61–70 of 268 posts
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I have no idea what agents are for, could be my own ignorance. That said, I have been using LLMs for a while now with great benefit. I did not notice anything missing, and I am not sure what agents bring to the table. Do you know?
An agent is an LLM + a tool call loop - it is quite a step up in terms of value in my experience
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This is obviously AI generated, if that matters. And I have an AI workflow that generates much better posts than this.
The thing that sucks about it is maybe his english is bad (not his native language) so he relies on LLM output for his posts. Im inclined to cut people slack for this. But the rub is that it is indistinguishable from spam/slop generated for marketing/ads/whatever. Or it's possible that he is one of those people that _realy_ adopted LLMs into _all_ their workflow, I guess, and he thinks the output is good enough as is…
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An agent is an LLM + a tool call loop - it is quite a step up in terms of value in my experience
What is the use case? What does it solve exactly, or what practical value does it give you? I am not sure what a tool call loop is.
Earlier quoted context omitted.
I have no idea what agents are for, could be my own ignorance. That said, I have been using LLMs for a while now with great benefit. I did not notice anything missing, and I am not sure what agents bring to the table. Do you know?
An agent is an LLM + a tool call loop - it is quite a step up in terms of value in my experience
I do think it’s a step up when done correctly. Thinking of tools like Cursor. Most of my concern and issue comes from the amount of folks I have seen trying to great a system that solves everything. I know in my org people were working on Agents without even a problem they were solving for. They are effectively trying to recreate ChatGPT which to me is a fools errand.
Earlier quoted context omitted.
An agent is an LLM + a tool call loop - it is quite a step up in terms of value in my experience
What is the use case? What does it solve exactly, or what practical value does it give you? I am not sure what a tool call loop is.
No, it is not "mathematically impossible". It is empirically implausible. There is no statement in mathematics that says that agents can not have a 99.999% reliability rate. Also, if you look at any human process you will realize that none of them have a 100% reliability rate. Yet, even without that we can manufacture e.g. a plane, something which takes millions of steps, each without a 100% success rate. I actually…
This is a good point, but it seems, empirically, that most parts of a standard passenger airplane have reliability approximating 100% in a predefined time window with proper inspection and maintenance, otherwise passenger transit would be impossible. When the system does start to degrade, e.g. because replacement parts and maintenance becomes unavailable or too costly (cf. the use of imported planes by Russian airlin…
My point was that something extremely complex, like a plane, works, because the system tries hard to prevent compounding errors.
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An agent is an LLM + a tool call loop - it is quite a step up in terms of value in my experience
What is the use case? What does it solve exactly, or what practical value does it give you? I am not sure what a tool call loop is.
If 50% of training data is not factually accurate, this needs to be weeded out.
Some industries require a first principles approach, and there are optimal process flows that lead to accurate and predictable results. These need research and implementation by man and machine.
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Don't tell management about this, as they're all betting the house on AI agents next year.
Only one of these outcomes will be correct, so worth putting money on it if you think they're wrong a la The Big Short.
I don't think this one is worth shorting because there's no specific event to trigger the mindshare to start moving and validating your position. You'd have to wait for very big public failures before the herd start to move.