Despite Sam Altman’s claims that we’ve crossed the AI “event horizon,” the reality is that today’s models remain far behind human intelligence in scale, flexibility, efficiency and learning, says Lewis Liu

Sam Altman is currently peddling the “gentle singularity“, claiming we are already “past the event horizon” for AI – at the point where the technology will be infused in every part of our lives and, in his words, “wonders become routine, and then table stakes”. But despite his claims that we’ve crossed this threshold, the math tells a different story.

I want to take a cold, hard look at what this actually means and examine the technical realities behind Altman’s vision, especially given how the rise of AGI (Artificial General Intelligence – AI genuinely smarter than humans) will shape human civilisation in the years to come.

There are obviously two camps: those who believe we are already at or super close to achieving AGI (Altman is the high priest of this movement), and the naysayers who argue that LLMs are nothing more than stochastic parrots with some useful applications (Gary Marcus is an intellectual ringleader for this camp). Some fall in between, depending on definition and context – full disclosure, that’s me.

However, from the perspective of true, genuine conscious AGI, I think we are far, far off. Let’s examine the technical parameters that tell the real story.

Scale Gap

Let’s first talk about the size of these models. The human adult brain is estimated to contain 100-500 trillion synapses, the connections between neurons. The best analogy for LLMs are parameters, where the largest current model, GPT-4, has roughly 1.8 trillion parameters. So just looking at pure size alone, the most modern LLMs are roughly one per cent the size of the adult human brain. For context, the number........

© City A.M.