The Bitter Lesson Is Misunderstood • Hacker News Board

Re: The Bitter Lesson Is Misunderstood

#101

Post by FloorEgg » Thu, Sep 04, 2025, 4:00 AM UTC

breuleux wrote: post #89

FloorEgg wrote: post #84

Earlier quoted context omitted.

Nicely said. This all aligns with my intuition, with one caveat. I think you and I are using different definitions of intelligence. I'm bought into Karl Friston's free energy principle and think it's intelligence all the way down. There is no separating embodiment and intelligence. The LLM distinction is intelligence via symbols as opposed to embodied intelligence, which is why I really like your shadow world analogy…

You're right, we probably have different ontologies. To me an intelligent system is a system which aims to realize a goal through modelling its environment and planning actions to bring about that intended state. That's more or less what humans do and I think that's more in line with the colloquial understanding of it. There are basically two approaches to defining intelligence, I think. You can either define it in t…

If intelligence is treated as a scale, should it be measured primarily by (a) the diversity of valid actions an entity can take combined with its ability to collect and process information about its environment and predict outcomes, or (b) only by its ability to collect and process information and predict outcomes?

In either case, the smallest unit of intelligence could be seen as a component of a two-field or particle interaction, where information is exchanged and an outcome is determined. Scaled up, these interactions generate emergent properties, and at each higher level of abstraction, new layers of intelligence appear that drive increasing complexity. Under such a view, a less intelligent system might still excel in a narrow domain, while a more intelligent system, effective across a broader range, might perform worse in that same narrow context.

Depending on the context of the conversation, I might go along with some cut-off on the scale, but I don't see why the scale isn't continuous. Maybe it has stacked s-curves though...

We just happen to exist at an interesting spot on the fractal that's currently the highest point we can see. So it makes sense we would start with our own intelligence as the idea of intelligence itself.

Re: The Bitter Lesson Is Misunderstood

#102

Post by [deleted] » Thu, Sep 04, 2025, 4:08 AM UTC

noduerme wrote: post #86

trescenzi wrote: post #82

Earlier quoted context omitted.

This is interesting to think about. It’s basically just birds and primates. Birds have an ancient evolutionary tree as they are dinosaurs, which did actually walk on two legs. But the gap between dinos and primates walking on two feet, I think, is tens of millions of years. So yea pretty long time.

This makes me think something else, though. Once we were able to reason about the physics behind the way things can move, we invented wheels. From there it's a few thousand years to steam engines and a couple hundred more years to jet planes and space travel. We may have needed a billion years of evolution from a cell swimming around to a bipedal organism. But we are no longer speed limited by evolution. Is there any…

[deleted]

Re: The Bitter Lesson Is Misunderstood

#103

Post by voxic11 » Thu, Sep 04, 2025, 4:27 AM UTC

jeremyjh wrote: post #51

voxic11 wrote: post #21

Earlier quoted context omitted.

Synthetic data is already widely used to do training in the programming and mathematics domains where automated verification is possible. Here is an example of an open source verified reasoning synthetic dataset https://www.primeintellect.ai/blog/synthetic-1

Are they actually producing new data though? This is the sort of thing I called "compression and filtering" because it seems to be new information content is not being produced, but LLMs are used to distill the information we already have. We need more raw information.

Yes this is new synthetic data which did not exist before. I encourage you to read the link.

Re: The Bitter Lesson Is Misunderstood

#104

Post by noduerme » Thu, Sep 04, 2025, 4:48 AM UTC

breuleux wrote: post #96

noduerme wrote: post #86

Earlier quoted context omitted.

This makes me think something else, though. Once we were able to reason about the physics behind the way things can move, we invented wheels. From there it's a few thousand years to steam engines and a couple hundred more years to jet planes and space travel. We may have needed a billion years of evolution from a cell swimming around to a bipedal organism. But we are no longer speed limited by evolution. Is there any…

Note that wheels, steam engines, jet planes, spaceships wouldn't survive on their own in nature. Compared to natural structures, they are very simple, very straightforward. And while biological organisms are adapted to survive or thrive in complicated, ever-changing ecosystems, our machines thrive in sanitized environments. Wheels thrive on flat surfaces like roads, jet planes thrive in empty air devoid of trees, and…

Okay, but (1) we don't need to simulate physics faster than physics to make accurate-enough predictions to fly a plane, in our heads, or build a plane on paper, or to model flight in code. (2) If that's only because we've cleared out the trees and the Canada Geese and whatnot from our simplified model and "built the road" for the wheels, then necessity is also the mother of invention. "Hey, I want to fly but I keep crashing into trees" could lead an AI agent to keep crashing, or model flying chainsaws, or eventually something that would flatten the ground in the shape of a runway. In other words, why are we assuming that agents cannot shape the world (virtual, for now) to facilitate their simplified mechanical and physical models of "flight" or "rolling" in the same way that we do?

Also, isn't that what's actually scary about AI, in a nutshell? The fact that it may radically simplify our world to facilitate e.g. paper clip production?

Re: The Bitter Lesson Is Misunderstood

#105

Post by delusional » Thu, Sep 04, 2025, 4:54 AM UTC

programjames wrote: post #78

breuleux wrote: post #74

Earlier quoted context omitted.

> So it makes me wonder, is embodiment (advanced robotics) 1000x harder than LLMs from an information processing perspective? Essentially, yes, but I would go further in saying that embodiment is harder than intelligence in and of itself. I would argue that intelligence is a very simple and primitive mechanism compared to the evolved animal body, and the effectiveness of our own intelligence is circumstantial. We man…

It took about the same amount of time to evolve human-level intelligence as human-level mobility. Pretty much no other animal walks on two legs...

