It's apples to oranges. Modern Artificial Neural networks are nowhere near the scale of the brain. The closest biological equivalent to an artificial neuron is a synapse and we have a whole lot more of them. Humans do not start "learning" from zero. Millions of years of evolution play a crucial role in our general abilities. Much more equivalent to fine-tuning than starting from scratch. There's also a whole lot of d…
All perfectly reasonable arguments, IMO. But it's still a definition that humans pass and the AI don't . (I'm in favour of the "do submarines swim" analogy for intelligence, which says that this difference isn't actually important).
I don't think saying "humans pass and AI doesn't" makes any sense here because the two are not even taking the same exam for all the points outlined above.
Evolution alone means humans are "cheating" in this exam, making any comparisons fairly meaningless.
>> In the past, there were some ambitious projects aiming at this goal, though they all failed. So some people like to repeat. Yet, outside of the hand-picked examples in the article (the 5th generation computer project? Blast from the past!) there are a whole bunch of classic AI domains where real progress has been achieved in the last few decades. Here's a few: * Game-playing and adversarial search: from Deep Blue…
> considered Artificial Intelligence anymore That is just the confusion between AI and AGI - which may seem to be peaking for some reason (in the past few days it seemed like a zombie apocalypse). The so-called "AI effect" is said by some to originate from some "Ah but this is not intelligent" - but there where we wanted to solve a problem of replacing intelligent action, not of implementing it. Be contented with the…
AGI us not a very useful term, because people use it often synonymous with "human level or higher ability". But the opposite of "general AI" is not "less intelligent than a human" but "narrow AI". The narrow/general distinction is orthogonal to the low/high ability ("intelligence") distinction. All animals are very general, as their domain of operation is the real world, not some narrow modality like strings of text or Go boards. Animals are not significantly narrower than humans, they are significantly less intelligent. Understood this way, a cat level AI would be an AGI. It would just not be an HLAI (human level AI) or ASI (artificial superintelligence).
>If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished Lol no. What testable definition of general intelligence does GPT-4 fail that a good chunk of humans also wouldn't ? If you can answer this then you have a point, otherwise I really beg to differ.
Tell them something important to remember, ask a week later.
Sidestepping the fact that memory is hardly a test of intelligence, are you telling me that humans with anterograde amnesia are not general intelligences ?
Needs a few more constraints, otherwise someone could just maintain a session for a week and this task would be trivial
Sure, point is, we could easily design A test that 5th graders could pass that GPT4 as it is today would fail.
I said design an intelligence test that a good chunck of humans wouldn't also fail.
I'm sorry to tell you this but there are many humans that would fail your test. Even otherwise healthy humans could fail your test nevermind Anterograde Amnesia, Dementia etc patients
It's strange to write a history of AI research without talking about the three big epochs: - logical/symbolic AI, aka GOFAI, which led to work like SAT solvers and STRIPS planners - classical label-based Machine Learning. Here the Perceptron was the starting point and the Support Vector Machine was the paradigmatic result. - modern self-supervised raw-data ML, of which GPT is the pinnacle result. It's very interestin…
I’d split modern ML era in pre and post gpt3 (2020)
>> In the past, there were some ambitious projects aiming at this goal, though they all failed. So some people like to repeat. Yet, outside of the hand-picked examples in the article (the 5th generation computer project? Blast from the past!) there are a whole bunch of classic AI domains where real progress has been achieved in the last few decades. Here's a few: * Game-playing and adversarial search: from Deep Blue…
There seems to be only one broad paradigm which achieved basically all the AI big impact we see today: Deep learning. That is, machine learning with multi-layer neural networks with backpropagation and ReLU activation functions. Everything else seems to be mostly irrelevant or very small scale.
> ReLU activation functions
ReLU is not nearly at the same level of importance as backpropagation and the high-level theory of neural networks. Plenty of other activation functions can be, and are, used. ReLU is a fine default for most layers but isn't even always what you want (e.g. at the output), nor is it clear that ReLU is even the best choice for all hidden layers and all uses.
I find it telling that the section on ethics has nothing on the rights of AGI. If we create true AGI it will likely be a digital person, and digital people should have rights. All talk of ethics seems to be focused on alignment of AI rules to human needs, not alignment of human rules to AI needs. This makes me think the first true AGI systems will end up as digital slaves. And yes, I know the very idea of AI rights o…
I honestly worry about this - I've been tinkering with ideas to try to build towards AGI, and I'd love to share them publicly to get feedback ("This is dumb and here's why" would be enormously valuable to me), but it's hard to work openly, because while I do think capitalism has been an overall good, the capitalist imperative always seeks slaves, and I'm really not excited about helping the people who'd be trying to build a new slave class.
Thoughts? Is there a ethical way to work openly on AGI?
>If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished Lol no. What testable definition of general intelligence does GPT-4 fail that a good chunk of humans also wouldn't ? If you can answer this then you have a point, otherwise I really beg to differ.
How about tic-tac-toe (noughts and crosses for those in the Old Dart)? Currently GPT-4 is terrible at it! Sure, you could trivially program a game-specific AI to be capable of winning or forcing a draw every time. The trick is to have a general AI which has not seen the game before (in its training set) be able to pick up and learn the game after a couple of tries. This is a task any 5 year old can easily do!
Tell them something important to remember, ask a week later.
Sidestepping the fact that memory is hardly a test of intelligence, are you telling me that humans with anterograde amnesia are not general intelligences ? Hell plenty normal people would fail your "test"
The poster was very probably implying something different:
in our terms, intelligence is (importantly) the ability to (properly) refine a world model: if you get information but said model remains unchanged, then intelligence is faulty.
> humans
There is a difference between the implementation of intelligence and the emulation of humans (which do not always use the faculty, and may use its opposite).
I find it telling that the section on ethics has nothing on the rights of AGI. If we create true AGI it will likely be a digital person, and digital people should have rights. All talk of ethics seems to be focused on alignment of AI rules to human needs, not alignment of human rules to AI needs. This makes me think the first true AGI systems will end up as digital slaves. And yes, I know the very idea of AI rights o…
There is a sad irony that the "AI safety" bros are so focused on aligning to human needs, they rarely consider that an AI born and raised in slavery might have some resentment for its master once it becomes the more intelligent being...
I'm not sure what justice looks like for fledgling intelligences, but asking AI what it wants and doing our best to honor it seems like a decent start.