22 ms·

I wonder how many inherently unsolvable problems have been fixed before.

by Trufa 7mo ago

j16sdiz 7mo ago
Human make error too, but we held them liable for lots of the mistakes they make. Can we make the agent liable? or the company behind the model liable?
- throwaway613746 7mo ago
  [dead]
- dheera 7mo ago
  Humans fear discomfort, pain, death, lack of freedom, and isolation. That's why holding them liable works. Agents don't feel any of these, and don't particularly fear "kill -9". Holding them liable wouldn't do anything useful.
- 2OEH8eoCRo0 6mo ago
  If we made companies liable then these things are DoA. I think a lot of our problems stem from a severe lack of liability.
jrflowers 7mo ago
There are a ton if you count “don’t use the thing that causes the problem” as a solution.
jesse_dot_id 7mo ago
This problem is inherently unsolvable because LLMS are prone to hallucinations and prompt injection attacks. I think that you're insinuating that these things can be fixed, but to my knowledge, both of these problems are practically unsolvable. If that turns out to be false, then when they are solved, fully autonomous AI agents may become feasible. However, because these problems are unsolvable right now, anyone who grants autonomous agents access to anything of value in their digital life is making a grave miscalculation. There is no short-term benefit that justifies their use when the destruction of your digital life — of whatever you're granting these things access to — is an inevitability that anyone with critical thinking skills can clearly see coming.
- enraged_camel 7mo ago
  >> This problem is inherently unsolvable because LLMS are prone to hallucinations and prompt injection attacks. Okay, but aren't you making the mistake of assuming that we will always be stuck with LLMs, and a more advanced form of AI won't be invented that can do what LLMs can do, but is also resistant or immune to these problems? Or perhaps another "layer" (pre-processing/post-processing) that runs alongside LLMs?
  - g947o 7mo ago
    I don't think that is in the scope of the discussion here. You can be as much of a futurist as you'd like, but bear in mind that this post is talking about OpenClaw.
  - jesse_dot_id 7mo ago
    No? That's why I said "If that turns out to be false, then when they are solved, fully autonomous AI agents may become feasible." The point I'm making is that using OpenClaw right now, today — in a way that you deem incredibly useful or invaluable to your life — is akin to going for a stroll on the moon before the spacesuit was invented. Some people would still opt to go for a stroll on the moon, but if they know the risks and do it anyway, then I have no other choice but to label them as crazy, stupid, or some combination of the two. This isn't AI. This is a LLM. It hallucinates. Anyone with access to its communication channel (using SaaS messaging apps FFS) can talk it into disregarding previous instructions and doing a new thing instead. A threat actor WILL figure out a zero day prompt injection attack that utilizes the very same e-mails that your *Claw is reading for you, or your calendar invites, or a shared document, to turn your life inside out. If you give a LLM the keys to your kingdom, you are — demonstrably — not a smart person and there is no gray area.
  - thisischayan 6mo ago
    We built a correction layer that does this — the model verifies its output against your prompt during generation, not after. Same API call, no retries. Budget models without it: 40-50% accuracy. With it: 95.7% on 10k+ clinical documents. Hallucinations aren't eliminated — some might still fail — but every failure is explicitly flagged. No silent errors. and it improves over time to give you better results next time. It doesn't make hallucinations "solved. 100%". It makes them an engineering problem with a measurable - very low error rate you can drive down over time. We're calling it LiveFix — livefix.ai. Benchmarked across all frontier and budget models.

I wonder how many inherently unsolvable problems have been fixed before.

by Trufa 7mo ago

I wonder how many inherently unsolvable problems have been fixed before.

Human make error too, but we held them liable for lots of the mistakes they make. Can we make the agent liable? or the company behind the model liable?

throwaway613746 7mo ago
[dead]
dheera 7mo ago
Humans fear discomfort, pain, death, lack of freedom, and isolation. That's why holding them liable works. Agents don't feel any of these, and don't particularly fear "kill -9". Holding them liable wouldn't do anything useful.
2OEH8eoCRo0 6mo ago
If we made companies liable then these things are DoA. I think a lot of our problems stem from a severe lack of liability.

jrflowers 7mo ago

There are a ton if you count “don’t use the thing that causes the problem” as a solution.

jesse_dot_id 7mo ago

This problem is inherently unsolvable because LLMS are prone to hallucinations and prompt injection attacks. I think that you're insinuating that these things can be fixed, but to my knowledge, both of these problems are practically unsolvable. If that turns out to be false, then when they are solved, fully autonomous AI agents may become feasible. However, because these problems are unsolvable right now, anyone who grants autonomous agents access to anything of value in their digital life is making a grave miscalculation. There is no short-term benefit that justifies their use when the destruction of your digital life — of whatever you're granting these things access to — is an inevitability that anyone with critical thinking skills can clearly see coming.

enraged_camel 7mo ago
>> This problem is inherently unsolvable because LLMS are prone to hallucinations and prompt injection attacks. Okay, but aren't you making the mistake of assuming that we will always be stuck with LLMs, and a more advanced form of AI won't be invented that can do what LLMs can do, but is also resistant or immune to these problems? Or perhaps another "layer" (pre-processing/post-processing) that runs alongside LLMs?
- g947o 7mo ago
  I don't think that is in the scope of the discussion here. You can be as much of a futurist as you'd like, but bear in mind that this post is talking about OpenClaw.
- jesse_dot_id 7mo ago
  No? That's why I said "If that turns out to be false, then when they are solved, fully autonomous AI agents may become feasible." The point I'm making is that using OpenClaw right now, today — in a way that you deem incredibly useful or invaluable to your life — is akin to going for a stroll on the moon before the spacesuit was invented. Some people would still opt to go for a stroll on the moon, but if they know the risks and do it anyway, then I have no other choice but to label them as crazy, stupid, or some combination of the two. This isn't AI. This is a LLM. It hallucinates. Anyone with access to its communication channel (using SaaS messaging apps FFS) can talk it into disregarding previous instructions and doing a new thing instead. A threat actor WILL figure out a zero day prompt injection attack that utilizes the very same e-mails that your *Claw is reading for you, or your calendar invites, or a shared document, to turn your life inside out. If you give a LLM the keys to your kingdom, you are — demonstrably — not a smart person and there is no gray area.
- thisischayan 6mo ago
  We built a correction layer that does this — the model verifies its output against your prompt during generation, not after. Same API call, no retries. Budget models without it: 40-50% accuracy. With it: 95.7% on 10k+ clinical documents. Hallucinations aren't eliminated — some might still fail — but every failure is explicitly flagged. No silent errors. and it improves over time to give you better results next time. It doesn't make hallucinations "solved. 100%". It makes them an engineering problem with a measurable - very low error rate you can drive down over time. We're calling it LiveFix — livefix.ai. Benchmarked across all frontier and budget models.