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ChatGPT agent: bridging research and action

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Re: ChatGPT agent: bridging research and action

#311

Post by pbh101 »

prettyblocks wrote: post #250
imiric wrote: post #238

Earlier quoted context omitted.

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.

Given how well it seems to be going in those specific areas, it seems like it's more of a regulatory issue than a technological one.

This is a big moving of the goalposts. The optimists were saying Level 5 would be purchasable everywhere by ~2018. They aren’t purchasable today, just hail-able. And there’s a lot of remote human intervention.

And San Francisco doesn’t get snow.

Re: ChatGPT agent: bridging research and action

#312

Post by stockresearcher »

simantel wrote: post #197
ricardobayes wrote: post #76

Earlier quoted context omitted.

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.

> 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.

The typical Lyft vehicle is a piece of junk worth less than $20k, while the typical Waymo vehicle is a pretend luxury car with $$$ of equipment tacked on.

Waymo needs to be proving 5-10x the number of daily rides as Lyft before we get excited

Re: ChatGPT agent: bridging research and action

#313

Post by imiric »

bugbuddy wrote: post #278
imiric wrote: post #259

Earlier quoted context omitted.

> 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 proble…

Right. I do think that just the capability to find and generate interesting patterns from existing data can be very valuable. It has many applications in many fields, and can genuinely be transformative for society.

But, yeah, the question is whether that approach can be defined as intelligence, and whether it can be applicable to all problems and tasks. I'm highly skeptical of this, but it will be interesting to see how it plays out.

I'm more concerned about the problems and dangers of this tech today, than whatever some entrepreneurs are promising for the future.

Re: ChatGPT agent: bridging research and action

#315

Post by loloquwowndueo »

Terretta wrote: post #285
OtherShrezzing wrote: post #281

Earlier quoted context omitted.

I’ve never experienced an intern who was remotely as mediocre and incapable of growth as an LLM.

What about a coach's ability for improving instruction?

What about it?

Re: ChatGPT agent: bridging research and action

#316

Post by SchemaLoad »

slg wrote: post #225
Aurornis wrote: post #127

Earlier quoted context omitted.

> 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... This is where the AI hype bites people. A great use of AI in this situation would be to automate the collection and checking of data. Se…

The proper use of these systems is to treat them like an intern or new grad hire. You can give them the work that none of the mid-tier or senior people want to do, thereby speeding up the team. But you will have to review their work thoroughly because there is a good chance they have no idea what they are actually doing. If you give them mission-critical work that demands accuracy or just let them have free rein with…

Isn't the point of an intern or new grad that you are training them to be useful in the future, acknowledging that for now they are a net drain on resources.

Re: ChatGPT agent: bridging research and action

#317

Post by mentalpiracy »

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 it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the time consuming work, that will save you a ton of time"

"Hello, yes, I would like to pollute my entire data store" is an insane a sales pitch. Start backing up your data lakes on physical media, there is going to be an outrageous market for low-background data in the future.

semi-related: How many people are going to get killed because of this?

Re: ChatGPT agent: bridging research and action

#318

Post by skydhash »

closewith wrote: post #231
throw-qqqqq wrote: post #215

Earlier quoted context omitted.

> Humans don't even have a 99.99% success rate in breathing Will you please elaborate a little on this?

Humans cough or otherwise have to clear their airways about 1 in every 1,000 breaths, which is a 99.9% success rate.

That’s quite good given the complexity and fragility of the system and the chaotic nature of the environment.

Re: ChatGPT agent: bridging research and action

#319

Post by samtp »

stpedgwdgfhgdd wrote: post #191
samtp wrote: post #82

Earlier quoted context omitted.

This is the exact same issue that I've had trying to use LLMs for anything that needs to be precise such as multi-step data pipelines. The code it produces will look correct and produce a result that seems correct. But when you do quality checks on the end data, you'll notice that things are not adding up. So then you have to dig into all this overly verbose code to identify the 3-4 subtle flaws with how it transform…

In my experience using small steps and a lot of automated tests work very well with CC. Don’t go for these huge prompts that have a complete feature in it. Remember the title “attention is all you need”? Well you need to pay a lot of attention to CC during these small steps and have a solid mental model of what it is building.

Yeah but once you break things down into small enough steps you might as well just code it yourself.

Re: ChatGPT agent: bridging research and action

#320

Post by bluefirebrand »

Terretta wrote: post #285
OtherShrezzing wrote: post #281

Earlier quoted context omitted.

I’ve never experienced an intern who was remotely as mediocre and incapable of growth as an LLM.

What about a coach's ability for improving instruction?

The point of coaching a Junior is so they improve their skills for next time

What would be the point of coaching an LLM? You will just have to coach it again and again

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