There were dozens of 20th Century ideological movements which developed their own forms of "Newspeak" in their own native languages. Largely, natural human dialog between native speakers and between those opposed to the prevailing regime recoils violently at stilted, official, or just "uncool" usages in daily vernacular. So I wouldn't be too surprised to see a sharp downtick in the popular use of any word that becomes subject to an LLM's positive-feedback loop.

Far from saying the pool of language is now polluted, I think we now have a great data set to begin to discern authentic from inauthentic human language. Although sure, people on the fringes could get caught in a false positive for being bots, like you or I.

The biggest LLM of them all is the daily driver of all new linguistic innovation: Human society, in all its daily interactions. The quintillions of daily phrases exchanged and forever mutating around the globe vastly eclipses anything any hardware could ever emulate given the current energy constraints. Software LLMs are just a state machine stuck in a moment in time. At best they will always lag, the way Stalinist language lagged years behind rhe patois of average Russians.

If there is one distinctly human trait, it's sniffing out anyone who sounds suspiciously inauthentic. (Sadly, it's also the trait that leads to every kind of conspiracy theorizing imaginable; but this too probably confers in some cases an evolutionary advantage).

humans also lag humans, the future may already be spoken, but the slang is not evenly memed out yet.

Really insightful.

I'm a little more cautious though. I think GPT will be way more integrated, simply because it's useful. Stalinist language was artificial, in the sense that it was basically imposed on you from outside for no good reason. When you wanted to get real stuff done (either talking to close friends, being productive with colleagues, etc) you wouldn't use socialist newspeak because it got in the way. GPT will be imposed by the outside world, but it's actually a useful thing to be able to converse with a language model; you'll do it every day at work, when buying things, when using your phone/PC.

And also, unlike in USSR times, so much of our communication is online and visible. It would not surprise me if we develop a model that can train continuously on the firehose. Text is small. Data rate of every person on earth speaking simultaneously:

- 150 words per minute spoken

- 150 words × (5 characters/word + 1 space) = 150 × 6 = 900 characters per minute

- 1 byte per char = 900 bytes/min = 15 bytes/sec

- 15 bytes / sec * 8,000,000,000 people speaking continuously = 120 gigabytes/second

That's a lot but it's not even the bandwidth of a single consumer GPU.