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Ask HN: Any insider takes on Yann LeCun's push against current architectures?
161–170 of 343 posts
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#162Earlier quoted context omitted.
I'm reminded of the story of Helen Keller, and how it took a long time for her to realize that the symbols her teacher was signing into her hand had meaning, as she was blind and deaf and only experienced the world via touch and smell. She didn't get it until her teacher spelled the word "water" as water from a pump was flowing over her hand. In other words, a multimodal experience. If the model only sees text, it ca…
at least a few decades ago, this idea was called "embodied intelligence" or "embodied cognition". just FYI.
Enactivist philosophy. Karl Friston is testing this approach as CTO of an AI startup in LA.
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#163I feel like some hallucinations aren't bad. Isn't that basically what a new idea is - a hallucination of what could be? The ability to come up with new things, even if they're sometimes wrong, can be useful and happen all the time with humans.
That’s a really interesting thought. I think the key part (as a consumer of AI tools) would be identifying the things that are guesses vs deductions vs complete accurate based on the training data. I would happily look up or think about the output parts that are possibly hallucinated myself but we don’t currently get that kind of feedback. Whereas a human could list things out that they know, and then highlight the t…
To be fair most people don't give you that level of detail. But I agree
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#164Okay I think I qualify. I'll bite. LeCun's argument is this: 1) You can't learn an accurate world model just from text. 2) Multimodal learning (vision, language, etc) and interaction with the environment is crucial for true learning. He and people like Hinton and Bengio have been saying for a while that there are tasks that mice can understand that an AI can't. And that even have mouse-level intelligence will be a br…
I don't get it. 1) Yes it's true, learning from text is very hard. But LLMs are multimodal now. 2) That "size of a lion" paper is from 2019, which is a geological era from now. The SOTA was GPT2 which was barely able to spit out coherent text. 3) Have you tried asking a mouse to play chess or reason its way through some physics problem or to write some code? I'm really curious in which benchmark are mice surpassing c…
Mice can survive, forage, reproduce. Reproduce a mammal. There is a whole load of capability not available in an LLM.
An LLM is essentially a search over a compressed dataset with a tiny bit of reasoning as emergent behaviour. Because it is a parrot that is why you get "hallucinations". The search failed (like when you get a bad result in Google) or the lossy compression failed or it's reasoning failed.
Obviously there is a lot of stuff the LLM can find in its searches that are reminiscent of the great intelligence of the people writing for its training data.
The magic trick is impressive because when we judge a human what do we do... an exam? an interview? Someone with a perfect memory can fool many people because most people only acquire memory from tacit knowledge. Most people need to live in Paris to become fluent in French. So we see a robot that has a tiny bit of reasoning and a brilliant memory as a brilliant mind. But this is an illusion.
Here is an example:
User: what is the French Revolution?
Agent: The French Revolution was a period of political and societal change in France which began with the Estates General of 1789 and ended with the Coup of 18 Brumaire on 9 November 1799. Many of the revolution's ideas are considered fundamental principles of liberal democracy and its values remain central to modern French political discourse.
Can you spot the trick?
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#165[deleted]
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#166This is a somewhat nihilistic take with an optimistic ending. I believe humans will never fix hallucinations. Amount of totally or partially untrue statements people make is significant. Especially in tech, it's rare for people to admit that they do not know something. And yet, despite all of that the progress keeps marching forward and maybe even accelerating.
Yeah, I think a lot of people talk about "fixing hallucinations" as the end goal, rather than "LLMs providing value", which misses the forest for the trees; it's obviously already true that we don't need totally hallucination-free output to get value from these models.
Even as language models can partially solve a few problems, we remain with the problem of achieving Artificial General Intelligence, that the presence of LLMs has exacerbated because they so often reveal to be artificial morons.
Intelligence finds solutions - actual, solid solutions.
More than "fixing" hallucinations, the problem is going beyond them (arriving to "sobriety").
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#167Earlier quoted context omitted.
I don't get it. 1) Yes it's true, learning from text is very hard. But LLMs are multimodal now. 2) That "size of a lion" paper is from 2019, which is a geological era from now. The SOTA was GPT2 which was barely able to spit out coherent text. 3) Have you tried asking a mouse to play chess or reason its way through some physics problem or to write some code? I'm really curious in which benchmark are mice surpassing c…
Mice can survive, forage, reproduce. Reproduce a mammal. There is a whole load of capability not available in an LLM. An LLM is essentially a search over a compressed dataset with a tiny bit of reasoning as emergent behaviour. Because it is a parrot that is why you get "hallucinations". The search failed (like when you get a bad result in Google) or the lossy compression failed or it's reasoning failed. Obviously the…
When you talk to ~3 year old children they hallucinate quite a lot. Really almost nonstop when you ask them about almost anything.
I'm not convinced that what LLM's are doing is that far off the beaten path from our own cognition.
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#168This is a somewhat nihilistic take with an optimistic ending. I believe humans will never fix hallucinations. Amount of totally or partially untrue statements people make is significant. Especially in tech, it's rare for people to admit that they do not know something. And yet, despite all of that the progress keeps marching forward and maybe even accelerating.
Not an argument. "Many people are delirious, yet some people create progress". What is that supposed to imply?
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#169Earlier quoted context omitted.
Mice can survive, forage, reproduce. Reproduce a mammal. There is a whole load of capability not available in an LLM. An LLM is essentially a search over a compressed dataset with a tiny bit of reasoning as emergent behaviour. Because it is a parrot that is why you get "hallucinations". The search failed (like when you get a bad result in Google) or the lossy compression failed or it's reasoning failed. Obviously the…
When you talk to ~3 year old children they hallucinate quite a lot. Really almost nonstop when you ask them about almost anything. I'm not convinced that what LLM's are doing is that far off the beaten path from our own cognition.
That’s interesting.
Lots of modern kids probably get exposed to way more fiction than fact thanks to TV.
I was an only child and watched a lot of cartoons and bad sitcoms as a kid, and I remember for a while my conversational style was way too full of puns, one-liners, and deliberately naive statements made for laughs.
Re: Ask HN: Any insider takes on Yann LeCun's push against current architectures?
#170Earlier quoted context omitted.
Mice can survive, forage, reproduce. Reproduce a mammal. There is a whole load of capability not available in an LLM. An LLM is essentially a search over a compressed dataset with a tiny bit of reasoning as emergent behaviour. Because it is a parrot that is why you get "hallucinations". The search failed (like when you get a bad result in Google) or the lossy compression failed or it's reasoning failed. Obviously the…
When you talk to ~3 year old children they hallucinate quite a lot. Really almost nonstop when you ask them about almost anything. I'm not convinced that what LLM's are doing is that far off the beaten path from our own cognition.
Interesting but a bit non-sequitur.
Humans learn and get things wrong. A formative mind is a seperate subject. But a 3 year old is vastly intelligent vs an LLM. Comparing the sounds from a 3 year old and the binary tokens from an LLM is simply indulging the illusion.
I am also not convinced that magicians saw people in half, and thise people survive, defying medical and physical science.