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From Wikipedia (https://en.wikipedia.org/wiki/Cyc#Criticisms https://en.wikipedia.org/wiki/Cyc#Criticisms) > ... A similar sentiment was expressed by Marvin Mi
by airstrike 5y ago
From Wikipedia (https://en.wikipedia.org/wiki/Cyc#Criticisms https://en.wikipedia.org/wiki/Cyc#Criticisms)
> ... A similar sentiment was expressed by Marvin Minsky: "Unfortunately, the strategies most popular among AI researchers in the 1980s have come to a dead end," said Minsky. So-called “expert systems,” which emulated human expertise within tightly defined subject areas like law and medicine, could match users’ queries to relevant diagnoses, papers and abstracts, yet they could not learn concepts that most children know by the time they are 3 years old. “For each different kind of problem,” said Minsky, “the construction of expert systems had to start all over again, because they didn’t accumulate common-sense knowledge.” Only one researcher has committed himself to the colossal task of building a comprehensive common-sense reasoning system, according to Minsky. Douglas Lenat, through his Cyc project, has directed the line-by-line entry of more than 1 million rules into a commonsense knowledge base."
- ypcx 5y agoAnd then, GPT-3 came along and rendered Cyc a wasted effort.
- goatlover 5y agoCyc was trying to encode common knowledge about the world in a bunch of rules. That goes well beyond what GPT-3 does with text.
- ypcx 5y agoGPT-3 learns these rules by itself.
- johnthescott 5y agocan you automate your fate with gpt-3? that is where the money lives. will sublime conclusions made by GPT-3 EVER be trusted if the reasoning to its conclusion is not understood by a human? perhaps the gestalt of gpt3 implies a meta gpt3 that could derive human grokkable explains of its "dumber" self. or maybe not.
- naresh_xai 5y agoCurrent set of tools in explainable AI do allow deep neural nets to tell why they gave the response that they did to a certain extent. Contact me if you want to see it applied to text based DL models, time series based DL models or Image based DL models.
- Peritract 5y agoNo it doesn't. It generates text that looks like it has learnt common sense rules, which is both subtly and importantly different.
- ypcx 5y agoHow would you define "common sense rules"?
- Peritract 5y agoThis Wikipedia article is a good start if you're curious: https://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) https://en.wikipedia.org/wiki/Commonsense_knowledge_(artific...
- ypcx 5y agoAmazing how our own brain can delude us by creating a feeling that we understand something because (apparently) we have produced a clear definition of it. Just a hint - each of these "facts" or "rules" mean slightly something else depending on the context they are used in. This context is not hard-encodable because it slightly mutates with every new information learned or forgotten.
- canjobear 5y agoI bet you could use GPT-3 to extend the list of rules.
- CodeGlitch 5y ago> And then, GPT-3 came along and rendered Cyc a wasted effort. I'm yet to see GPT-3 do anything commercially important? Cyc on the other hand seems to have been used in a number of sectors. Not to downplay GPT-3 - it's cool tech that produces cool demos - Cyc just seems more like a tool rather than a toy.
- montenegrohugo 5y agoGPT-3 has been used in a ton of commercially important applications. To name a few: - GitHub CoPilot (transformative imo) - Markcopy.ai, jenni.ai, etc.... Tons of content generation and SEO tools startups - AI Dungeon and such - Plenty of chatbots - It's super useful for all kinds of classification tasks too (as are all transformer models)
- CodeGlitch 5y agoThanks for the response, I'm not familiar with Markcopy.ai, jenni.ai, but the others are "toys" if we're being honest (although as I said - very cool toys). You wouldn't want to use GPT-3 to recommend drugs for a condition you feed it...would you? As far as I understand, this is the kind of problem Cyc is trying to solve with it's domain-specific rules. edit: Cyc can also tell you why it gave the response it did - something that deep nets cannot do. This is important in many fields, otherwise you cannot trust any response it produces.
- naresh_xai 5y agoCurrent set of tools in explainable AI do allow deep neural nets to tell why they gave the response that they did to a certain extent. Contact me if you want to see it applied to text based DL models, time series based DL models or Image based DL models.