5 ms·

As someone who's been working on this space as their day job for the last several months, I can say that LLMs are SURPRISINGLY GOOD at this. The real challenge

by madrox 3y ago

As someone who's been working on this space as their day job for the last several months, I can say that LLMs are SURPRISINGLY GOOD at this. The real challenge is the sentiment you're articulating here...trust. I've been relating it to self-driving cars. I love the idea, but I'm going to be very anxious the first several times I climb into one to take me somewhere at freeway speeds. The biggest UX work in the short term is going to be around giving people the right amount of transparency so they still feel in control. The actual LLM work is relatively easy and impressive.

moffkalast 3y ago
How can you get transparency from an LLM? They're complete black boxes by architecture.
- AussieWog93 3y ago
  >How can you get transparency from an LLM? They're complete black boxes by architecture. You just ask them. I literally just prompted ChatGPT (3.5) to think about its answer again and explain what's wrong with it, and it did. Kept going 2 or 3 times, until it was sure it wasn't doing anything wrong, and magically the script it produced at that stage just worked.
  - a_bonobo 3y ago
    But can you believe that these are the correct explanations? Perhaps it just confabulated an explanation that sounds likely given your prompt, and is not the actual reason it told you what it did?
  - moffkalast 3y ago
    That'll just give you made up rationalizations, like asking a human to explain an emotional subconscious choice.
- deleted 3y ago
  [deleted]
- ignoramous 3y ago
  For inference? Not really. LLM observability startups are a thing. Arize.ai probably the most well known.
timetraveller26 3y ago
Haven't they recently discovered that Tesla crashes are far more frequent that previous estimations?
- greymalik 3y ago
  Whatever that number is, how does it compare to crashes based on human error?
  - ericbarrett 3y ago
    Tesla won't release the numbers so we don't know.
    - haliskerbas 3y ago
      It’s also weird to compare the Tesla to some ‘99 Toyota. Why not compare across the pool of cars that also have adaptive cruise control, lane keep assist, forward collision prevention, etc..?
  - jamilton 3y ago
    I recall the number of deaths from Tesla self-driving being reported as being 10x per mile as regular highway driving. I think it was this article, but it's paywalled. https://www.nytimes.com/2022/06/08/technology/tesla-autopilot-safety-data.html https://www.nytimes.com/2022/06/08/technology/tesla-autopilo...
scyzoryk_xyz 3y ago
I believe you. I think for at least some people this might be one of those generational differences. Wanting to do some things by hand might be increasingly a thing only people over a certain age do.
ignoramous 3y ago
I know from use that perplexity.ai (which builds atop GPT4) hallucinates very little compared to Bard and ChatGPT. What are some techniques that these products use apart from bounding context and prompt engineering? ReAct sounds like it might help: https://react-lm.github.io/ https://react-lm.github.io/
lsy 3y ago
Similar to self-driving cars, I think the last 1% of the way is going to be the near-insurmountable barrier that makes widespread implementation difficult or potentially impossible. For tasks where you can plausibly check the results with some kind of external software harness, or defer double-checking to a person, these models will make development quick (if resource-intensive). But any kind of fully-automated complex process where the consequences are important will be tough to hand over to black-box generators.
iudqnolq 3y ago
But is surprisingly good useful? Suppose you configure your inbox such that you unpredictably don't see a small percentage of important emails. Suppose you miss an email from your boss telling you a very important client needs you to fix a critical bug today, and as a result you start working on that bug slightly later when your boss contacts you another way. Your boss might tell you to uninstall your LLM and just read all your email
- foverzar 3y ago
  The same logic could be applicable to pretty much any other spam filtering mechanism.
  - iudqnolq 3y ago
    No, it's the same category, but the specific values makes all the difference. The logic depends on the probability of error, the predictability of error, and the social acceptability of error. By analogy it's socially more acceptable to have an outage because AWS is down than because insert_nich_provider is down even if insert_nich_provider has fewer outages. If insert_nich_provider has more outages it's even worse.

by madrox 3y ago

moffkalast 3y ago

How can you get transparency from an LLM? They're complete black boxes by architecture.

AussieWog93 3y ago
>How can you get transparency from an LLM? They're complete black boxes by architecture. You just ask them. I literally just prompted ChatGPT (3.5) to think about its answer again and explain what's wrong with it, and it did. Kept going 2 or 3 times, until it was sure it wasn't doing anything wrong, and magically the script it produced at that stage just worked.
- a_bonobo 3y ago
  But can you believe that these are the correct explanations? Perhaps it just confabulated an explanation that sounds likely given your prompt, and is not the actual reason it told you what it did?
- moffkalast 3y ago
  That'll just give you made up rationalizations, like asking a human to explain an emotional subconscious choice.
deleted 3y ago
[deleted]
ignoramous 3y ago
For inference? Not really. LLM observability startups are a thing. Arize.ai probably the most well known.

timetraveller26 3y ago

Haven't they recently discovered that Tesla crashes are far more frequent that previous estimations?

greymalik 3y ago
Whatever that number is, how does it compare to crashes based on human error?
- ericbarrett 3y ago
  Tesla won't release the numbers so we don't know.
  - haliskerbas 3y ago
    It’s also weird to compare the Tesla to some ‘99 Toyota. Why not compare across the pool of cars that also have adaptive cruise control, lane keep assist, forward collision prevention, etc..?
- jamilton 3y ago
  I recall the number of deaths from Tesla self-driving being reported as being 10x per mile as regular highway driving. I think it was this article, but it's paywalled. https://www.nytimes.com/2022/06/08/technology/tesla-autopilot-safety-data.html https://www.nytimes.com/2022/06/08/technology/tesla-autopilo...

scyzoryk_xyz 3y ago

I believe you. I think for at least some people this might be one of those generational differences. Wanting to do some things by hand might be increasingly a thing only people over a certain age do.

ignoramous 3y ago

I know from use that perplexity.ai (which builds atop GPT4) hallucinates very little compared to Bard and ChatGPT. What are some techniques that these products use apart from bounding context and prompt engineering? ReAct sounds like it might help: https://react-lm.github.io/ https://react-lm.github.io/

lsy 3y ago

Similar to self-driving cars, I think the last 1% of the way is going to be the near-insurmountable barrier that makes widespread implementation difficult or potentially impossible. For tasks where you can plausibly check the results with some kind of external software harness, or defer double-checking to a person, these models will make development quick (if resource-intensive). But any kind of fully-automated complex process where the consequences are important will be tough to hand over to black-box generators.

iudqnolq 3y ago

But is surprisingly good useful? Suppose you configure your inbox such that you unpredictably don't see a small percentage of important emails. Suppose you miss an email from your boss telling you a very important client needs you to fix a critical bug today, and as a result you start working on that bug slightly later when your boss contacts you another way. Your boss might tell you to uninstall your LLM and just read all your email

foverzar 3y ago
The same logic could be applicable to pretty much any other spam filtering mechanism.
- iudqnolq 3y ago
  No, it's the same category, but the specific values makes all the difference. The logic depends on the probability of error, the predictability of error, and the social acceptability of error. By analogy it's socially more acceptable to have an outage because AWS is down than because insert_nich_provider is down even if insert_nich_provider has fewer outages. If insert_nich_provider has more outages it's even worse.