary in relation to what they can be used and interpreted as referring to.

5. An algorithm (executable physically as a Turing Machine) manipulates symbols based on their (arbitrary) shapes, not their interpretations (if any).

6. The algorithms of interest in computation are those that have at least one meaningful interpretation.

7. Examples of symbol shapes are numbers (1, 2, 3), words (one, two, three; onyx, tool, threnody), or any object or state that is used as a symbol by a Turing Machine that is executing an algorithm (symbol-manipulation rules).

8. Neither a sensorimotor feature of an object in the world, nor a sensorimotor feature-detector of a robot interacting with the world, is a symbol (except in the trivial sense that any arbitrary shape can be used as a symbol).

9. What sensorimotor features (which, unlike symbols, are not arbitrary in shape) and sensorimotor feature-detectors (whether “symbolic” or “connectionist”) might be good for is connecting symbols inside symbol systems (e.g., robots) to the outside objects that they can be interpreted as referring to.

10. If you are interpreting “symbol” in a wider sense than this formal, literal one, then you are closer to lit-crit than to cogsci.