Deep Learning's Diminishing Returns

Re:Deep Learning's Diminishing Returns by CodeGlitch on Friday September 24, 2021 @05:18PM (#28647959)

> 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.

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Re:Deep Learning's Diminishing Returns by montenegrohugo on Friday September 24, 2021 @05:33PM (#28648089)

GPT-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)

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Re:Deep Learning's Diminishing Returns by CodeGlitch on Friday September 24, 2021 @05:48PM (#28648206)

Thanks 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.

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Re:Deep Learning's Diminishing Returns by naresh_xai on Friday September 24, 2021 @11:28PM (#28650232)

Current 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.

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