31–40 of 53 posts
0: a type of evolved sea-slug
1: by capturing it and torturing it
Everyone keeps thinking current GPT models will improve to be superhuman, it won't. It's trained on human data. Much like alpha-go had to drop completely the concept of learning from human plays since it was stuck at a local minimum. Once they started to train with adversarial networks, it evolved a well above the previous local minimum (with an extra order of magnitude of computation). So, don't expect much more fro…
Kind of have the same intuition. However, to play devil's advocate, the human data and knowledge far exceeds what a single human can know and learn - so it would make it already superhuman.
Searle's chinese room argument is starting to make sense in this case.
What's not 'safe' about AI? If you mean the hallucinations I don't think that will ever really be solved. I think people just have to learn that LLMs are not divine oracles that are always correct. Just like the training data generated by the flawed humans that are often either wrong or outright lying. Garbage in, garbage out. Not saying that AI isn't useful. But expecting what is basically a "human simulator" not to…
This is true by definition, since a 'hallucination' isn't a failure condition in which the system isn't working as designed, it's just a post-hoc term for when probabilistic output doesn't meet our expectations, which is inherent to the nature of all probabilistic systems.
Within the system, there is no distinction between 'hallucination' and 'non-hallucination'.LLMs are applying the same stochastic process in all cases, and the criteria of whether we call its output a 'hallucination' is entirely external to their functioning.
Strictly speaking, LLMs are always hallucinating, since they are always generating inferences based on hard-coded statistical models and have no awareness of the semantic meaning of the tokens they correlate, nor any internal criteria of external correctness.
> I think people just have to learn that LLMs are not divine oracles that are always correct.
We all need to keep repeating the mantra "all models are wrong; some models are useful."
This one is easy, within a year, as safe as GPT-4 and it will be an incremental advance over 4. Most people will use it and not see much difference over GPT-4.
Exactly that. People were having the same unrealistic expectations about GPT-4 and it turned out to be barely noticeably different from GPT-3.5 for a lot of use cases.
Everyone keeps thinking current GPT models will improve to be superhuman, it won't. It's trained on human data. Much like alpha-go had to drop completely the concept of learning from human plays since it was stuck at a local minimum. Once they started to train with adversarial networks, it evolved a well above the previous local minimum (with an extra order of magnitude of computation). So, don't expect much more fro…
https://openai.com/index/video-generation-models-as-world-si...
Here's a completely made up point of view. (I haven't read the articles.) GPT-4 is not an LLM, but a complex software system, which has LLM(s) at its core, but also other components like RAG, toxicity filter, apologizing mechanism, expert systems, etc. "GPT-4" is product name / marketing name. For OpenAI, this would be logical for performance and business reasons. This explains also how they can tune it, the apparent…
Everyone keeps thinking current GPT models will improve to be superhuman, it won't. It's trained on human data. Much like alpha-go had to drop completely the concept of learning from human plays since it was stuck at a local minimum. Once they started to train with adversarial networks, it evolved a well above the previous local minimum (with an extra order of magnitude of computation). So, don't expect much more fro…
Unlike the game of go where AI can try random stuff and see what works, it's not possible with general knowledge.
GenAI is destined to know at most what humanity knows, and we can already see that it has terrible reasoning capabilities. GenAI is not going to hit a wall, it already has.
Earlier quoted context omitted.
> - a steady increment of GPT-n+1 every 6 months for marketing purposes. You already failed then, gpt4 was released more than a year ago
Reasonable assumption would be from now moving forward. Last release was gpt-4o. But there is little to engage with in your comment, I'd be most curious to explore on what u believe it's capacities might be, and societal impact.
Earlier quoted context omitted.
> - a steady increment of GPT-n+1 every 6 months for marketing purposes. You already failed then, gpt4 was released more than a year ago
Reasonable assumption would be from now moving forward. Last release was gpt-4o. But there is little to engage with in your comment, I'd be most curious to explore on what u believe it's capacities might be, and societal impact.
No, it is not reasonable to start with a minor release. Only if you want to stretch things to fit a narrative. Which we are free to disagree.
If you check other comments, I have talked about what I believe are their capacities and social impact. Downgrading it and calling the next major releases a marketing stunt is a opinion that we are fine to disagree, no?