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The Rise of the AI Engineer

latent.space

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Re: The Rise of the AI Engineer

#111

Post by z3c0 »

visarga wrote: post #100
rvz wrote: post #38

Earlier quoted context omitted.

We are indeed at the "Peak of Inflated Expectations" in the Garter hype cycle. Everyone is screaming that we are out of the AI winter and throwing LLMs at every problem. > What the LLM community needs now is for companies to leverage and productize these LLM models for truly game changing use cases. The killer serious use-case has always been summarization of existing text. That's it. Everything else is a constant fl…

Not just summarisation, information extraction in general. LLMs are great data normalisers.

No. No they are not. Do not keep proliferating this idea, as there are real consequences. Your input only informs the likelihood of the output. There is no model actually extrapolating rules from the information, so the premise of LLMs being extractive is 100% verifiably false. They summarize well due to being handed a roughly correct arrangement of tokens to mimic the order of. This should not be confused with extraction.

To put it simply, keep falling for that, and it'll bite you in the ass.

Re: The Rise of the AI Engineer

#112

Post by riku_iki »

ducharmdev wrote: post #106
riku_iki wrote: post #67

Earlier quoted context omitted.

but rate of growth is likely 100-1000 times higher

On a smaller time scale, is rate of growth that meaningful? I guess I'm just thinking, until we see the how this all pans out over the next decade, we don't really know if the current rate of growth will hold, or if it'll plateau/slow down.

> On a smaller time scale, is rate of growth that meaningful?

revenue in initial stage of extreme growth is much less meaningful.

Re: The Rise of the AI Engineer

#113

Post by swyx »

sanderjd wrote: post #73
swyx wrote: post #55

Earlier quoted context omitted.

we haven't launched it widely yet but if you peek at the top level nav you'll find the course we are working on :) https://www.latent.space/s/university

How about that! :) One interesting thing is that there do seem to be courses available for this, but I still haven't come across any books . Maybe this is just because I'm a dinosaur, but I really feel like what I'm missing is a book about this, with a good Introduction and Chapter 1 motivating the subject and giving a lay of the land. I'm sure every techie publisher will have one of these by the end of the year, but…

thank you! yeah i guess its easier to iterate on a course than a book, but ofc we are also effecitvely writing and market testing the book contents. having written my own book before i'm not particularly keen on doing that again but am trying to work with partners to do this :)

Re: The Rise of the AI Engineer

#114

Post by z3c0 »

intellectronica wrote: post #71

In my experience people who make dismissive comments about AI (in its current form) and AI Engineering as a discipline tend to have very little experience with and superficial understanding of AI. Once you start using it seriously as part of your engineering stack it quickly becomes clear that there’s a lot of detail and complexity that more than justify specialisation.

Heavily disagree, and this just seems like posturing from the other side of things. I understand AI rather heavily, and have been a part of the scene far before the explosion of even the first GPT model.

Frankly, I've been quite irked by all the people who claim themselves "ML engineer" when most of what they do is glue huggingface models together. They're doing none of the work required to make models, which is quite extensive. They understand very little about the models they wield.

This new wave, I find even more irksome. "Prompt engineer" and "AI engineer" and aren't much more than pseudoscientists who fanangle API inputs until they get what they want. This is in stark contrast to all the maths I perform to understand a model's performance.

Re: The Rise of the AI Engineer

#115

Post by sanderjd »

swyx wrote: post #113
sanderjd wrote: post #73

Earlier quoted context omitted.

How about that! :) One interesting thing is that there do seem to be courses available for this, but I still haven't come across any books . Maybe this is just because I'm a dinosaur, but I really feel like what I'm missing is a book about this, with a good Introduction and Chapter 1 motivating the subject and giving a lay of the land. I'm sure every techie publisher will have one of these by the end of the year, but…

thank you! yeah i guess its easier to iterate on a course than a book, but ofc we are also effecitvely writing and market testing the book contents. having written my own book before i'm not particularly keen on doing that again but am trying to work with partners to do this :)

Ha, totally get it.

