[observationist]

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.

-Irving John Good, 1965

If you want a short, easy way to know what AGI means, it's this: Anything we can do, they can do better. They can do anything better than us.

If we screw it up, everyone dies. Yudkowsky et al are silly, it's not a certain thing, and there's no stopping it at this point, so we should push for and support people and groups who are planning and modeling and preparing for the future in a legitimate way.

[visarga]

John Good's quote is pretty myopic, it assumes machines make better machines based on being "ultraintelligent" instead of learning from environment-action-outcome loop.

It's the difference between "compute is all you need" and "compute+explorative feedback" is all you need. As if science and engineering comes from genius brains not from careful experiments.

[observationist]

There's an implicit assumption there, anything a computer as intelligent as a human does will be exactly what a human would do, only faster. Or more intelligent. If the process is part of the intelligent way of doing things, like the scientific method and careful experimentation, then that's what the ultraintelligent machine will do.

There's no implication that it's going to do it all magically in its head from first principles; it's become very clear in AI that embodiment and interaction with the real world is necessary. It might be practical for a world model at sufficient levels of compute to simulate engineering processes at a sufficient level of resolution that they can do all sorts of first principles simulated physical development and problem solving "in their head", but for the most part, real ultraintelligent development will happen with real world iterations, robots, and research labs doing physical things. They'll just be far more efficient and fast than us meatsacks.

[ACCount37]

At sufficient levels of intelligence, one can increasingly substitute it for the other things.

Intelligence can be the difference between having to build 20 prototypes and building one that works first try, or having to run a series of 50 experiments and nailing it down with 5.

The upper limit of human intelligence doesn't go high enough for something like "a man has designed an entire 5th gen fighter jet in his mind and then made it first try" to be possible. The limits of AI might go higher than that.

[circlefavshape]

> As if science and engineering comes from genius brains not from careful experiments

100% this. How long were humans around before the industrial revolution? Quite a while

[tjoff]

Have you gotten any indication that machines won't have sensors?!

[Eldt]

Maybe ultraintelligence is having an improved environment-action-outcome loop. Maybe that's all intelligence really is

[santadays]

Intelligence seems to boil down to an approximation of reality. The only scientific output is prediction. If we want to know what happens next just wait. If we want to predict what will happen next we build a model. Models only model a subset of reality and therefore can only predict a subset of what will happen. Llms are useful because they are trained to predict human knowledge, token by token.

Intelligence has to have a fitness function, predicting best action for optimal outcome.

Unless we let AI come up with its own goal and let it bash its head against reality to achieve that goal then I’m not sure we’ll ever get to a place where we have an intelligence explosion. Even then the only goal we could give that’s general enough for it to require increasing amounts of intelligence is survival.

But there is something going on right now and I believe it’s an efficiency explosion. Where everything you want to know if right at hand and if it’s not fuguring out how to make it right at hand is getting easier and easier.

[whodidntante]

With AI, as we currently understand it, we may have stumbled upon being able to replicate a part of the layer of our brain that provides the "reason" in humans., and a very specific type of "reason" a that.

All life has intelligence. Anyone who has spent a lot of time with animals, especially a lot of time with a specific animal, knows that they have a sense of self, that they are intelligent, that they have unique personalities, that they enjoy being alive, that they form bonds, that they have desires and wants, that they can be happy, excited, scared, sad. They can react with anger, surprise, gentleness, compassion. They are conscious, like us.

Humans seem to have this extra layer that I will loosely call "reasoning", which has given us an advantage over all other species, and has given some of us an advantage over the majority of the rest of us.

It is truly a scary thing that AI has only this "reasoning", and none of the other characteristics that all animals have.

Kurt Vonnegut's Galapagos and Peter Watts Blindsight have different, but very interesting takes on this concept. One postulates that our reasoning, our "big brains" is going to be our downfall, while the other postulates that reasoning is what will drive evolution and that everything else just causes inefficiencies and will cause our downfall.

[lazystar]

i think theres a paradox here. intelligence needs a judge - if nothing verifies that the optimal outcome was chosen, it's too easy for the intelligence to fall into biased decisions

[scroot]

It's the "no stopping it at this point" that always sticks out to me in these discussions. Why is there no stopping it, exactly? At this juncture these systems require massive physical infrastructure and loads of energy. It's possible to shut it all down. What's lacking is the political will.

[mc32]

Should then the powers that are developing AGI enter an analogue to the SALT treaties but this time governing AGI do things don’t go off the rails?

[SecretDreams]

> support people and groups who are planning and modeling and preparing for the future in a legitimate way.

Who is doing that right now, exactly? And how can we take their tech and turn it into the next profitable phone app?

[dylan604]

The "legitimate way" is nothing short of weasel words. Who defines what is legitimate. The doomers that are prepping for the future by building stockpiles of food/water/weapons being stored in bunkers/shelters they have built would say this is exactly what they are doing. Yet, these people are often panned as being a little unhinged. If we're having a conversation about tech destroying humanity, then planning a way to survive without tech seems like a legitimate concept.

