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January 11, 2023

Comments

Wow, I actually agree with a lot here. That's a nice change of pace.

Like you said, ChatGPT and most other contemporary machine learning just reflects the well-known and timeless principle of statistics that having larger quantities of data, and the data being of higher quality, leads to better predictions.

The ubiquity of miniaturized, affordable sensors, plus so much of human activity being transacted online/digitally provides the abundant, high-quality data at low cost. Not to mention that computing performance keeps improving, while storage gets cheaper and more plentiful, so of course ML can take advantage of that.

Again, as you point out, ChatGPT etc. are only as good their input data, which is usually either provided by humans in the first place anyway, or derived along the way from something originally human-generated. So under the hood, it's actually just people doing the grunt work. (Cue the Soylent Green references!) Moreover, that approach bears little resemblance to real human cognition. One of the hallmarks of human reasoning (as I see it at least) is the ability to generalize from very small data sets. That's something quite lacking in ML/AI.

Similarly, another massive problem in the field is that of domain-specific approaches. As good as ChatGPT ever gets at its task, it'll never be able to one day also drive a car. You need a completely separate approach for that. Whereas, the very same humans who compose rap songs and publish essays can easily hop in the car and drive to the store whenever they need groceries.

Last, you rightly note ML/AI models' inability to recognize or comprehend the actual "semantics" of whatever task they're performing. That's another pronounced shortcoming. In the end, no matter how good ML/AI gets at replicating the performance of various discrete human tasks—and even if it does so in ways that are superficially similar to human cognition, like relying on synapses, which is just one small aspect of a brain's structure and functionality—that will hardly mean ML/AI has actually become "human" or sentient. And how could it be otherwise? After all, we're still quite far from having a comprehensive model of actual human cognition itself. You can't emulate something when you don't fully comprehend its mechanism in the first place.

However, taking all the above to manufacture an argument against mental process law seems like a total non sequitur. The doctrine's whole point isn't that a process has to be accomplished by a computer and a human in an identical way. Rather, it's just the basic yes-or-no question of whether in fact the process could be performed by a human (and/or with a physical aid)—after you properly disregard the presence of any generic computers or computer/networking constructs as mere window dressing. And that serves a laudable purpose of preventing the monopolization of business processes and other purely human activities via the simple expedient of artful claim drafting.

Kotodamas, your last sentence prompts a thought about setting a boundary between what is eligible or patenting and what is not. Should it be everything under the sun except X? Or should it be nothing under the sun except X?

I mean, every patent is a restraint of trade and we want to minimse restraints of trade, right? The only patent that is justified is the one whose restraint of trade is more than compensated for by its promotion of the progress of useful arts. The only ones that can do that are (pace GATT-TRIPS) the ones with claims that are confined in their reach to a non-obvious solution (with new technology) of a problem in technology that defeats the efforts of the univentive skilled person. So, govenments seeking to promote the progress should refuse every patent application except those, right?

Mind you, if and when somebody does invent how to get a computer to "think", they will have solved (inventively and with new technology) a stupendous problem in technology, right?

I chuckled out loud at this:

"But even if it quacks like a duck that does not mean that it flies south for the winter."

Inside joke a bit, but devastatingly on point.

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