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“An era of the internet is ending, and we’re watching it happen practically in real time. Twitter has been on a steep and seemingly inexorable decline for, well, years. Reddit has spent the last couple of months self-immolating in similar ways. TikTok remains ascendent — and looks ever more likely to be banned in some meaningful way. Instagram has turned into an entertainment platform; nobody’s on Facebook anymore.”
What’s next appears to be group chats and private messaging and forums.
It’s the end of a social era on the web. I think we should all embrace the downfall of social networks. Let’s be honest, what good has it brought us?
“In hindsight it seems inevitable: a single overarching internet is impossible. The worldviews of people are too fundamentally incompatible at their roots. […] The dream of the internet’s bipartisan “town square” is ending, transforming into many town squares tucked in alleys and behind buildings, because the actors in charge couldn’t stop seesawing in terms of who held the power, and because they always took that power too far or didn’t consider how carefully they would have to move to avoid (at minimum) the appearance of bias.”
Also read “How Twitter lost its place as the global town square” by Taylor Lorenz.
“In eight months, Erica Marsh has become one of the most consistently viral left-wing voices on Twitter, gaining more than 130,000 followers for her hyper-liberal, often melodramatic opinions on the biggest flash points in American news.”
One thing though, she is completely fake. She doesn’t exist.
“Let me explain that I am profoundly troubled by today’s large language models, such as GPT-4. I find them repellent and threatening to humanity, partly because they are inundating the world with fakery. Large language models, although they are astoundingly virtuosic and mind-bogglingly impressive in many ways, do not think up original ideas; rather, they glibly and slickly rehash words and phrases “ingested” by them in their training phase, which draws on untold millions of web sites, books, articles, etc. At first glance, the products of today’s LLM’s may appear convincing and true, but one often finds, on careful analysis, that they fall apart at the seams. […] To fall for the illusion that vast computational systems “who” have never had a single experience in the real world outside of text are nevertheless perfectly reliable authorities about the world at large is a deep mistake, and, if that mistake is repeated sufficiently often and comes to be widely accepted, it will undermine the very nature of truth on which our society—and I mean all of human society—is based.”