Talking about "time to evolve something" seems patently absurd and unscientific to me. All of nature evolved simultaneously. Nature didn't first make the human body and then go "that's perfect for filling the dishwasher, now to make it talk amongst itself" and then evolve intelligence. It all evolved at the same time, in conjunction.

You cannot separate the mind and the body. They are the same physiological and material entity. Trying anyway is of course classic western canon.

Re: The Bitter Lesson Is Misunderstood

#106

Post by dosnem » Thu, Sep 04, 2025, 4:55 AM UTC

cs702 wrote: post #3

I don't think Sutton's essay is misunderstood, but I agree with the OP's conclusion: We're reaching scaling limits with transformers. The number of parameters in our largest transformers, N, is now in the order of trillions, which is the most we can apply given the total number of tokens of training data available worldwide, D, also in the order of trillions, resulting in a compute budget C = 6N × D, which is in the…

This seems so simple but I’m totally not understanding it..

If C = D^2, and you double compute, then 2C ==> 2D^2. How do you and the original author get 1.41D from 2D^2?

Re: The Bitter Lesson Is Misunderstood

#107

Post by jacobolus » Thu, Sep 04, 2025, 5:00 AM UTC

dr_dshiv wrote: post #57

jacobolus wrote: post #37

Earlier quoted context omitted.

The volume of text in English and digitized from the past few years dwarfs the volume of Latin text from all time. Unless you are wondering about a very niche historical topic there’s more written in English than Latin about basically everything.

Well, if you are looking for diversity of perspective— temporal diversity may be valuable. Marsilio Ficino was hired by the Medici to translate Plato and other classical Greek works into Latin. He directly taught DaVinci, Raphael, Michelangelo, Toscanelli, etc. I mean to say that his ideas and perspectives helped spark the renaissance. Insofar as we hope for an AI renaissance and not an AI apocalypse, it might benefi…

And here you can e.g. find Ficino's correspondence translated into English, with commentary, https://archive.org/details/lettersofmarsili0000fici

If you make a cursory search you can also find other translations of his works, various biographies, and a wide range of commentary and criticism by later authors.

Many of Ficino's originals are also in the corpus of scanned and OCRed or recently republished texts. I'm sure there are archives here or there with additional materials which have not been digitized, but it seems questionable whether those would make any significant difference to a process as indiscriminate and automatic as LLM training.

Re: The Bitter Lesson Is Misunderstood

#108

Post by giardini » Thu, Sep 04, 2025, 5:02 AM UTC

breuleux wrote: post #74

FloorEgg wrote: post #56

Earlier quoted context omitted.

10+ years ago I expected we would get AI that would impact blue collar work long before AI that impacted white collar work. Not sure exactly where I got the impression, but I remember some "rising tide of AI" analogy and graphic that had artists and scientists positioned on the high ground. Recently it doesn't seem to be playing out as such. The current best LLMs I find marvelously impressive (despite their flaws), a…

> So it makes me wonder, is embodiment (advanced robotics) 1000x harder than LLMs from an information processing perspective? Essentially, yes, but I would go further in saying that embodiment is harder than intelligence in and of itself. I would argue that intelligence is a very simple and primitive mechanism compared to the evolved animal body, and the effectiveness of our own intelligence is circumstantial. We man…

Plato's "Allegory of the cave" was uninteresting and uninformative when I first read it more than 50 years ago. It remains so today.

https://en.wikipedia.org/wiki/Allegory_of_the_cave

Also, other than in sculpture/dentistry/medicine I also find "ablation" to not be a particularly insightful metaphor either. Although I see ablation's application to LLMs I simply had to laugh when I first read about it: I envisioned starting with a Greyhound bus and blowing off parts until it was a Lotus 7 sports car!8-). Good luck with that! Kind of like fixing the TV set by kicking it (but it _does_ work sometimes!).

Perhaps we should refrain somewhat from applying metaphors/simile/allegories to describe LLMs relative to human intelligence unless they provide some insight of significant value.

Re: The Bitter Lesson Is Misunderstood

#109

Post by baq » Thu, Sep 04, 2025, 5:04 AM UTC

noduerme wrote: post #86

trescenzi wrote: post #82

Earlier quoted context omitted.

This is interesting to think about. It’s basically just birds and primates. Birds have an ancient evolutionary tree as they are dinosaurs, which did actually walk on two legs. But the gap between dinos and primates walking on two feet, I think, is tens of millions of years. So yea pretty long time.

This makes me think something else, though. Once we were able to reason about the physics behind the way things can move, we invented wheels. From there it's a few thousand years to steam engines and a couple hundred more years to jet planes and space travel. We may have needed a billion years of evolution from a cell swimming around to a bipedal organism. But we are no longer speed limited by evolution. Is there any…

Something that isn’t obvious when we’re talking about the invention of the wheel: we aren’t actually talking about the round shape thing, we’re actually talking about the invention of the axle which allowed mounting a stationary cart on moving wheels.

Re: The Bitter Lesson Is Misunderstood

#110

Post by yberreby » Thu, Sep 04, 2025, 5:09 AM UTC

dosnem wrote: post #106

cs702 wrote: post #3

I don't think Sutton's essay is misunderstood, but I agree with the OP's conclusion: We're reaching scaling limits with transformers. The number of parameters in our largest transformers, N, is now in the order of trillions, which is the most we can apply given the total number of tokens of training data available worldwide, D, also in the order of trillions, resulting in a compute budget C = 6N × D, which is in the…

This seems so simple but I’m totally not understanding it.. If C = D^2, and you double compute, then 2C ==> 2D^2. How do you and the original author get 1.41D from 2D^2?

If C ~ D^2, then D ~ sqrt(C).

In other words, the required amount of data scales with the square root of the compute. The square root of 2 ~= 1.414. If you double the compute, you need roughly 1.414 times more data.