He reads, "Step-1: prior to translating the note, we are going to train your neural networks on a Chinese corpus consisting of 410 billion tokens from Common Crawl, 19 billion tokens from WebText, 67 billion tokens from Books, and 3 billion tokens from Wikipedia. Training in 5, 4, 3..."

He shouts, "wait but if you do that wo shuō zhōngwén."

Does it matter then that the writer has no understanding of the language, when the backend clearly does?

(I think I get it actually, after writing these two questions, but I’ll post them anyway.)

Searle and subsequent proponents fail to define mind, intelligence, or understanding. The argument is founded in anthropocentric arrogance.

Gpt-3 has convincingly passed the Turing test, with various and sundry incarnations passing as human for days or even weeks on reddit and Twitter and other social media. You can keep moving the goalposts, but the herd has left the barn. The argument is over. The Turing test has been passed.

There is no way to frame human mind, intelligence, or understanding such that you exclude the equivalent functionality in software without engaging in magical thinking.

Searle's assertion that he would not understand Chinese while executing the rules isn't relevant. Searle could conceivably execute the inference pass over a gpt-3 model based on Chinese, and produce results that surpass the Turing threshold as conceived by Searle at the time. The intelligence and understanding and mind is encoded in the model and logic of the processing.

This demonstrates that substrate is not involved in the process of intelligence. There's nothing unique or magical about the human brain that suggests a shred of evidence that it can't be replicated by any Turing complete processing system, or computer. Our minds are an algorithm being run continuously by a messy wet computer in a bone vat connected to a meat suit.

Your sense of continuous perception is the state of a model stored in and processed by the physical, electrical, and chemical configuration of your brain and the laws of physics.

Any methodical definition of understanding arrives at logic and semantic relationships between concepts and information theory. The brain has to be operating as a computer because there is literally nothing else that could be reasonably asserted.

Understanding and consciousness and intelligence and mind are consequences of algorithms, or software. Gpt-3 and similar models are undeniably different types of minds then that of humans, lacking persistent state, online feedback, and a myriad of systems and capabilities. Transformers in their current form are not agi and interact with the world in a radically different way than humans do. They do something that human minds do, however.

Consciousness could be the result of a certain class of algorithms being processed, with a self referential model processed concurrent with external input. Additional systems might be required, but consciousness has to be accomplished using no more than the capabilities offered by the brain, so it's likely to be an emergent consequence of the holistic execution of the cortical algorithm.

Each inference pass might represent a single moment of mind, a disjoint and ephemeral flash of consciousness, unrelated to its prior or future states, deterministically replicable and static.

The Chinese room is a failed argument and we should move on to more interesting things. Brain meat is not magic.