[mathgradthrow]

never let philosophers do math

[mrandish]

> Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man

The things this definition misses: First, 'intelligence' is a poorly defined and overly broad term. Second, machine intelligence is profoundly different than biological intelligence. Third, “surpassing humans” is not a single threshold event because machine and human intelligence are not only shaped differently, they're highly non-linear. LLMs are a particular class of possible machine intelligences which can be much more intelligent than humans on some dimensions and much less intelligent on others. Some of the gaps can be solved by scaling and brilliant engineering but others are fundamental to the nature of LLMs.

> an ultraintelligent machine could design even better machines

There is a huge leap between "surpass all the intellectual activities of any man" and "invent extraordinary breakthroughs and then reliably repeat that feat in a sequential, directed fashion in the exact way required to enable sustained iteration of substantial self-improvement across infinite generations in a runaway positive feedback loop". That's an ability no human or collective has ever come close to demonstrating even once, much less repeatedly. (hint: the hardest parts are "reliably repeat", "extraordinary breakthroughs" and "directed fashion"). A key, yet monumental, subtlety is that the self- improvements must not only be sustained and substantial but also exponentially amplify the self-improvement function itself by discovering novel breakthroughs which build coherently on one other - over and over and over.

The key unknown of the 'Foom Hypothesis' is categorical. What kind of 'difficult feat' this is? There are difficult feats humans haven't demonstrated like nuclear fusion, but in that example we at least have evidence from stellar fusion that it's possible. Then there are difficult feats like room-temp superconductors, which are not known to be possible but aren't ruled out. The 'Foom Hypothesis' is a third category of 'hard' which is conceptually coherent but could be physically blocked by asymptotic barriers, like faster-than-light travel under relativity.

Assuming Foom is like fusion - just a challenging engineering and scaling problem - is a category error. In reality, Foom requires superlinear, recursively amplifying cognitive returns—and we have no empirical evidence that such returns can exist for artificial or biological intelligences. The only prior we have for open‑ended intelligence improvement is biological evolution which shows extremely slow and unreliable sublinear returns at best. And even if unbounded self‑improvement is physically possible, it may be practically unachievable due to asymptotic barriers in the same way approaching light speed requires exponentially more energy.

[LeifCarrotson]

"There's no stopping it at this point" - Sure there is, if a handful of enormous datacenters pull the very large plugs (or if their shaky finances collapse), the dubiously intelligent machines will be turned off. They're not ultraintelligent yet.

Stopping it merely requires convincing a relatively small number of people to act morally rather than greedily. Maybe you think that's impossible because those particular people are sociopathic narcissists who control all the major platforms where a movement like this would typically be organized and where most people form their opinions, but we're not yet fighting the Matrix or the Terminator or grey goo, we're fighting a handful of billionaires.

[observationist]

I'm not saying it's technically impossible, I'm saying that in the real world, it's not going to stop. Nobody is going to stop it. A significant number of people don't want it to stop. A minority of people are in the "stop AI" camp, and the ones with the money and power are on the other side.

It's an arms race replete with tribalism and the quest for power and taps into everything primal at the root of human behavior. There's no stopping it, and thinking that outcome can happen is foolish; you shouldn't base any plans or hopes for the future on the condition that the whole world decides AGI isn't going to happen and chooses another course. Humans don't operate that way, that would create an instant winner-takes-all arms race, whereas at least with the current scenario, you end up with a multipolar rough level of equivalence year over year.

[goodmythical]

right, because turning off any number of data centers is going to do anything at all but create massive pressure on researching the efficiency and effectiveness of the models.

There are already designs that do not require massive data centers (or even a particularly good smart phone) to outperform average humans in average tasks.

All you'd accomplish by hobbling the data centers is slow the growth of sloppy models that do vastly more compute than is actually required and encourage the growth of models that travel rather directly from problem to solution.

And, now that I'm typing about it, consider this: The largest computational projects ever in the history of the world did not occur in 1/2/5/10 data centers. Modern projects occur across a vast and growing number of smaller data centers. Shit, a large portion of Netflix and Youtube edge clusters are just a rack or a few racks installed in a pre-existing infrastructure.

I know that the current design of AI focusses on raw time to token and time to response, but consider an AGI that doesn't need to think quickly because it's everywhere all at once. Scrappy botnets often clobber large sophisticated networks. WHy couldn't that be true of a distributed AI especially now that we know that larger models can train cheaper models? A single central model on a few racks could discover truths and roll out intelligence updates to it's end nodes that do the raw processing. This is actually even more realistic for a dystopia. Even the single evil AI in the one data center is going to develop viral infection to control resources that it would not typically have access to and thereby increase it's power beyond it's own existing original physical infrastructure.

quick edit to add: At it's peak Folding@Home was utilizing 2.4 EXAflops worth of silicon. At that moment that one single distributed computational project had more compute than easily the top 100 data centers at the time. Let that sink in: The first exa-scale compute was achieved with smartphones, PS3s, and clunky old HP laptops; not a "hyperscaler"

[trvz]

Open models barely any worse than SOTA exist, and so does consumer-ish hardware able to run them. The genie’s out, the bottle broken.

[slibhb]

Do you really think AI companies/researchers are motivated by greed? It doesn't seem that way to me at all.

Stopping AI would be immoral; it has the potential to supercharge technology and productivity, which would massively benefit humanity. Yes there are risks, which have to be managed.