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Yeah sure, but most CS students will have to do a simple paper trace of a TM or design a TM diagram to graduate. It was on the exam and they only gave you 90 mi

Yeah sure, but most CS students will have to do a simple paper trace of a TM or design a TM diagram to graduate. It was on the exam and they only gave you 90 minutes, so it is clearly possible to train a human to do it. Regarding the second half. You aren't very creative. Sometimes you have something very basic, like two tables with numbers in the columns and you ask the LLM to select table rows using it's language capabilities and then tell it to give you the sum and it doesn't work. Great. Except in two years someone will figure out how to train a model to do this and nobody will care. The bitter lesson doesn't mean architectural changes are worthless, it just tells you that an approach that lets the machine leverage its computational capabilities will outpace a researcher's effort to patch a fundamentally broken model with a thousand small workarounds.

vidarh 3y ago
So incentives, in other words. It is possible to teach a human there are consequences not to, and rewards for doing so, because we are consistently fine tuning and retaining state over time, and we have feedback mechanisms in the form of drives. Nothing I said is to suggest it can't be done with LLMs - I'm on record in HN saying LLMs can be made to work as turing machines just fine, and I stand by that. What you can't expect is to give it a prompt, no ongoing constraints or reinforcement, or other feedback, and stay on task for prolonged periods of time. Humans don't do that with any consistency. We self regulate through a whole array of feedback systems, including internal ongoing thoughts, that by the time of exams have been conditioned over years to get better at sticking to a task and consider exam outcomes to matter. And still a lot of us struggle to keep focus for even that kind of time period. Or engage in activities we know are bad for us. Provide similar mechanisms to regular LLMs and they can stay on task too - we can trivially get LLMs to execute individual steps of turing machines, so getting them to keep doing it is a question of how to regulate their ongoing behaviour, not an inherent limitation.

vidarh 3y ago

So incentives, in other words. It is possible to teach a human there are consequences not to, and rewards for doing so, because we are consistently fine tuning and retaining state over time, and we have feedback mechanisms in the form of drives. Nothing I said is to suggest it can't be done with LLMs - I'm on record in HN saying LLMs can be made to work as turing machines just fine, and I stand by that. What you can't expect is to give it a prompt, no ongoing constraints or reinforcement, or other feedback, and stay on task for prolonged periods of time. Humans don't do that with any consistency. We self regulate through a whole array of feedback systems, including internal ongoing thoughts, that by the time of exams have been conditioned over years to get better at sticking to a task and consider exam outcomes to matter. And still a lot of us struggle to keep focus for even that kind of time period. Or engage in activities we know are bad for us. Provide similar mechanisms to regular LLMs and they can stay on task too - we can trivially get LLMs to execute individual steps of turing machines, so getting them to keep doing it is a question of how to regulate their ongoing behaviour, not an inherent limitation.