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Am I the only one who thinks the AI doomsayers are even more ridiculous than the AI cheerleaders? ChatGPT may be useful and so on, but dear god. It's still jus

Am I the only one who thinks the AI doomsayers are even more ridiculous than the AI cheerleaders? ChatGPT may be useful and so on, but dear god. It's still just a fucking chat bot. We need to regulate AI and get better at building safe AI systems. Especially for things like facial recognition, self-driving cars, hyper-targeted advertising / engagement hacking, and the like. But "slow down" is such a ridiculous framing. The issues with these systems are obvious to everyone, and addressing those issues is a deeply technical and deeply difficult problem. We need to be throwing money at computer scientists to help build safety engineering tools and best practices. Hand-wringing over obvious faults by philosophers is not helpful, nor is burying our heads it the sand and going full Amish but with 2016 as our "just the right amount of technology" basline. I hope in five year we remember that the non-technical journalist class lost their god damned minds over what ultimately amounted to be a mildly useful parlor trick.

heyitsguay 4y ago
Thank you, you said it better than I did replying to another comment, but I feel about the same. It's disheartening how many outlets we have on social media to engage with big exciting narratives that are just detached from reality, and now here's one more.
deleted 4y ago
[deleted]
lwhi 4y ago
I'd like to think this is just a fad (like Blockchain for instance) .. but there's such tangible application for LLMs that I think for once the hype is justified.
- thwayunion 4y ago
  This is more a statement about how bad technology hype has gotten of late. Having "tangible applications" is a very low bar. If we paused for every technology that has "tangible applications" we'd probably be entering the bronze age any moment now.
  - ninjasaid13 4y ago
    Which overhyped technology has tangible applications like LLM?
- KevinEldon 4y ago
  The blockchain hype was in pitching a solution to every problem in an effort to get rich quick. The technology still has application for verification and ultra-micro transactions. I expect it will be foundational within before the end of the decade.
dwohnitmok 4y ago
> The issues with these systems are obvious to everyone, and addressing those issues is a deeply technical and deeply difficult problem. We need to be throwing money at computer scientists to help build safety engineering tools and best practices. Doesn't this go hand-in-hand with slowing AI research down and focusing more on safety engineering and best practices? I think everyone in the AI safety community is very very much onboard with "We need to be throwing money at computer scientists to help build safety engineering tools and best practices," but the current challenge is how to build the societal incentive structures to make that happen. Right now the overwhelming majority of prestige and money is in making AI more capable, not in safety engineering and best practices.
- thwayunion 4y ago
  > Doesn't this go hand-in-hand with slowing AI research down and focusing more on safety engineering and best practices? I don't see how this is given. It could very well be the opposite. Consider self driving, for example. Better object detection makes the system safer, full stop. It's on the AI safety folks to keep up with building good analyses for SoTA. Suspending all future improvements to object detection until we can better understand fault models of existing systems could very well make everyone less safe. > but the current challenge is how to build the societal incentive structures to make that happen. Right now the overwhelming majority of prestige and money is in making AI more capable, not in safety engineering and best practices. Slowing down doesn't address that problem at all. The answer here is regulation and accountability, which may or may not have the side-effect of slowing down deployments. But slowing down for the sake of slowing down is a non-solution unless you're a Philosophy major who watches too many movies.
  - dwohnitmok 4y ago
    > It's on the AI safety folks to keep up with building good analyses for SoTA. Suspending all future improvements to object detection until we can better understand fault models of existing systems could very well make everyone less safe. Sure. That's certainly the responsibility of AI safety folks. The only problem is that there are too few of them relative to people trying to make AI more capable. How do we get society to agree to funnel more resources into AI safety? > Slowing down doesn't address that problem at all. The answer here is regulation and accountability, which may or may not have the side-effect of slowing down deployments. I don't think your viewpoint and the article's viewpoint (or at least Ding's viewpoint), despite its snappy title, are really that far apart. Ding isn't saying that slowing down is intrinsically good, but rather, in his words: > If you’re a tech company, if you’re a policymaker, if you’re someone who wants your country to benefit the most from AI, investing in safety regulations could lead to less public backlash and a more sustainable long-term development of these technologies which sounds pretty similar to what you're saying. Yes a likely outcome of that is slowing down AI development, but it's not the goal itself per se. The gist of it is that we have a social problem. How do we coordinate to make sure that we develop AI safely? Because a free-for-all arms race where everyone cares only about the next shiny new capability seems really dangerous. Maybe the answer is regulation, but even then there are all sorts of questions of enforcement regimes and the like.
aaron695 4y ago
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boringuser1 4y ago
[dead]
dTal 4y ago
You are underestimating the scale of the tectonic shift. A computer program that can pass the god damned Turing test is not "a mildly useful parlor trick", it is the single most impressive computer program ever made. It exhibits reasoning, it can think with analogies. You can give it complicated requests in natural language. Given suitable prodding, it's creative. Everyone just woke up to the fact that we're a sneeze away from AGI. >The issues with these systems are obvious to everyone They are not. Already people routinely ask ChatGPT for factual info, and it doesn't bother them that it will simply make things up. It walks and quacks like a duck, so people assume it's a duck. >addressing those issues is a deeply technical and deeply difficult problem Alignment is a deeply difficult problem for philosophical reasons - we don't know how to reliably "align" humans either - but getting LMMs to output "roughly" what we want is fun and easy (they're like virtual humans!) and they're going to be deployed everywhere, problems notwithstanding. Things are about to change, big time. In the short term we're only talking about something like the smartphone revolution, where the parameters of social interaction are fundamentally reshaped. In the long term it could get real weird... I think it's pointless arguing about "slowing down", the cat is out of the bag. I would just like to see some transparency rules about weights and prompts - we're rapidly reaching a stage where a company hosting a highly used language model could do extreme violence to culture and business. Language models aren't paperclip maximizers - corporations are paperclip maximizers, and language models are the HypnoDrones.
- ninjasaid13 4y ago
  [flagged]
- thwayunion 4y ago
  People used to anthropomorphize Markov chains like this. I've been through this rodeo before, at least a few times. I did a little lab on GPT with middle schoolers as part of a Science enrichment activity. Without prompting, the entire class was making it say nonsense inside of the one hour session. Try using a GPT model to do something humans actually do, other than random bullshitting on the internet. Field customer service requests. Even carefully SFT'd models struggle to beat decision trees, and are sometimes worse, at actually solving the customer's problem. They sound more human / less robotic, but who cares if the customer's problem isn't solved and the dialog quickly diverges into insanity? Just because you want to see God on a piece of toast doesn't mean that the average human has completely lost their capacity for critical thought.

