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"Over the last year, Doug and I tried to write a long, complex paper that we never got to finish. Cyc was both awesome in its scope, and unwieldy in its implementation. The biggest problem with Cyc from an academic perspective is that it’s proprietary.
To help more people understand it, I tried to bring out of him what lessons he learned from Cyc, for a future generation of researchers to use. Why did it work as well as it did when it did, why did fail when it did, what was hard to implement, and what did he wish that he had done differently? ...
...One of his last emails to me, about six weeks ago, was an entreaty to get the paper out ASAP; on July 31, after a nerve-wracking false-start, it came out, on arXiv, Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyc (https://arxiv.org/ftp/arxiv/papers/2308/2308.04445.pdf).
The brief article is simultaneously a review of what Cyc tried to do, an encapsulation of what we should expect from genuine artificial intelligence, and a call for reconciliation between the deep symbolic tradition that he worked in with modern Large Language Models."
> my content would probably just add noise to the internet
Maybe, but there is worse noise out there for sure. :) Anyhow, some unsolicited advice from me: don't replay this quote to yourself any more than necessary; it isn't exactly a motivational mantra masterpiece. Share what you think is important.
Why? Even small, "improbable" improvements to knowledge can to matter. Given enough of them, statistically speaking, we can move the needle. Yeah, and we need to be able to find the relevant stuff; a big problem in of itself.