The twitterverse is all verklempt with Anthropic’s latest blog.

The blog, which shows considerable advances in the ability of their systems to write code, is interesting, and make an argument for slowing down AI research that should be considered.

But it should also carry an advisory. Here’s the advisory they forgot to include:

AGI is *harder* than “recursive self improvement” [RSI]

AGI: machine can do anything human can do, autonomously. That has not achieved]

RSI (as used below): AI is a useful coding tool that humans can leverage [achieved]; it’s great at (some) code optimizations

The results in the blog are about RSI, not AGI.

Getting to AGI will require new ideas, not just new code optimizations.

So we don’t need to panic yet.

To some degree, the new Anthropic blog is a bait and switch: Anthropic is trying to strike terror into everyone’s hearts (“full recursive self-improvement also might increase the risks of humans losing control over AI systems”) but all they have really shown is just faster coding — entirely under human control.

A faster coding tool will probably not end the world.

§

More good news. Terrific news, really.

I had written before in an essay called “This one weird trick might cost your retirement fund billions” that the S&P 500 was considering rules changes that would have allowed SpaceX to be included in the S&P 500 faster and with fewer restrictions than ever before, an idea that I thought could prove horrific for retail investors and retirees investing in index funds, given that many (thought not quite all) onlookers find the initial share price to be loopy.

To my great joy S&P did NOT change the rules!

You can click the above to read the full reasoning, but the bottom line is that Musk’s dubiously-priced SpaceX offer will NOT be immediately jammed down index funds without delay.

Instead, SpaceX will have to earn its keep; index funds may still wind up indexing it, but only after the market has had a year to evaluate its worth.

That is great news for fairness. Rejoice!

P.S. Some commentators have interpreted the coding speed up results in the Anthropic blog as showing that AI or deep learning are not hitting a wall. It actually shows the former but not the latter. The progress is real, but this isn’t a victory for pure scaling per se, it’s victory for harnesses and symbolic tools, which are neurosymbolic systems. Pure deep learning has largely hit a wall; neurosymbolic AI is rescuing it. (Put differently and more personally, my own claim was never that AI would hit a wall, or that deep learning should be abandoned, but that we would need to supplement deep learning with neurosymbolic AI, in order to address the limitation of pure scaling. And that’s exactly what happened.)