heyitsguay 4y ago

Thank you, you said it better than I did replying to another comment, but I feel about the same. It's disheartening how many outlets we have on social media to engage with big exciting narratives that are just detached from reality, and now here's one more.

deleted 4y ago

[deleted]

lwhi 4y ago

I'd like to think this is just a fad (like Blockchain for instance) .. but there's such tangible application for LLMs that I think for once the hype is justified.

thwayunion 4y ago
This is more a statement about how bad technology hype has gotten of late. Having "tangible applications" is a very low bar. If we paused for every technology that has "tangible applications" we'd probably be entering the bronze age any moment now.
- ninjasaid13 4y ago
  Which overhyped technology has tangible applications like LLM?
KevinEldon 4y ago
The blockchain hype was in pitching a solution to every problem in an effort to get rich quick. The technology still has application for verification and ultra-micro transactions. I expect it will be foundational within before the end of the decade.

dwohnitmok 4y ago

> The issues with these systems are obvious to everyone, and addressing those issues is a deeply technical and deeply difficult problem. We need to be throwing money at computer scientists to help build safety engineering tools and best practices. Doesn't this go hand-in-hand with slowing AI research down and focusing more on safety engineering and best practices? I think everyone in the AI safety community is very very much onboard with "We need to be throwing money at computer scientists to help build safety engineering tools and best practices," but the current challenge is how to build the societal incentive structures to make that happen. Right now the overwhelming majority of prestige and money is in making AI more capable, not in safety engineering and best practices.

