> There is no summary of these photographs which gives information about the world over and above just summarising patterns in the night sky.
You're stating this as fact but it seems to be the very hypothesis the authors (and related papers) are exploring. To my mind, the OthelloGPT papers are plainly evidence against what you've written - summarising patterns in the sky really does seem to give you information about the world above and beyond the patterns themselves.
(to a scientist this is obvious, no? the precession of mercury, a pattern observable in these photographs, was famously not compatible with known theories until fairly recently)
> Modelling the measurement data is taking cardboard and cutting it out so it matches the shadows. Modelling the world means creating clay pots to match the ones passing by.
I think these are matters of degree. The former is simply a worse model than the latter of the "reality" in this case. Note that our human impressions of what a pot "is" are shadows too, on a higher-dimensional stage, and from a deeper viewpoint any pot we build to "match" reality will likely be just as flawed. Turtles all the way down.
It is exactly this non-sequitur which I'm pointing out.
Approximating an abstract discrete function (a game), with a function approximator has literally nothing to do with whether you can infer the causal properties of the data generating process from measurement data.
To equate the two is just rank pseudoscience. The world is not made of measurements. Summaries of measurement data aren't properties in the world, they're just the state of the measuring device.
If you sample all game states from a game, you define the game. This is the nature of abstract mathematical objects, they are defined by their "data".
Actual physical objects are not defined by how we measure them: the solar system isnt made of photographs. This is astrology: to attribute to the patterns of light hitting the eye some actual physical property in the universe which corresponds to those patterns. No such exists.
It is impossible, and always has been, to treat patterns in measurements as properties of objects. This is maybe one of the most prominent characteristics of psedusocience.
The point is that approximating a distribution causally downstream of the game (text-based descriptions, in this case) produces a predictive model of the underlying game mechanics itself. That is fascinating!
Yes, the one is formally derivable from the other, but the reduction costs compute, and to a fixed epsilon of accuracy this is the situation with everything we interact with on the day to day.
The idea that you can learn underlying mechanics from observation and refutation is central to formal models of inductive reasoning like Solomonoff induction (and idealised reaoners like AIXI, if you want the AI spin). At best this is well established scientific method, at worst a pretty decent epistemology.
Talking about sampling all of the game states is irrelevant here; that wouldn't be possible even in principle for many games and in this case they certainly didn't train the LLM on every possible Othello position.
> This is astrology: to attribute to the patterns of light hitting the eye some actual physical property in the universe which corresponds to those patterns. No such exists.
Of course not - but they are highly correlated in functional human beings. What do you think our perception of the world grounds out in, if not something like the discrepancies between (our brain's) observed data and it's predictions? There's even evidence in neuroscience that this is literally what certain neuronal circuits in the cortex are doing (the hypothesis being that so-called "predictive processing" is more energy efficient than alternative architectures).
Patterns in measurements absolutely reflect properties of the objects being measured, for the simple reason that the measurements are causally linked to the object itself in controlled ways. To think otherwise is frankly insane - this is why we call them measurements, and not noise.
You're stating this as fact but it seems to be the very hypothesis the authors (and related papers) are exploring. To my mind, the OthelloGPT papers are plainly evidence against what you've written - summarising patterns in the sky really does seem to give you information about the world above and beyond the patterns themselves.
(to a scientist this is obvious, no? the precession of mercury, a pattern observable in these photographs, was famously not compatible with known theories until fairly recently)
> Modelling the measurement data is taking cardboard and cutting it out so it matches the shadows. Modelling the world means creating clay pots to match the ones passing by.
I think these are matters of degree. The former is simply a worse model than the latter of the "reality" in this case. Note that our human impressions of what a pot "is" are shadows too, on a higher-dimensional stage, and from a deeper viewpoint any pot we build to "match" reality will likely be just as flawed. Turtles all the way down.