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.
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.