Date: August 25th, 2026 3:06 PM Author: Avocado metal brethren
for 30+ years, “ai” consisted of borderline useless proofs-of-concept. then, within a span of a year or two, dozens of companies were suddenly able to produce far, far more advanced and effective models. what sudden discovery/shift/dynamic allowed for this sea change?
Date: August 25th, 2026 3:08 PM Author: rose boyish nursing home background story
CERN unlocked portal to other side of black hole hell from Event Horizon for demonic possession of computer shell multiverse seepage. Why do you think it's suddenly "shut down" after all this?
Date: August 29th, 2026 3:05 PM Author: Richard Ames
He simply exited our realm. It's uncanny. He "dies" after spending years more-or-less coordinating world events. Then Covid is ushered in months after his death and then LLMs go full bore.
The crazier part of my pet theory on this is that meetings between Epstein and major world figures are retroactively brought into existence as needed.
"Trump's going to release the Epstein files!" Oh weird, here are a bunch of photos and videos out of fucking nowhere showing them hanging out together.
Date: August 25th, 2026 7:19 PM Author: Stirring codepig
the tokenization process became faster and more workable. think of a 'classic' AI program like Dr. Sbaitso. it didn't really have a 'transformer' process behind its output. it mostly just took inputs and spat out a reply based on a lookup table of pre-programmed responses.
a modern Dr. Sbaitso would use a different system based on abstract representations of user inputs. it wouldn't just use a basic parsing tool to look at the text; the input text would be converted into a series of numerical values/tokens. these tokens would be placed into a mathematical vector space in relation to other tokens, which is why graphics cards are so important to this kind of processing.
modern Dr. Sbaitso would run the token through the vector space and then reconstruct a reply. it's no longer a direct Input(A) --> Program(B) --> Output(C) model. everything flows through the vector space before an output is rendered.
Date: August 26th, 2026 11:09 AM Author: Avocado metal brethren
was the tokenization itself a novel process? otherwise, what drove the suddenness of the change in viability? obviously the capital that’s been poured into the space since has helped, but it seems like there was a fundamental shift that occurred beforehand.
Date: August 26th, 2026 5:39 PM Author: Stirring codepig
in large part, yes. it was mostly theoretical prior to the 2010's. because in order to use the vector model, you have to grab up enormous amounts of data to create the initial tokens and initial 'weights' and models and so on, and that needed a large amount of storage space and computing power.
Date: August 26th, 2026 11:18 AM Author: Hairless Irradiated Double Fault
my understanding of it is that they realized chaining unimaginable amounts of COMPUTE together and brute forcing 'probabilistic' responses was simpler than trying to build a 'thinking/learning' AI.
Date: August 26th, 2026 11:43 AM Author: lake arrogant faggot firefighter windowlicker
this is what the human brain does anyway imo it has great neuron compute but sometimes people still just babble total stream of consciousness hallucinations like AI does exact same thing
Date: August 26th, 2026 6:20 PM Author: Multi-colored pervert
crypto mining shit the bed so Nvidia needed to repurpose their GPUs to keep sales strong. All the early developer support was financed or subsidized by Nvidia