Three Observations

> Moore waited at least five years [1] before deriving his law.

OpenAI has been around since 2015. Even if we give them four years to ramp up, that's still five years worth of data. If you're referring to the example he gave of token cost, that could just be him pulling two points off his data set to serve as an example. I don't know that's the case, of course, but I don't see anything in his text that contradicts the point.

> I don't think that it makes much sense to compare commercial pricing schemes to technical advancements.

How about Kurzweil's plot [1]?

[1] https://scx2.b-cdn.net/gfx/news/hires/2011/kurzweilfig.1.jpg

The "10x every 12 months" is pure salesman from sama. An engineer wouldn't do these extrapolations from little data in good faith.

Yeah that was my first thought, don’t sully the name of Gordon Moore with this.

This sounds more like an insight into how things are working at open ai than anything else. And I’m not sure if deep seek and others are going to follow his nice rules.

More generally, transistors are a technical phenomenon…they are either smaller (and work) or don’t. The thing I really don’t feel enough folks appreciate about AGI is it’s a social phenomenon - not in the making of it but in the pragmatic reality of it.

To a sufficient number of folks the current version is AGI, I see students every day trust it more than themselves. To bosses it also might be, if it’s more intelligent than you average employee than that’s sufficiently general intelligence to replace them. So far, I’ve really tried but don’t beyond generating the most basic outline I have yet to find a model that helps with my work, so it’s not intelligent for me.

I’m aware of the benchmarks but they don’t matter outside of places like HN. intelligence is and, likely, will always be social before it is technical and that makes these laws..not useful?

> I don't see why we should trust OpenAI's promises now, when they've broken promises in the past.

I don't see what "our" trust has to do with anything. Perhaps you're an investor in OpenAI and your trust matters to OpenAI and its plans? But for the rest of us, our trust doesn't matter. It would be like me saying, "I don't see why we should trust Saudi Aramco."

First, it requires exponential investment because

> 1. The intelligence of an AI model roughly equals the log of the resources used to train and run it.

Incremental improvements in intelligence require exponentially more resources. Only once that step is achieved can costs be reduced.

Second, intelligence is not the same as education. Education is specialized, intelligence is general. Every modern convenience around you is the result of intelligence.

"cost to use" != "cost to train"

Elsewhere he says that model intelligence is determined by the log of the resources used to train it, and this relationship has been constant for many orders of magnitude.

The implication is that it takes exponentially increasing investment to achieve a linear increase in intelligence.

Exponentially increasing costs sound like a bad thing.

But then he says the linear increase in intelligence generates exponentially increasing economic benefits.

Those exponentially increasing benefits sounds like they might justify the exponentially increasing costs.

The costs are coming down fast because of the investment and would not happen independently of the investment. The same reason for Moore's law can be generalized as the learning/experience curve. You could make the argument that the demand for AI has a higher growth rate than the learning rate ex. if AI becomes 10x more cost efficient and results in demand growing 100x, you would also need to follow with an exponential growth in inference investment.

You could also make an argument that the bulk of college degrees are not economically useful. The demand for certain kinds of education and knowledge is certainly finite - but the demand ceiling for general intelligence seems much much higher, and appears to be limited only by the cost of hiring ever smarter people.

Same. I think the tools have gotten a little better with agent mode and all that but it still doesn't get anything even slightly complicated for an API it hasn't seen before. Like it hasn't gotten more intelligent since maybe Gpt 3.5.

I quite like them as somebody who has a huge problem with onset procrastination. I immediately ask them to write something and criticize them and write it myself because whatever it comes up with is so damn stupid.

Even though I have a reasonable intuition and understanding of how a LLM works, I am still awe-struck each and every time I use one. The fact that I have a junior developer at my convenience is a huge efficiency gain. I’ve been able to automate the rudimentary elements and focus my time on the stuff that counts.

In terms of solutions: UBI is frequently proposed. Depending on the degree to which AI and automation obsoletes human labor and increases, UBI could become arbitrarily redistributive. Increased output would keep inflation at bay, and the reduced incentive to work would be mitigated by the fact that there almost wouldn't need to be any incentives remaining for wealth creation.

Such an AGI scenario might also raise some old questions about the degree to which wealth disparity-as-an-incentive-for-success remains useful and justifiable. One wonders how Altman would receive this proposal.

