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ChatGPT agent: bridging research and action

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Re: ChatGPT agent: bridging research and action

#101

Post by Topfi »

tomschwiha wrote: post #45
Topfi wrote: post #24

Earlier quoted context omitted.

Could you name which specific regulations that are applying to all EEA members those would be and why/how they also apply to Switzerland?

I think Switzerland is applying legal rules of Europe to maintain trading access and stay up to European standards.

Correct me, but I don't think such alignment between Switzerland and the rest of the EEA on LLM/"AI" technology does currently exist (though there may and likely will be some in the future) and it cannot explain the inevitable EEA wide release that is going to follow in a few weeks, as always. The "EU/EEA/European regulations prevent company from offering software product here" shouts have always been loud, no matter how often we see it turn out to have been merely a delayed launch with no regulatory reasoning.

If this had been specific to countries that have adopted the "AI Act", I'd be more than willing to accept that this delay could be due them needing to ensure full compliance, but just like in the past when OpenAI delayed a launch across EU member states and the UK, this is unlikely. My personal, though 100% unsourced thesis, remains, that this staggered rollout is rooted in them wanting to manage the compute capacity they have. Taking both the Americas and all of Europe on at once may not be ideal.

Re: ChatGPT agent: bridging research and action

#102

Post by exitb »

jstummbillig wrote: post #89
twalkz wrote: post #30

The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…

I am looking forward to learning why this is entirely unlike working with humans, who in my experience commit very silly and unpredictable errors all the time (in addition to predictable ones), but additionally are often proud and anxious and happy to deliberately obfuscate their errors.

You can point out the errors to people, which will lead to less issues over time, as they gain experience. The models however don’t do that.

Re: ChatGPT agent: bridging research and action

#103

Post by FergusArgyll »

pants2 wrote: post #70

I've been using OpenAI operator for some time - but more and more websites are blocking it, such as LinkedIn and Amazon. That's two key use-cases gone (applying to jobs and online shopping). Operator is pretty low-key, but once Agent starts getting popular, more sites will block it. They'll need to allow a proxy configuration or something like that.

If people will actually pay for stuff (food, clothing, flights, whatever) through this agent or operator, I see no reason Amazon etc would continue to block them.

Re: ChatGPT agent: bridging research and action

#105

Post by thewebguyd »

alach11 wrote: post #14

It's very hard for me to imagine the current level of agents serving a useful purpose in my personal life. If I ask this to plan a date night with my wife this weekend, it needs to consult my calendar to pick the best night, pick a bar and restaurant we like (how would it know?), book a babysitter (can it learn who we use and text them on my behalf?), etc. This is a lot of stuff it has to get right, and it requires a…

> It's very hard for me to imagine the current level of agents serving a useful purpose in my personal life. If I ask this to plan a date night with my wife this weekend, it needs to consult my calendar to pick the best night, pick a bar and restaurant we like (how would it know?), book a babysitter (can it learn who we use and text them on my behalf?), etc. This is a lot of stuff it has to get right, and it requires a lot of trust!

This would be my ideal "vision" for agents, for personal use, and why I'm so disappointed in Apple's AI flop because this is basically what they promised at last year's WWDC. I even tried out a Pixel 9 pro for a while with Gemini and Google was no further ahead on this level of integration either.

But like you said, trust is definitely going to be a barrier to this level of agent behavior. LLMs still get too much wrong, and are too confident in their wrong answers. They are so frequently wrong to the point where even if it could, I wouldn't want it to take all of those actions autonomously out of fear for what it might actually say when it messages people, who it might add to the calendar invites, etc.

Re: ChatGPT agent: bridging research and action

#106

Post by dingnuts »

ricardobayes wrote: post #76
twalkz wrote: post #30

The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…

Of course, Pareto principle is at work here. In an adjacent field, self-driving, they are working on the last "20%" for almost a decade now. It feels kind of odd that almost no one is talking about self-driving now, compared to how hot of a topic it used to be, with a lot of deep, moral, almost philosophical discussions.

The critics of the current AI buzz certainly have been drawing comparisons to self driving cars as LLMs inch along with their logarithmic curve of improvement that's been clear since the GPT-2 days.

Whenever someone tells me how these models are going to make white collar professions obsolete in five years, I remind them that the people making these predictions 1) said we'd have self driving cars "in a few years" back in 2015 and 2) the predictions about white collar professions started in 2022 so five years from when?

Re: ChatGPT agent: bridging research and action

#107

Post by bijant »

pants2 wrote: post #70

I've been using OpenAI operator for some time - but more and more websites are blocking it, such as LinkedIn and Amazon. That's two key use-cases gone (applying to jobs and online shopping). Operator is pretty low-key, but once Agent starts getting popular, more sites will block it. They'll need to allow a proxy configuration or something like that.

THIS is the main problem. I was listening the whole time for them to announce a way to run it locally or at least proxy through your local devices. Alas the Deepseek R1 distillation experience they went through (a bit like when Steve Jobs was fuming at Google for getting Android to market so quickly) made them wary of showing to many intermediate results, tricks etc. Even in the very beginning Operator v1 was unable to access many sites that blocked data-center IPs and while I went through the effort of patching in a hacky proxy-setup to be able to actually test real world performance they later locked it down even further without improving performance at all. Even when its working, its basically useless and its not working now and only getting worse. Either they make some kinda deal with eastdakota(which he is probably too savvy to agree to)or they can basically forget about doing web browsing directly from their servers.Considering, that all non web applications of "computer use" greatly benefit from local files and software (which you already have the license for!)the whole concept appears to be on the road to failure. Having their remote computer use agent perform most stuff via CLI is actually really funny when you remember that computer use advocates used to claim the whole point was NOT to rely on "outdated" pre-gui interfaces.

Re: ChatGPT agent: bridging research and action

#108

Post by gh0stcat »

travelalberta wrote: post #59
twalkz wrote: post #30

The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…

I think this is my favorite part of the LLM hype train: the butterfly effect of dependence on an undependable stochastic system propagates errors up the chain until the whole system is worthless. "I think it got 98% of the information correct..." how do you know how much is correct without doing the whole thing properly yourself? The two options are: - Do the whole thing yourself to validate - Skim 40% of it, 'seems…

I wonder if you can establish some kind of confidence interval by passing data through a model x number of times. I guess it mostly depends on subjective/objective correctness as well as correctness within a certain context that you may not know if the model knows about or not. Either way sounds like more corporate drudgery.

Re: ChatGPT agent: bridging research and action

#110

Post by bijant »

While they did talk about partial-mitigations to counter prompt-injection, highlighting the risks of cc numbers and other private information leaking, they did not address whether they would be handing all of that data over under the court-order to the NYT.
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