kakes,

I suspect we’ll see a lull before the next paradigm shift, but I highly doubt we’ll drop these GPT AIs quite like we’ve dropped those other ones.

We really struck something with these transformer algorithms, and I don’t think it’s a fad by any means.

CorrodedCranium,
@CorrodedCranium@leminal.space avatar

I feel like it’s more inline with a staircase where progress is made followed plateaus.

If for example we can talk to voice assistants in a more human matter and ask follow up questions like “What was that last part you said?” I don’t think there would be much reason to regress

CorrodedCranium,
@CorrodedCranium@leminal.space avatar

In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or even decades later.


There were two major winters approximately 1974–1980 and 1987–2000, and several smaller episodes, including the following:

  • 1966: failure of machine translation
  • 1969: criticism of perceptrons (early, single-layer artificial neural networks)
  • 1971–75: DARPA’s frustration with the Speech Understanding Research program at Carnegie Mellon University
  • 1973: large decrease in AI research in the United Kingdom in response to the Lighthill report
  • 1973–74: DARPA’s cutbacks to academic AI research in general
  • 1987: collapse of the LISP machine market
  • 1988: cancellation of new spending on AI by the Strategic Computing Initiative
  • 1990s: many expert systems were abandoned
  • 1990s: end of the Fifth Generation computer project’s original goals
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