zlacker

>>todsac+(OP)
I would argue that Lenat was at least directionally correct in understanding that sheer volume of data (in Cyc's case, rules and facts) was the key in eventually achieving useful intelligence. I have to confess that I once criticized the Cyc project for creating an ever-larger pile of sh*t and expecting a pony to emerge, but that's sort of what has happened with LLMs.

>>vannev+14
I suspect at some point the pendulum will again swing back the other way and symbolic approaches will have some kind of breakthrough and become trendy again. And, I bet it will likely have something to do with accelerating these systems with hardware, much like GPUs have done for neural networks, in order to crunch really large quantities of facts

>>cmrdpo+G8
The Bitter Lesson has a few things to say about this.

http://www.incompleteideas.net/IncIdeas/BitterLesson.html

>>luma+Wf
Imho, this is wrong. Even independent of access to vast amounts of compute, symbolic methods seem to consistently underperform statistical/numerical ones across a wide variety of domains. I can't help but think that there's more to it than just brute force.

>>bcoate+CO
I've lost count how many times I've written the same words in this thread but: SAT Solving, Automated Theorem Proving, Program Verification and Model Checking, Planning and Scheduling. These are not domains where symbolic methods "consistently underperform" anything.

You guys really need to look into what's been going on in classical AI in the last 20-30 years. There are two large conferences that are mainly about symbolic AI, IJCAI and AAAI. Then there's all the individual conferences on the above sub-fields, like the International Conference on Automated Planning and Scheduling (ICAPS). Don't expect to hear about symbolic AI on social media or press releases from Alpha and Meta, but there's plenty of material online if you're interested.