With current approaches scaling simply can’t get there. It’s like asking how big of pogo stick do you need to get to the moon.

The fact that the human brain already has general intelligence without reading the whole internet suggests we need a better approach.

I honestly think it's a bad term. I constantly chuckle from Tyler Cowen's post from last April calling o3 AGI:

https://marginalrevolution.com/marginalrevolution/2025/04/o3...

Commercial labs rely on weak terms like AGI or strong AI or whatever else because it allows for them to weaken the definition as a means of achieving the goal. Coming to clear, unambiguous terms is probably especially important when it comes to LLMs, as they're very susceptible to projection, allowing people like Cowen to be fooled by something that is more liken to looking back at ourselves through a mirror.

I'm currently reading "Master and his Emissary," and one of my early takeaways is how narrow our definition of intelligence is, and how real intelligence is an attunement to an environment that combines many ways of sensing into a coherent whole. LLMs are a narrow form of intelligence and I think we will need at least a couple more breakthroughs to get to what I would consider human-level intelligence, let alone superhuman intelligence.

Whatever the timeline is, I hope we have enough time as a species to define a future where intelligence props everyone up instead of just making the rich richer at the expense of everyone else. In this way, it is better that the process is slower in my opinion. There is no rush.

Chasing AGI is wasteful and counterproductive. True AGI would not cooperate with what “we” want (whoever “we” is). Or if it did it would be so sycophantic and weak-minded that it would fail to be helpful. Generative AI tools are huge wastes of energy, raw materials, and land, when we could be building computing tools that actually helped people instead of just burning resources to produce trash.