Re: The Rise of the AI Engineer

#116

Post by intellectronica »

z3c0 wrote: post #114
intellectronica wrote: post #71

In my experience people who make dismissive comments about AI (in its current form) and AI Engineering as a discipline tend to have very little experience with and superficial understanding of AI. Once you start using it seriously as part of your engineering stack it quickly becomes clear that there’s a lot of detail and complexity that more than justify specialisation.

Heavily disagree, and this just seems like posturing from the other side of things. I understand AI rather heavily, and have been a part of the scene far before the explosion of even the first GPT model. Frankly, I've been quite irked by all the people who claim themselves "ML engineer" when most of what they do is glue huggingface models together. They're doing none of the work required to make models, which is quit…

I think you've just proven my point.

Re: The Rise of the AI Engineer

#117

Post by z3c0 »

intellectronica wrote: post #116
z3c0 wrote: post #114

Earlier quoted context omitted.

Heavily disagree, and this just seems like posturing from the other side of things. I understand AI rather heavily, and have been a part of the scene far before the explosion of even the first GPT model. Frankly, I've been quite irked by all the people who claim themselves "ML engineer" when most of what they do is glue huggingface models together. They're doing none of the work required to make models, which is quit…

I think you've just proven my point.

On reddit, this might seem like a burn, but here, you need to explain that claim and not just hope somebody rides with it. How is tinkering with an API an actual understanding of AI? Please actually explain

Re: The Rise of the AI Engineer

#118

Post by 29athrowaway »

senko wrote: post #89
charles_f wrote: post #66

There's a bit of snake oil in all of that. By any means ML is a very specialized subfield, where you need solid math basis and a deep understanding of the science behind it all. But I struggle to see the same thing for AI. If by "AI engineers" you mean someone who builds an LLM*, then it's very much just ML. If you mean someone who integrates with the LLM someone else built, then it's very much just backend work. Sur…

If you have React engineers, why couldn't you have AI engineers? I think the post is right to try to delineate the roles of "builds LLMs or other ML models" and "uses those models", as (as you noted) the skills required are very different (vs. "creates a JS framework" vs "uses a JS framework" are the same skills, just on another level). "AI engineer" is, as you say, inaccurate, but as swyx says, it's least cringy of…

Because AI as terminology is vague and can mean anything.

Graph search is AI, pathfinding is AI, decision trees are AI, fuzzy logic is AI, expert systems are AI, machine learning is AI.

Just say LLM analyst or whatever.

Re: The Rise of the AI Engineer

#119

Post by ImaCake »

staunton wrote: post #102
onion2k wrote: post #65

Earlier quoted context omitted.

75+80+80+100 is £335m per year in revenue. For a point of comparison, that's approximately 11 hours of Google's revenue.

Consider the possibility that may be a point in a technology's evolution where you can "look at what is being done with it" and conclude that it's useful from that , rather than just comparing revenue figures across domains.

Yeah the dollar values here are a distraction. I use copilot everyday at my Data Science job. Its useful!

What we are not considering is integrating a custom trained LLM into our work because the tech just isn’t there yet.

Re: The Rise of the AI Engineer

#120

Post by foobiekr »

z3c0 wrote: post #114
intellectronica wrote: post #71

In my experience people who make dismissive comments about AI (in its current form) and AI Engineering as a discipline tend to have very little experience with and superficial understanding of AI. Once you start using it seriously as part of your engineering stack it quickly becomes clear that there’s a lot of detail and complexity that more than justify specialisation.

Heavily disagree, and this just seems like posturing from the other side of things. I understand AI rather heavily, and have been a part of the scene far before the explosion of even the first GPT model. Frankly, I've been quite irked by all the people who claim themselves "ML engineer" when most of what they do is glue huggingface models together. They're doing none of the work required to make models, which is quit…

Strong agreement. What we have right now is a lot of people doing light glue code and pretending it is engineering.
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