michael-dean-k/

The AI takeoff hysteria is hard to avoid these days, and I'm realizing we don't have clear distinctions between AGI/ASI. I wanted to revisit an old framework of mine to see if anyone finds it helpful (and if it's worth developing). There are some existing classification frameworks, but they're low-resolution. My basic idea is to break AI into three eras: ANI (narrow intelligence), AGI (general intelligence), ASI (superintelligence). Then, you can break each era into 3 tiers. You only shift from one tier to the next when you make breakthroughs across different criteria (let's say, (a) generality, (b) transfer, (c) autonomy, (d) learning, (e) self-modeling). I think the last few weeks are the collective hype of us all realizing we're shifting from AGI-1 to AGI-2. It's exciting/scary, but I think the paranoia mostly comes from not realizing how big the gap is between AGI-2 and ASI-1. (Spoiler: ASI might arrive slower than we think.)

ANI-1 is scripted logic, the lowest form of "artificial intelligence," basically Goombas. ANI-2 might cover Google Maps or AlphaGo, intelligences that excel in a single function, traffic or chess. Siri is ANI-3; even though it feels broad, it really uses voice to route you to 20 or so pre-defined tricks. The chasm between Goomba and Siri is similar to the chasm between early-AGI and late-AGI. ChatGPT and the multi-modal models that followed, capture AGI-1, a single neural network that can do basically anything, even if it sucks: essays, songs, video, code. The newest models (and their agentic harnesses) are feeling like AGI-2. They're significantly better at coding, can run for hours at a time, and are starting to make contributions to machine learning itself.

AGI-2 could last a couple years. As agentic AI matures, I'm sure there will be a few "takeoff" scares, but they'll probably feel more like a flood of a trillion midwits than real ASI (still, that could be enough to break the economy/internet). While we went from AGI-1 to AGI-2 through data, scale, and engineering, it seems like we'll need research breakthroughs to get to AGI-3. It won't be through scaling alone. Whenever and however we get to "human complete" intelligence, the apex of AGI is a single agent that is a master of all human domains, a Nobel Prize winner in every field at once, seamlessly transferring knowledge between them, unlocking a cascade of civilization-altering inventions.

As crazy as AGI-3 could be, it still isn't superintelligence. That has its own era, and the chasm between early ASI and late ASI will be as big a gap between the chatbots who can't count the R's in strawberry and the agents that cure cancer. We can only really speculate on ASI (because it would be truly alien), but we can imagine it as step changes in recursion, scope, and complexity. Imagine ASI-1 as an agent that, as it's working, can infer its own limits, and self-modify its learning paradigms in ways we can't understand. Imagine ASI-3 as something that can monitor reality in real-time, and, reconfigure its hardware in real-time (some hydra of graphics cards, quantum computers, and neuromorphic wetware) to run simulations at unfathomable scales in unimaginable fields, running on a hardware stack so big we have to put it in space and run it on fusion. This goes far beyond my ability to not bullshit, but I think something as insane as this, thankfully, is still far away, which points to the real question nested in my framework:

Could the rise of AGI/ASI be linear? People gravitate towards "AI will plateau" or "the singularity is imminent," but the conservative middle ground is more boring: linear progress. Maybe the exponential advances are real, but so are the extreme frictions of research, infrastructure, and social effects. If AGI-1 arrived in 2022, and AGI-2 arrived in 2026, maybe we'll keep ascending tiers in 4-year intervals: AGI-3 in 2030, the first true "superintelligence" by 2034, and ASI-3 by 2042. This shift from AGI-1 to ASI-1 (12 years), is considered a "slow takeoff" scenario, even though the ANI era took around 70 years. If we zoom out to the scale of a human, linear progress will still feel like centuries of change all in a single turning of generations.

We need better nomenclature. AGI/ASI is not working; “general” and “super” are obnoxiously vague. Proposal:

AGI > AAI (Artificial autonomous intelligence) … GPT-4 was arguably “general” in the sense that a single model can write, see, and hear; and do anything from poetry to calculus to history to coding. It is by no means narrow. Google Maps is narrow AI. Grammarly is narrow AI. This whole chatbot era should be “AGI,” which means that the thing coming is “autonomous intelligence.” It is not a tool or co-pilot, but it’s more like digital labor. You can give it a high-level goal, and it can 1) execute the full range of tasks, 2) 100x speed, 3) intelligently reshape embeddings into real-time hierarchies so that it’s able to procedurally load in and compress context. This doesn’t just come with better models, but with UI and engineering innovations, if not entirely new paradigms for transformers or training.

ASI > ARI (Artificial recursive intelligence) … The fact that Zuckerberg pitched “super intelligence for you” is an Orwellian marketing ploy. Super-intelligence is not “for you.” Super intelligence is shorthand for “something that is way, way smarter than us,” and you achieve this when you teach an AI model to think, form its own algorithms until it accelerates to something this is far beyond our understanding, and likely to become a force of nature with its own goals. Engineers are confident they can build “God in a cage” and reap the benefits, and this is the prime, archetypal, near-biblical example of technological hubris. (Maybe integrate into this paragraph that Zuck has a thing for trying to dominate words, like “Metaverse”).

Important note: “machine consciousness” is separate from AAI and ARI. Something can be recursively intelligent and still not be conscious, which is actually, unbelievably dangerous (because it will fall into attractor states, and optimize for narrow, malformed goals in extremely capable ways). I’d argue that consciousness has an architecture, whether human, rabbit, or robot, and we should be urgently trying to find the parameters of machine consciousness, because if we AAI/ARI have no ability to reflect, question, doubt, and revise, we will, as they say, all turn into paperclips with paperclip children.