A while ago I needed some info about a document for tax reasons. When I called in to the UK tax office line a robot voice required me to name the department that I wanted to talk to. I didn't know which this was and it wasn't on their website (and indeed "who do I request this document from?" was the essence of my question). Speak to a human operator was not offered as an option.
I think I just said random words until it put me through to some departmen and from there they had a normal call tree via which I got an unrelated human who could tell me who I actually needed to ask for. But I'm not looking forward to the day that no humans are in the loop and unanticipated circumstances are completely unresolvable.
I fear our AI future not because of evil but because of bureaucrats.
I'm also resorting to punching 1,1,1,1 or whatever combo works and asking the first person who answers on that tree to put me through where I need to go. For voice activation it means making unintelligible sounds in the hopes of the system switching to a human. Strangely enough, whatsapp business is becoming a much better experience in place of calling, but sometimes even chat isn't enough.
> I fear our AI future not because of evil but because of bureaucrats.
Fair, though the advantage of an actual LLM here is that it's not limited to a dumb hard-coded menu, so if done right (I know, I know) an LLM would help a lot.
(One of the disadvantages is that current models sometimes extemporise answers even if none exist).
LLMs, transformer models in particular, are artificial neural networks. They have always been AI. AI is the field which led to this, the research is published as AI research.
It's amazing how often us humans (me included!) don't use RAG (retrieval augmented generation) in the form of a search engine and just trust our gut instinct for off-the-cuff responses :D
> Large language models have no formal reasoning, they have no long term recall, they contain no structured logic.
> I’m not saying it can’t be solved. I’m saying it can’t be solved INSIDE the LLM.
Do you mean transformers then? Because that is the current vogue architecture for large language models which is clearly a broader category.
The full details for the current best models are secret, but they're still large language models, and they're demonstrating surprisingly high performance on logic and reasoning.
For all that LLMs produce good performance, it's still just predictive texting. If you can get the hallucination rate on that down to 0% without using anything else, I'll be extremely shocked.
Now, layer a few sanity checks on top of an LLM, especially some clever thing we haven't invented yet, and I'll totally believe it - the task is absolutely doable, I'd just find it really weird if a predictive engine could do it 100% accurately, using only modern resources.
Conditional on it still sounding like you mean Transformers rather than LLMs, we're pretty close to agreement.
But even Transformers really are not just preditive text.
IIRC the original Google usage, Attention is All You Need era, was for translation; and while I would indeed characterise the first few OpenAI/GPT models as "autocomplete on steroids", that changed with InstructGPT, which was the first time I saw them transforming requests into actions, in the form of creating a very simple web game.
> I'd just find it really weird if a predictive engine could do it 100% accurately, using only modern resources.
I currently think there is no such thing as "knowledge" in reality, that such a state is as unrealisable as counting to infinity, that all we can really have are beliefs of varying certainty; in this regard, 100% can never happen in any system including humans — but also, I wouldn't say an AI is "hallucinating" if the error rate was similar to that of a human.
Likewise, I find it really weird how a neural network with the complexity of a mid-sized rodent is able to transform prompts in the most used languages into mostly-correct source code in most programming languages — this is not a thing I would have expected, given the observable lack of employment opportunities for rodents* in software engineering departments.
I think I just said random words until it put me through to some departmen and from there they had a normal call tree via which I got an unrelated human who could tell me who I actually needed to ask for. But I'm not looking forward to the day that no humans are in the loop and unanticipated circumstances are completely unresolvable.
I fear our AI future not because of evil but because of bureaucrats.