Earlier quoted context omitted.
Expecting a purely technical discussion is unrealistic because many people have significant vested interests. This includes not only those with financial stakes in AI stocks but also a large number of professionals in roles that could be transformed or replaced by this technology. For these groups, the discussion is inherently political, not just technical.
I don't really mind if people advocate for their value judgements, but the total disregard for good faith arguments and facts is really out of control. The number of people who care at all about finding the best position through debate and are willing to adjust their position is really shockingly small across almost every issue.
AGI fantasy is a blocker to actual engineering
271–280 of 683 posts
Re: AGI fantasy is a blocker to actual engineering
#272Earlier quoted context omitted.
On the other hand, a large part of the complexity of human hardware randomly evolved for survival and only recently started playing around in the higher-order intellect game. It could be that we don't need so many neurons just for playing intellectual games in an environment with no natural selection pressure. Evolution is winning because it's operating at a much lower scale than we are and needs less energy to achie…
Evolution has won so far because it had a four billion year head start. In two hundred years, technology has gone from "this multi-ton machine can do arithmetic operations on large numbers several times faster than a person" to "this box produces a convincing facsimile of human conversation, but it only emulates a trillion neurons and they're not nearly as sophisticated as real ones." I do think we probably need a ne…
Re: AGI fantasy is a blocker to actual engineering
#273Earlier quoted context omitted.
Hey Simon, author here (and reader of your blog!). I used to share your view, but what changed my mind was reading Hao's book. I don't have it to hand, but if my memory serves, she writes about a community in Chile opposing Google building a data centre in their city. The city already suffers from drought, and the data centre, acccording to Google's own assessment, would abstract ~169 litres of water a second from lo…
The fact that certain specific data centres are being proposed or built in areas with water issues may be bad, but it does not imply that all AI data centres are water guzzling drain holes that are killing Earth, which is the point you were (semi-implicitly) making in the article.
Re: AGI fantasy is a blocker to actual engineering
#274Earlier quoted context omitted.
> The water issue really is a distraction which harms the credibility of people who lean on it Is that really the case? - "Data Centers and Water Consumption" - https://www.eesi.org/articles/view/data-centers-and-water-co... "...Large data centers can consume up to 5 million gallons per day, equivalent to the water use of a town populated by 10,000 to 50,000 people..." "I Was Wrong About Data Center Water Consumption…
What counts as data center water consumption here? There are many ways to arguably come up with a number. Does it count water use for cooling only, or does it include use for the infrastructure that keeps it running (power generation, maintenance, staff use, etc.) Is this water evaporated? Or moved from A to B and raised a few degrees.
Re: AGI fantasy is a blocker to actual engineering
#275Earlier quoted context omitted.
Can you? You have weather readouts. One set is from a weather simulation - a simulated planet with simulated climate. Another is real recordings from the same place at the same planet, taken by real weather monitoring probes. They have the same starting point, but diverge over time. Which one is real though? Would you be able tell?
They're not asking about telling the difference in collected data sets, data sets aren't weather. The question is can you tell the difference between the rain you see outside your window, and some representation of a simulated environment where the computer says "It's raining here in this simulated environment". The implied answer is of course, one is water falling from the sky and one is a machine.
A human brain is a big pile of jellied meat spread. An LLM is a big pile of weights strung together by matrix math. Neither looks "intelligent". Neither is interpretable. The most reliable way we have to compare the two is by comparing the outputs.
You can't drill a hole in one of those and see something that makes you go "oh, it's this one, this one is the Real Intelligence, the other is fake". No easy out for you. You'll have to do it the hard way.
Re: AGI fantasy is a blocker to actual engineering
#276Earlier quoted context omitted.
> "While AlphaEvolve is currently being applied across math and computing, its *general* nature means it can be applied to any problem whose solution can be described as an algorithm, and automatically verified. We believe AlphaEvolve could be transformative across many more areas such as material science, drug discovery, sustainability and wider technological and business applications." Is that not general enough fo…
> Do you imagine AGI as a robot and not as datacenter solving all kinds of problems? AGI means it can replace basically all human white collar work, alpha evolve can't do that while average humans can. White collar work is mostly done by average humans after all, if average humans can learn that then so should an AGI. An easier test is that the AGI must be able to beat most computer games without being trained on tho…
Isn't it just an optimization problem from this point? E.g. now training take a lot of hardware and time. If they make it so efficient that training can happen in matter of minutes and cost only few dollars, won't it satisfy your criterion?
I'm not saying AlphaEvolve is "AGI", but it looks odd to deny it's a step towards AGI.
Re: AGI fantasy is a blocker to actual engineering
#277> As a technologist I want to solve problems effectively (by bringing about the desired, correct result), efficiently (with minimal waste) and without harm (to people or the environment). Me too. But, I worry this “want” may not be realistic/scalable. Yesterday, I was trying to get some Bluetooth/BLE working on a Raspberry CM 4. I had dabbled with this 9 months ago. And things were making progress then just fine. Sud…
Re: AGI fantasy is a blocker to actual engineering
#278Earlier quoted context omitted.
Evolution has won so far because it had a four billion year head start. In two hundred years, technology has gone from "this multi-ton machine can do arithmetic operations on large numbers several times faster than a person" to "this box produces a convincing facsimile of human conversation, but it only emulates a trillion neurons and they're not nearly as sophisticated as real ones." I do think we probably need a ne…
But we don't even need a human brain. We already have those, they take months to grow, take forever to train, and are forever distracted. Our logic-based processes will keep getting smaller and less power hungry as we figure out how to implement them at even lower scales, and eventually we'll be able to solve problems with the same building blocks as evolution but in intelligent ways, of which LLMs will likely only p…
They're not that great at knowledge (and we're currently wasting most of the neurons on memorizing common crawl, which... have you looked at common crawl?)
They're not that great at determinism (a good solution here is that the LLM writes 10 lines of Python, which then feed back into the LLM. Then the task completes 100% of the time, and much cheaper too).
They're not that great at complex rules (surprisingly good actually, but expensive and flakey). Often we are trying to simulate what are basically 50 lines of Prolog with a trillion params and 50KB of vague English prompts.
I think if we figure out what we're actually trying to do with these things, then we can actually do each of those things properly, and the whole thing is going to work a lot better.
Re: AGI fantasy is a blocker to actual engineering
#279It is ultimately a hardware problem. To simplify it greatly, an LLM neuron is a single input single output function. A human brain neuron takes in thousands of inputs and produces thousands of outputs, to the point that some inputs start being processed before they even get inside the cell by structures on the outside of it. An LLM neuron is an approximation of this. We cannot manufacture a human level neuron to be s…
The EDA [0] problem is immune to the bitter lesson. There are certainly specific arrangements of matter that can solve this problem better than a GPU/TPU/CPU can today.
[0] https://en.wikipedia.org/wiki/Electronic_design_automation