thwayunion 4y ago
> Doesn't this go hand-in-hand with slowing AI research down and focusing more on safety engineering and best practices? I don't see how this is given. It could very well be the opposite. Consider self driving, for example. Better object detection makes the system safer, full stop. It's on the AI safety folks to keep up with building good analyses for SoTA. Suspending all future improvements to object detection until we can better understand fault models of existing systems could very well make everyone less safe. > but the current challenge is how to build the societal incentive structures to make that happen. Right now the overwhelming majority of prestige and money is in making AI more capable, not in safety engineering and best practices. Slowing down doesn't address that problem at all. The answer here is regulation and accountability, which may or may not have the side-effect of slowing down deployments. But slowing down for the sake of slowing down is a non-solution unless you're a Philosophy major who watches too many movies.
- dwohnitmok 4y ago
  > It's on the AI safety folks to keep up with building good analyses for SoTA. Suspending all future improvements to object detection until we can better understand fault models of existing systems could very well make everyone less safe. Sure. That's certainly the responsibility of AI safety folks. The only problem is that there are too few of them relative to people trying to make AI more capable. How do we get society to agree to funnel more resources into AI safety? > Slowing down doesn't address that problem at all. The answer here is regulation and accountability, which may or may not have the side-effect of slowing down deployments. I don't think your viewpoint and the article's viewpoint (or at least Ding's viewpoint), despite its snappy title, are really that far apart. Ding isn't saying that slowing down is intrinsically good, but rather, in his words: > If you’re a tech company, if you’re a policymaker, if you’re someone who wants your country to benefit the most from AI, investing in safety regulations could lead to less public backlash and a more sustainable long-term development of these technologies which sounds pretty similar to what you're saying. Yes a likely outcome of that is slowing down AI development, but it's not the goal itself per se. The gist of it is that we have a social problem. How do we coordinate to make sure that we develop AI safely? Because a free-for-all arms race where everyone cares only about the next shiny new capability seems really dangerous. Maybe the answer is regulation, but even then there are all sorts of questions of enforcement regimes and the like.

aaron695 4y ago

[dead]

boringuser1 4y ago

[dead]

dTal 4y ago

You are underestimating the scale of the tectonic shift. A computer program that can pass the god damned Turing test is not "a mildly useful parlor trick", it is the single most impressive computer program ever made. It exhibits reasoning, it can think with analogies. You can give it complicated requests in natural language. Given suitable prodding, it's creative. Everyone just woke up to the fact that we're a sneeze away from AGI. >The issues with these systems are obvious to everyone They are not. Already people routinely ask ChatGPT for factual info, and it doesn't bother them that it will simply make things up. It walks and quacks like a duck, so people assume it's a duck. >addressing those issues is a deeply technical and deeply difficult problem Alignment is a deeply difficult problem for philosophical reasons - we don't know how to reliably "align" humans either - but getting LMMs to output "roughly" what we want is fun and easy (they're like virtual humans!) and they're going to be deployed everywhere, problems notwithstanding. Things are about to change, big time. In the short term we're only talking about something like the smartphone revolution, where the parameters of social interaction are fundamentally reshaped. In the long term it could get real weird... I think it's pointless arguing about "slowing down", the cat is out of the bag. I would just like to see some transparency rules about weights and prompts - we're rapidly reaching a stage where a company hosting a highly used language model could do extreme violence to culture and business. Language models aren't paperclip maximizers - corporations are paperclip maximizers, and language models are the HypnoDrones.

ninjasaid13 4y ago
[flagged]
thwayunion 4y ago
People used to anthropomorphize Markov chains like this. I've been through this rodeo before, at least a few times. I did a little lab on GPT with middle schoolers as part of a Science enrichment activity. Without prompting, the entire class was making it say nonsense inside of the one hour session. Try using a GPT model to do something humans actually do, other than random bullshitting on the internet. Field customer service requests. Even carefully SFT'd models struggle to beat decision trees, and are sometimes worse, at actually solving the customer's problem. They sound more human / less robotic, but who cares if the customer's problem isn't solved and the dialog quickly diverges into insanity? Just because you want to see God on a piece of toast doesn't mean that the average human has completely lost their capacity for critical thought.