Oh there have been LOADS over the years. The old ones say this is going to happen, the new ones say this is happening, the new new ones say oh btw our measurement systems for labour market and society during this change period are probably not accurate so we need new ones ASAP.

https://www.mckinsey.com/~/media/mckinsey/industries/public%...

https://www.oecd.org/en/publications/the-risk-of-automation-...

https://news.mit.edu/2019/work-future-report-technology-jobs...

https://arxiv.org/pdf/2306.12001

https://institute.global/insights/economic-prosperity/the-im...

https://ipc.mit.edu/research/work-of-the-future/

"AI will replace many workers" feels eerily similar to the message of the early 2000s in the US: "Tech/Knowledge workers from low cost locations will replace many workers from high cost locations." In truth, the high cost locations continued to grow, side-by-side, with low cost locations. To be clear: I am not speculating on the why, rather only sharing what I see.

I firmly believe AI will become heavily taxed and regulated.

It would be foolish to ban it, but equally foolish to allow it to replace a large percentage of your country’s workforce. It would completely destabilize the economy and society as a whole.

AI can do a lot of great things for humanity. Putting vast amounts of people out of a job is not one of those things.

There needs to be more smart people talking about and studying what the future realistically looks like.

Won't there be more jobs for people maintaining and servicing the data centers? Amongst all the other AI infrastructure?

Plenty of jobs that are decades away from automation. Will a robot climb on your roof to fix your A/C or repair your plumbing soon? Probably not. Now I'm sure some enterprising startup is trying, but seriously, it's not close.

> But muh singularity!

Sure, any day now Optimus will become sentient and replace home builders... or not.

So yeah, probably less lawyers(yay), software techs, accountants, etc. But those dollars will flow to people taking vacations, renovating their homes, eating fancy food, etc. Who knows what the net effect will be in the long term?

[dead]

It feels like every major lab is saying the same thing:

https://darioamodei.com/machines-of-loving-grace https://www.wsj.com/video/events/the-race-for-true-ai-at-goo...

Even folks _leaving_ OpenAI, who have no incentive to drive hype, are saying that we're very close to AGI. https://x.com/sjgadler/status/1883928200029602236

Even folks like Yoshua Benjio, Hinton are saying we're close to it. The models keep getting better at an exponential.

How much evidence does one need to dispel the "this is OpenAI/sama hype" argument?

The article is written for journalist (and investor). See the footnote.

"assume the sale" is the marketing tactic. ie, in every pitch, project that agi (whatever that means) is here, and is a persistent threat.

unfortunately, ai is not search or social. there are no network-effects here. so, get-big-fast is not going to work. and slowly the masses start waking up and asking what the hell is this good for except as a fancy auto-complete.

The article you linked is from Sept '24 and points to the ARC-AGI test as "evidence" that we're not getting close.

We're in Feb '25. ARC-AGI (at least the version they're referencing) already has been solved by AI at above average human level.

>everything points to incremental progress with signs of diminishing returns.

Seems like everything in just Dec '24/ Jan '25 points the other way. These models are already helping PhDs in novel research, they're already getting super human at coding (yes yes, they're not perfect and I'm sure someone on HN has this weird coding job that AI can't replace yet and they're very excited to shit over AI), but they've already replaced a lot of real software dev jobs.

Also aren't you contradicting yourself?

> everything points to incremental progress with signs of diminishing returns

> corporation replacing employees with AI

If we have incremental progress, how are corporations going to replace employees with AI?

> Altman thinks benefits will naturally trickle down when everything points to corporation replacing employees with AI to boost their profit margins.

That's not what he is saying. He is saying that this investment in AI will yield incredible returns and power. The investor will dominate the next decade(s) and thus you should invest. Of course, he has to say it in a careful way not to alarm politically correct people. But, in essence, he is trying to create investor FOMO to drive his next round.

He explicitly stated progress is logarithmic.

> 1. The intelligence of an AI model roughly equals the log of the resources used to train and run it.

This is a great point. Life is tough because we are all competing in a game. Tweaking the rules of the game so that each basket is worth more points doesn’t make the game easier for any player.

From Henry George:

> Now, to produce wealth, two things are required: labor and land. Therefore, the effect of labor-saving improvements will be to extend the demand for land. So the primary effect of labor-saving improvements is to increase the power of labor. But the secondary effect is to extend the margin of production. And the end result is to increase rent.

