Only if your AI coding approach is the slot machine approach.
I've ended up with a process that produces very, very high quality outputs. Often needing little to no correct from me.
I think of it like an Age of Empires map. If you go into battle surrounded by undiscovered parts of the map, you're in for a rude surprise. Winning a battle means having clarity on both the battle itself and risks next to the battle.
Until it produces predictable output, it's gambling. But it can't produce predictable output because it's a non-deterministic tool.
What you're describing is increasing your odds while gambling, not that it's not gambling. Card counting also increases your odds while gambling, but it doesn't make it not gambling.
This is a pretty wild comparison in my opinion, it counts almost everything as gambling which means it has almost no use as a definition.
The most obvious issue is it’d class working with humans as gambling. Fine if you want to make that as your definition but it seems unhelpful to the discussion.
You seem to have a fundamental issue understanding what the term deterministic even means.
If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time. Hell, it might even get better over time by giving them feedback at the end of the task that it can learn from.
If you run the same script five times in a row while changing some input variables, you're gonna get the same, predictable output that you can understand, look at the code, and fix.
If you ask the same question to the same LLM model five times in a row, are you getting the same result every time? Is it kind of random? Can the quality be vastly different if you reject all of its changes, start a new conversation, and tell it to do the same thing again using the exact same prompt? Congrats, that's gambling. It's no different than spinning a slot machine in a sense that you pass it an input and hope for the best as the output. It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
Deterministic doesn’t mean “generally pretty predictable, in broad strokes”.
> If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time.
Probably pretty similar but not quite the same. Sometimes they might drop a plate.
> If you ask the same question to the same LLM model five times in a row, are you getting the same result every time?
Probably pretty similar results. Sometimes they might mess up.
> It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
It rather can, we don’t call literally anything with a random element to the outcome gambling.
I’m probably gambling with my life if I pick a random stranger to operate on me. Am I gambling with my life if I take a considered look at the risk and reward and select a highly qualified surgeon?
Is it gambling to run a compiler given that bitflips can happen?
How does it 'count almost everything as gambling'? They just said 'non-deterministic' output is gambling-like, that is not 'almost everything'. Most computation that you use on a day-to-day basis (depending on how much you use AI now I suppose) is in all ways deterministic. Using probabilistic algorithms is not new, but it your point is not clicking...
Almost everything is non deterministic to some degree. Huge amounts of machine learning, most things that have some timing element to them in distributed systems, anything that might fail, anything involving humans, actual running computation given that bitflips can happen. At what point does labelling everything that has some random element “gambling” become pointless? At best it’ll be entirely different to how others use the term.
That starts to get into a very philosophical space talking about human action as deterministic or not. I think keeping to the fact that the artifacts (ie code) we are working off will have deterministic effects (unless we want it not to) is exactly the point. That is what lets chaotic human brains communicate with machines at all. Adding more chaos to the system doesn't strike me as obviously an improvement.
Dam this is so accurate. As a project manager turned product manager this is so true. You need to estimate a project based on the “pedigree” of your engineers
Only if your AI coding approach is the slot machine approach.
I've ended up with a process that produces very, very high quality outputs. Often needing little to no correct from me.
I think of it like an Age of Empires map. If you go into battle surrounded by undiscovered parts of the map, you're in for a rude surprise. Winning a battle means having clarity on both the battle itself and risks next to the battle.
Good analogy! Would be interesting to read more details about how you’re getting very high quality outputs
Would you mind sharing some of your findings?
Until it produces predictable output, it's gambling. But it can't produce predictable output because it's a non-deterministic tool.
What you're describing is increasing your odds while gambling, not that it's not gambling. Card counting also increases your odds while gambling, but it doesn't make it not gambling.
This is a pretty wild comparison in my opinion, it counts almost everything as gambling which means it has almost no use as a definition.
The most obvious issue is it’d class working with humans as gambling. Fine if you want to make that as your definition but it seems unhelpful to the discussion.
You seem to have a fundamental issue understanding what the term deterministic even means.
If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time. Hell, it might even get better over time by giving them feedback at the end of the task that it can learn from.
If you run the same script five times in a row while changing some input variables, you're gonna get the same, predictable output that you can understand, look at the code, and fix.
If you ask the same question to the same LLM model five times in a row, are you getting the same result every time? Is it kind of random? Can the quality be vastly different if you reject all of its changes, start a new conversation, and tell it to do the same thing again using the exact same prompt? Congrats, that's gambling. It's no different than spinning a slot machine in a sense that you pass it an input and hope for the best as the output. It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
Deterministic doesn’t mean “generally pretty predictable, in broad strokes”.
> If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time.
Probably pretty similar but not quite the same. Sometimes they might drop a plate.
> If you ask the same question to the same LLM model five times in a row, are you getting the same result every time?
Probably pretty similar results. Sometimes they might mess up.
> It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
It rather can, we don’t call literally anything with a random element to the outcome gambling.
I’m probably gambling with my life if I pick a random stranger to operate on me. Am I gambling with my life if I take a considered look at the risk and reward and select a highly qualified surgeon?
Is it gambling to run a compiler given that bitflips can happen?
At what point does the word lose all meaning?
How does it 'count almost everything as gambling'? They just said 'non-deterministic' output is gambling-like, that is not 'almost everything'. Most computation that you use on a day-to-day basis (depending on how much you use AI now I suppose) is in all ways deterministic. Using probabilistic algorithms is not new, but it your point is not clicking...
Almost everything is non deterministic to some degree. Huge amounts of machine learning, most things that have some timing element to them in distributed systems, anything that might fail, anything involving humans, actual running computation given that bitflips can happen. At what point does labelling everything that has some random element “gambling” become pointless? At best it’ll be entirely different to how others use the term.
Working with humans is decidedly not deterministic, though. And the discussion here is comparing AI coding agents and humans.
That starts to get into a very philosophical space talking about human action as deterministic or not. I think keeping to the fact that the artifacts (ie code) we are working off will have deterministic effects (unless we want it not to) is exactly the point. That is what lets chaotic human brains communicate with machines at all. Adding more chaos to the system doesn't strike me as obviously an improvement.
Similar to quantum computing, a probabilistic model when condensed to sufficiently narrow ranges can be treated as discrete.
Dam this is so accurate. As a project manager turned product manager this is so true. You need to estimate a project based on the “pedigree” of your engineers
Would it make us uncomfortable to reword the above example to
> AI coding is gambling on slot machines, managing developers is gambling on the stock market.
Because I feel like that is a much more apt analogy.
What is it with you guys and stallions?
There is a long history of managers just wanting to work their developers like horses.
Great analogy, I’m saving it!