In fact I find it a really bad example. Yes I think your personal AI could be allowed to tell you how to cover up a murder. I'm not entirely sure about it but seems possible.
What about your personal, local AI guiding you to modifying a flu virus for maximum contagiousness and deadliness? "Sure George, here's your shopping list. It's $1500 total in equipment, do you want me to proceed with the orders?"
You do realise then that "we know how it works, there is no "extra" there" is an argument that can be used against any artificial intelligence, now or in a thousand years, as well as (at some level) against human intelligence (no magic, it's all physics, just dumb cells exchanging signals). This should be enough to give you pause- you immediately reached for an argument that is entirely empty.
> I see a lucky stochastic search result
Again you're reaching for a mechanistic explanation of some kind (let's leave for the moment whether it makes sense or not) as if having an explanation somehow contradicted a display of intelligence. It doesn't. Yes of course we made it, we know how it works (ar some level) and there is no magic. But what matters is the result- this machine, matrix multiplier, stochastic parrot, consistently displays intelligence, to the point of being able to perform very complex, open-ended tasks that integrate discovery, planning, tool usage, decision and even some aesthetic sense, understanding and using natural language, context awareness, you name it.
> This is nothing new, we've been playing with these toys for like 70 fucking years
Lol no. For god's sake. Hundreds of billions of parameters organised in a specific architecture and trained with unimaginable amounts of data and compute? Unless by "these toys" you mean "any computer program vaguely AI-related".
> We know how these machines work, it's not mysterious, there's nothing "extra" happening.
Lol. This is more telling about your implicit unscientific preconceptions that you wanted to reveal. Of course there isn't anything "extra". Where do you think intelligence comes from, some mysterious realm? It's physical, computational. The fact that at the bottom we produced it via matrix multiplication is irrelevant. Maybe humbling. You are denying a visible fact (a machine performs tasks that require flexible analytical and cognitive skills) precisely because there is no magic happening anywhere.
> Without massive amounts of investment, AI development stops dead.
Would the US government not pour enormous resources in AI labs if needed, knowing that China might be doing the same? What happens if an adversary develops an AI capable of finding and implementing exploits in every software run by your country's strategic infrastructure?
Jesus... This morning while I was drinking coffee and staring at the screen (it's Saturday) an agent did the equivalent of days of my work, reading code, understanding, hypothesizing, comparing, using tools, writing scripts, launching compilers and running tests, identifying problems and proposing solutions, and more. Only someone who hasn't spent a second reflecting about what it means to think and to be intelligent can claim that we miss a realistic path to intelligence. It's so damn clueless and stubborn and confidently wrong that it annoys me immensely, so sorry for the rant.
It's a static decoy message independent from what you type in. You can see it if you take a long exposure pic of the screen (e.g. with your smartphone).
> We attach basically zero value to writing a new program
What does it mean "new"? And, was it a difficult or trivial accomplishment?
A solution to a well known open math problem is both new and non-trivial- you know that many, very smart, very well trained human experts have dedicated time to the problem and haven't been able to solve it, despite good incentives.
> still one area where it is notoriously bad is creation of novel things
Is there any proof of this? My feeling is that people just assume that since something has been generated by AI, then it must not be original. And truly original thought or craft is exceedingly rare if it exists at all: everything comes from something else. Individual innovations are often small.
> Because that is the only loophole in LLMs that can not be fixed
This is magical thinking. Humans don't have a small device in their head capable of "true creativity" whatever that even is. At most, they experience so much random input that their outputs are less predictable. But nothing that LLMs won't be able to do soon; as for raw intelligence, they're already smarter than the large majority of the population.
Israel keeps acting as a cartoonishly evil advisor trying to manipulate the king with flattery and outrageous lies. It's so evident and so vile that it's funny.
Because you can share types and even modules with your frontend project? Because for applications that aren't CPU-intensive it makes almost no difference? Because you are familiar with it and like it? Because of the humongous amount of libraries?
> then they shouldn't care whether it's a human or a LLM.
I imagine that the whole point of posting a task to Mechanical Turk nowadays is that you want it to be completed by humans. Either because you are after the small discrepancy between AI and human performance, or because humans are the object of your investigation.
Anthropic won't do it, but they published the j-lens to introspect the model- from what I understand it's roughly simply feeding a chosen layer straight into the final layers of the LLM for decoding into language:
It's been shown that LLMs use their outer layers to decode from and encode to language, while their middle layers deal in language-independent abstract concepts. This means that the same question or statement in different languages activates the outer layers differently but produces the same patterns in the middle layers. Check this article with cool visualizations (btw, this is one of the articles mentioned also by a sibling answer):
The middle layers also perform reasoning on the abstract concepts, to the point that you can replicate some blocks of inner layers (thus giving the LLM more internal "reasoning space") and by this increase the model's reasoning abilities. The video in this article shows that when performing a sequence of arithmetic operations (without CoT, i.e. the result is spit out directly), internally the intermediate calculations are spelled out, and this can only happen in the depth direction of the LLM (since no new token is added to the sequence). So this "jspace" can only be situated in the middle layers, probably in circuits that repeat nearly identical across several layers.
What about your personal, local AI guiding you to modifying a flu virus for maximum contagiousness and deadliness? "Sure George, here's your shopping list. It's $1500 total in equipment, do you want me to proceed with the orders?"