Has the hallucination problem in AI been solved? My understanding that all AI can, and will hallucinate. I get downvoted for saying this, but no one ever says I'm wrong or cites any source. Perhaps it's more nuanced than that? Please, enlighten me. |
Has the hallucination problem in AI been solved? My understanding that all AI can, and will hallucinate. I get downvoted for saying this, but no one ever says I'm wrong or cites any source. Perhaps it's more nuanced than that? Please, enlighten me. |
For the first, we're mostly past the point of just "testing". So I don't see that too much anymore. Mostly I still see that though in bug reports generated by AI by someone else. There is usually some underlying bug being reported, but the AI explanation and "helpful suggestion" is typically inaccurate. Generally, suggested fixes are terrible. (They likely work, but fix a symptom not the cause.)
The second still happens, but with much less regularity for me though. It does make mistakes though.
In areas where I'm not as skilled it's very hard to spot errors. When researching general information I'm mostly accepting it on face value.
I find the bug-report thing really interesting. For lots of simple bugs it's great. For more complex things it seems to be very superficial- if a 0 causes an issue here, add a simple guard for 0. There's no depth of understanding why the value is 0 in the first place, when it should be set. If it can (incorrectly) be 0 here, where else might 0 be impacting the code?
This informs my opinion of vibe coded stuff - where there is no skilled human inspection. I expect that code to be of a poor underlying quality. Especially if it's AI changes to an existing human-coded app.
Worth noting that both cases indirectly involve the humans that designed devices and the humans that made the placement and trigger condition decisions.
Further:
> AI drones are being used to autonomously target and kill targets by the Ukraine using technology they have been given.
Ukrainian Combat Robot Holds Frontline Position for Six Weeks in Sign of Growing UGV Maturity - https://defenceleaders.com/news/ukrainian-combat-robot-holds...
are remote operated, they allow defenders cover while themselves being out and exposed.
However were they altered to autonomously fire, that would be on the basis of pattern matching in the visible and infra red spectrum - shoot at all hot blobs.
That's more of a trigger threshold setting issue than an LLM hallucination issue, and the danger is on par with any weapon system on auto fire, you really shouldn't approach such things until they are put in a safe off state or have exhausted ammunition.
edit for clarity
First point, vision systems have been used in industry to look for misaligned labels, incorrectly folded papers (in high speed paper presses), wrong items on high speed conveyor belts etc. for thirty odd years now - they have issues that a very distinct from LLM 'AI' hallucinations.
That's nomenclature out the way.
Landmines are indiscriminate, they trigger on any weight or pressure over a threshold.
A vision based Felixer, by contrast, only triggers on cats (well, almost always only) and leaves bilbies and bettongs to walk on by.
That's an improvement over landmines.
The crux of your issue here might be the morality and ethics of establishing human exclusion zones within which all humans are highly likely to die.
These historically are created with rapid patterned artillery fire, butterfly mines, Napalm, indiscriminate criss crossing machine gun fire, etc.
Now there exists an option to use drones to kill all humans and leave the horses and cows alive.
Is it your concern that a bad vision threshold might kill a horse rather than a person? (Likely not)
Would you prefer an area to be napalm'd and agent orange'd back to dust?
War is hell.
* https://www.abc.net.au/news/2020-05-29/feral-cat-management-...