> This shows that effects attributed to population are really due to technological progress. It also explains the otherwise perplexing fact that laborsaving machinery fails to benefit workers

> Anyway, AI/AGI will not yield economic liberation for the masses. We already produce more than enough for economic liberation all over the world, many times over. It hasn't happened.

In Marshall Sahlins's Stone Age Economics, he studies work time of hunter gatherer tribes in Africa, Papua New Guinea, the Amazon etc. They often less work less than 40 hours a week. The hunter gatherer painting in caves in Chauvet seemed to have leisure time. Less hours than some fresh college grad pounding out C++ or C# for Electronic Arts any how.

The past 50 years has seen the hourly wage stay flat while the profit workers create is sucked up by the heirs.

Paying for four years if college to get a CS degree, then studying Leetcode, interning, working cheap as an associate/junior used to be seen as a good path, but obviously since late 2022 this has stagnated for most.

Can you define what you mean by economic liberation? For most of economic history, I think the definition would have been freedom from famine and slavery and I think on both counts we've been wildly successful. Both basically only occur in failed states, where there's either no government at all (Somalia, Sudan, parts of Iraq and Syria) or the government is an authoritarian dictatorship (North Korea, Venezuela)

I ask, because I think you might be overestimating the ability of the current global system to produce "economic liberation", depending upon what you mean. A rough estimate of GDP per capita would put it at ~$20K if you adjust for purchasing power, less than $15K if you don't. That's well below what most people in the developed world would consider to be free of burden or worry and it assumes a completely equal distribution of all production, which is obviously unreasonable.

We need to continue to push the ball forward in growing wealth by continuing to improve productivity, which is going to require continued advancements in technology like mass adoption of AI.

This is a key point. Given current overall levels of economic productivity, we should all be working 3-4 day weeks, at most.

To whom do the benefits of all this newfound efficiency accrue?

> The price of land will skyrocket

Is that really true?

Let's look at some data from Google, the World Bank, etc.:

     US land area: 3,532,316 square miles

     US population: 334.9 million

     640 acres per square mile

     ( 640 * 3,532,316 ) / 334,900,000 =
     6.750 acres per person

     Fertility rate: 1.66 births per woman
     (2022) World Bank

     GDP growth rate: 2.5% annual change
     (2023) World Bank

     ( 4 * 640 * 3,532,316 ) / 334,900,000
     = 27 acres per family of four

A guess is that people are crowded into tall buildings in dense cities to reduce costs of communications. So, yes, in dense cities, the cost of land per acre is comparatively high.

But the Internet is reducing the costs of communications meaning that people can move to land that is less densely populated and cheaper.

So, for the near future, tough to believe:

> The price of land will skyrocket

> We already produce more than enough for economic liberation all over the world, many times over. It hasn't happened. Why?

Because directing material resources towards that end requires a certain aggregate amount of willing/aligned general intelligence, which we simply don't have as a society. Failure after failure of socialist states demonstrate that human general intelligence is on average, uninterested in working towards the greater good. AGI won't have such limitations.

The blog post even addresses this: "the cost of intelligence and the cost of energy constrain a lot of things".

However, I actually do agree with you, but for a different reason. AGI is highly unlikely to yield economic liberation for the masses. Not because we won't have the intelligence capacity, but because the iota of people that will have their hands on the levers of power will in all likelyhood be uninterested in tending to the masses of now economically useless people.

30 years ago, no one in my native place has seen telephone. Now every single person young and old are connected to the internet, conduct banking and other transaction via phone and many many other things.

Many unimaginable things happened in last 30 year from vantage point of my native place. Assuming same level of of transformation for next 30 year it will be still massive progress. Given current tech and AI, the rate of progress for next 30 years will be far greater than last 30. So I am believer in AI and tech in general will make massive progress in next decade

If each human body needs 0.2 acre of land to grow the food necessary for subsistence, what happens when the price of intelligence keeps dropping and one person's intelligence (even when directed towards the highest-value use!) is not enough to afford the use of that land? In other words, what happens when humans are no longer economically viable?

Jevon's Paradox means that the demand for intelligence will keep rising as the cost drops, so I can't help but expect a steady increase in the economic value of land _when used for AI_. It'll take a long time before it exceeds the economic value of land when used for human subsistence, but the growth curves are not pointing in encouraging directions.

The next fifty years are going to be quite interesting.