Which human? Helen Keller's understanding of text is going to be radically different from your average Red Fish, Blue Fish reading precocious toddler, and they're going to be radically different from a medieval monk reading scriptio continua, and all in turn will be different from the average Japanese reader, used to Kanji in different orientations.

What does performance mean? With regards to humans, its hard to quantify cognition and thinking. Even measuring neural activity is incredibly difficult, and depending on what type of brain from the above list of humans you are sampling from, the same level of consideration and understanding might be taking place, but with radically different levels of cortical activation in different areas of the brain.

I don't do this to be pedantic, but to show that, much like the word love, or the experience of seeing white clouds on a blue sky, the words and ideas we use to communicate in the space of cognition and understanding are extremely broad, and not terribly useful in a technical or engineering context.

There are demonstrations of synthetic hippocampus prosthetics in animals that provide memory of places and things that apparently are equivalent to a biological hippocampus - experiments with rats and other small animals have allowed pretty convincing evidence that what the brain is doing is substrate independent and neuronal functional equivalence is sufficient to repair and augment function.

Things like NeuraLink and cochlear implants give brains the capacity to perform actions and accept normal input signals. Labs like Numenta have done great work identifying pieces and structures of algorithms that human brains are actually using in the course of human cognition.

Once we have this, we'll have an objective measure of what human level AI means, for the algorithms that actually underpin human intelligence.

Without those algorithms, or a rigorous way of approximating them, we are left with speculating about things like min and max range of processing power of a human brain, studies involving input and output measurements of human capabilities, and so on.

The minimum FLOPS needed to emulate a hypothetical human level brain emulation AGI could have run on a desktop in the early aughts, and the maximum, with precise individual neuronal simulation, is a few orders of magnitude away - 4 or 5 petaflops should be able to emulate a brain at the cellular level, with reasonably precise electrochemical simulation.

Until we have a better understanding of what cognition actually is we're left with rough measures of human performance, with tests that are inevitably cheated and gamed and goodharted.

We're at superhuman levels of text output - you can specify things like {Joe Biden's last state of the union address} + "give me an article in the style of Hunter S. Thompson that lampoons Biden over his SOTU address" and in a single pass, get something that could plausibly have been written by Hunter S. Thompson. With multiple passes, a good editing process, and a few hours, you could arguably produce text that is all but indistinguishable from high quality human output, in much less time than it would take for any human to actually produce it.

The same applies to art - your imagination is your limit. There are mode collapses, weird artifacts, and other issues, but by and large, any human on the planet can now use software to bring a visual idea or vivid imagination to life. Some of the most fun I've had with generative AI has been producing fantastic unicorns with my 4 year old niece.

So baseline human level performance might mean one masterpiece painting in a lifetime - but give someone with the mind of a Monet or Da Vinci or Michelangelo the tools we have at hand, and what could they produce? I think it's unarguable that they would have found levels of nuance and excellence in the use of these tools that are going to be inaccessible to other people, and over the coming years we are going to see new levels of artistic excellence come about as people learn to use these new tools in new ways.

As human tool use gets better, so does human capacity. If you look at an uncivilized human, without language, having survived in isolation, raised among animals, they may never be able to acquire a language. Feral humans have the same basic capacity, but their cognition is going to be wildly different than a modern Western human. LLMs have superior understanding to humans in that context, with the capacity to perform basic reasoning in the context of language that is structurally unavailable to a feral human.

I think we're already basically at superhuman level for most simple tasks involving text, and at least some very hard tasks. We're not at general level AI yet, since there are higher level meta-cognition domains that seem unavailable to LLMs, and multimodal systems are more frankenstein mashups of discrete models than a unified incorporation of multiple modalities, but at some point in the seemingly near future, we're going to be faced with software that can basically do anything and everything any and every human has ever done.

We might not be able to quantify exactly what "human level" means for now, but we can see the trajectory of where things are going, and the line tracking AI capabilities seems pretty clearly on course for overtaking humans. It's a good time to be alive.