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ChatGPT agent: bridging research and action

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Re: ChatGPT agent: bridging research and action

#271

Post by bo1024 »

NortySpock wrote: post #260
ivape wrote: post #196

Earlier quoted context omitted.

”The people who YOLO it with prompting cycles until the code passes tests and then submit a PR are causing problems almost as fast as they’re developing new features in non-trivial codebases.” This might as well be the new definition of “script kiddie”, and it’s the kids that are literally going to be the ones birthed into this lifestyle. The “craft” of programming may not be carried by these coming generations and p…

Oh come on, people have been writing code with bad, incomplete, flaky, or absent tests since automated testing was invented (possibly before). It's having a good, useful and reliable test suite that separates the sheep from the goats.* Would you rather play whack-a-mole with regressions and Heisenbugs, or ship features? * (Or you use some absurdly good programing language that is hard to get into knots with. I've bee…

It sounds like you’re saying that good tests are enough to ensure good code even when programmers are unskilled and just rewrite until they pass the tests. I’m very skeptical.

Re: ChatGPT agent: bridging research and action

#272

Post by msgodel »

divan wrote: post #218

And I'm still waiting for the simple feature – the ability to edit documents in projects. I use projects for working on different documents - articles, research, scripts, etc. And would absolutely love to write it paragraph after paragraph with the help of ChatGPT for phrasing and using the project knowledge. Or using voice mode - i.e. on a walk "Hey, where did we finish that document - let's continue. Read the last…

It's crazy. Aider has been able to do this forever using free models but none of these companies will even let you pay for it in a phone/web app. I almost feel like I should start building my own service but I know any day now they'd offer it and I'd have wasted all that effort.

Re: ChatGPT agent: bridging research and action

#273

Post by superconduct123 »

ddp26 wrote: post #176

Predicted by the AI 2027 team in early April: > Mid 2025: Stumbling Agents The world sees its first glimpse of AI agents. Advertisements for computer-using agents emphasize the term “personal assistant”: you can prompt them with tasks like “order me a burrito on DoorDash” or “open my budget spreadsheet and sum this month’s expenses.” They will check in with you as needed: for example, to ask you to confirm purchases.…

Predicting 4-months into the future is not really that impressive

Re: ChatGPT agent: bridging research and action

#274

Post by pradn »

2oMg3YWV26eKIs wrote: post #167

The security risks with this sound scary. Let's say you give it access to your email and calendar. Now it knows all of your deepest secrets. The linked article acknowledges that prompt injection is a risk for the agent: > Prompt injections are attempts by third parties to manipulate its behavior through malicious instructions that ChatGPT agent may encounter on the web while completing a task. For example, a maliciou…

I can't imagine voluntarily giving access to my data and also being "scared". Maybe a tad concerned, but not "scared".

Re: ChatGPT agent: bridging research and action

#276

Post by WXLCKNO »

DanHulton wrote: post #208
2oMg3YWV26eKIs wrote: post #167

The security risks with this sound scary. Let's say you give it access to your email and calendar. Now it knows all of your deepest secrets. The linked article acknowledges that prompt injection is a risk for the agent: > Prompt injections are attempts by third parties to manipulate its behavior through malicious instructions that ChatGPT agent may encounter on the web while completing a task. For example, a maliciou…

There is almost guaranteed going to be an attack along the lines of prompt-injecting a calendar invite. Those things are millions of lines long already, with tones of auto-generated text that nobody reads. Embed your injection in the middle of boring text describing the meeting prerequisites and it's as good as written in a transparent font. Then enjoy exfiltrating your victim's entire calendar and who knows what els…

In the system I'm building the main agent doesn't have access to tools and must call scoped down subagents who have one or two tools at most and always in the same category (so no mixed fetch and calendar tools). They must also return structured data to the main agent.

I think that kind of isolation is necessary even though it's a bit more costly. However since the subagents have simple tasks I can use super cheap models.

Re: ChatGPT agent: bridging research and action

#277

Post by fragmede »

imiric wrote: post #238
simantel wrote: post #197

Earlier quoted context omitted.

> 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 Probably because it's just here now? More people take Waymo than Lyft each day in SF.

It's "here" if you live in a handful of cities around the world, and travel within specific areas in those cities. Getting this tech deployed globally will take another decade or two, optimistically speaking.

Most people live within a couple hours of a city though, and I think we'll see robot taxis in a majority of continents by 2035 though. The first couple cities and continents will take the longest, but after that it's just a money question, and rich people have a lot of money. The question then is: is the taxi cab consortium, which still holds a lot of power, despite Uber, in each city the in world, large enough to prevent Waymo from getting a hold, for every city in the world that Google has offices in.

Re: ChatGPT agent: bridging research and action

#278

Post by bugbuddy »

imiric wrote: post #259
ameliaquining wrote: post #157

Earlier quoted context omitted.

The Gartner hype cycle assumes a single fundamental technical breakthrough, and describes the process of the market figuring out what it is and isn't good for. This isn't straightforwardly applicable to LLMs because the question of what they're good for is a moving target; the foundation models are actually getting more capable every few months, which wasn't true of cryptocurrency or self-driving cars. At least some…

> If scaling doesn't stall out soon, then I honestly have no idea what to expect the visibility curve to look like. We are seeing diminishing returns on scaling already. LLMs released this year have been marginal improvements over their predecessors. Graphs on benchmarks[1] are hitting an asymptote. The improvements we are seeing are related to engineering and value added services. This is why "agents" are the latest…

The problem with LLMs and all other modern statistical large-data-driven solutions’ approach is that it tries to collapse the entire problem space of general problem solving to combinatorial search of the permutations of previously solved problems. Yes, this approach works well for many problems as we can see with the results with huge amount of data and processing utilized.

One implicit assumption is that all problems can be solved with some permutations of existing solutions. The other assumption is the approach can find those permutations and can do so efficiently.

Essentially, the true-believers want you to think that rearranging some bits in their cloud will find all the answers to the universe. I am sure Socrates would not find that a good place to stop the investigation.

Re: ChatGPT agent: bridging research and action

#279

Post by [deleted] »

ddp26 wrote: post #176

Predicted by the AI 2027 team in early April: > Mid 2025: Stumbling Agents The world sees its first glimpse of AI agents. Advertisements for computer-using agents emphasize the term “personal assistant”: you can prompt them with tasks like “order me a burrito on DoorDash” or “open my budget spreadsheet and sum this month’s expenses.” They will check in with you as needed: for example, to ask you to confirm purchases.…

[deleted]

Re: ChatGPT agent: bridging research and action

#280

Post by lotyrin »

slg wrote: post #246
chatmasta wrote: post #233

Earlier quoted context omitted.

Yeah, people complaining about accuracy of AI-generated code should be examining their code review procedures. It shouldn’t matter if the code was generated by a senior employee, an intern, or an LLM wielded by either of them. If your review process isn’t catching mistakes, then the review process needs to be fixed. This is especially true in open source where contributions aren’t limited to employees who passed a hi…

This is taking what I said further than intended. I'm not saying the standard review process should catch the AI generated mistakes. I'm saying this work is at the level of someone who can and will make plenty of stupid mistakes. It therefore needs to be thoroughly reviewed by the person using before it is even up to the standard of a typical employee's work that the normal review process generally assumes.

Yep, in the case of open source contributions as an example, the bottleneck isn't contributors producing and proposing patches, it's a maintainer deciding if the proposal has merit, whipping (or asking contributors to whip) patches into shape, making sure it integrates, etc. If contributors use generative AI to increase the load on the bottleneck it is likely to cause a negative net effect.
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