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The Rise of the AI Engineer

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Re: The Rise of the AI Engineer

#101

Post by ignoramous »

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…

> If you have React engineers, why couldn't you have AI engineers?

We most definitely could. That's one way to prop up a cottage industry, stay relevant, command hefty salaries, and maintain that charade of importance through complexity by creating Frankenstein features in search of problems and promotions.

Re: The Rise of the AI Engineer

#102

Post by staunton »

onion2k wrote: post #65
swyx wrote: post #45

Earlier quoted context omitted.

(author here) There are at least 4 killer apps ($100m/yr revenue potential) so far: 1. Generative Text for writing - Jasper AI going 0 to $75m ARR in 2 years 2. Generative Art for non-artists - Midjourney has by some accounts $80m ARR 3. Copilot for knowledge workers - GitHub’s Copilot has roughly 50-80m ARR as well 4. Conversational AI UX - ChatGPT probably has >$100m ARR by now, Bing Chat has brought $m's worth of…

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.

Re: The Rise of the AI Engineer

#103

Post by visarga »

cbm-vic-20 wrote: post #7

I'm a natural skeptic, and I believe we're still on the rising edge of the "AI" hype cycle. Five years ago, it was "blockchain", and everyone was trying to ram blockchain into everything, attracting lots of VC and media attention, etc. It seems that blockchain is beyond the honeymoon phase: I haven't seen an NFT or even a Bitcoin headline in HN for a while. So I'm trying to wrap my head around what an "AI Engineer" i…

When your task is too nuanced to be described in a prompt and a few demonstrations you need to use one of the fine-tuning scripts to bake into the model much more supervised data. That's still doable for AI Engineers, prepare data, call LoRA fine tuning script, deploy model.

The problem is having a good supervised training set. But recently it can be generated with LLMs + plugins and language chains, basically amplified LLMs. In other cases you need to collect human preference data and apply a different kind of fine-tuning. Still mostly dataset curation and iterative model building, something and AI Engineer should be able to do.

Working with LLMs is very different from building neural nets like in 2017. Tons of those old skills are not needed anymore, so many of the old tasks are basically solved at human level. And a whole new set of problems appeared.

Re: The Rise of the AI Engineer

#104

Post by staunton »

moffkalast wrote: post #58
swyx wrote: post #45

Earlier quoted context omitted.

(author here) There are at least 4 killer apps ($100m/yr revenue potential) so far: 1. Generative Text for writing - Jasper AI going 0 to $75m ARR in 2 years 2. Generative Art for non-artists - Midjourney has by some accounts $80m ARR 3. Copilot for knowledge workers - GitHub’s Copilot has roughly 50-80m ARR as well 4. Conversational AI UX - ChatGPT probably has >$100m ARR by now, Bing Chat has brought $m's worth of…

The tech problems will eventually get sorted out I'm sure, the most uncertain problems are legal. The world's copyright law is not even up to date enough to deal with the internet without crappy patchwork workarounds (like Youtube's contentID nonsense), much less LLMs. Steam just banned AI art and text assets and built in generators because they don't want the liability of hosting it. Midjourney is getting sued by Ge…

If people get used to LLMs governing their lives, those copyright laws will "just" be changed. People will not accept a legal challenge taking away their toys. Granted, we're not at that point yet. But the window for the legal stuff really making a difference is slowly closing. Meanwhile, the legal system is pretty slow.

Re: The Rise of the AI Engineer

#105

Post by ilaksh »

supportengineer wrote: post #11

There are a couple types of roles that sounds really interesting to me. One would be taking some proprietary data and training LLM in a format it could use. One company I know has a database of cars. They want to train their LLM with some inventory facts like "We have a Ford Mustang on the lot whose vin is ABC123 and it has the following features...". And then another role would be writing the prompts for API calls t…

What I have done for a similar use case is to have ChatGPT via the OpenAI API generate SQL (or KQL) based on the user request and then run that query and display the results (with some prose if appropriate). Works fairly well even with GPT-3.5-turbo. With GPT-4 can handle more complex requests (slower). It could even create a custom Chart.js chart on the fly if requested.

To me this demonstrates that there is a specific job here, even if you don't want to call it "engineering". Which I would argue is the correct category of job at least.

The above project was presented as "let's put a table of data in a vector database and then search it using the embedding of the user query". Here you were suggesting fine-tuning an LLM with the structured data. Again, it makes more sense to just generate the SQL and leave it in the relational database.

So there are a few basic things about how this stuff works that are not obvious and require some specialization. Even for programmers.

Right now I think it's fair enough to put it in its own job category since there are plenty of software engineers that just don't have any experience with generative AI. But within a few years, I think knowing how to integrate generative AI into a product will be considered core knowledge for a software engineer. So using LLMs or Stable Diffusion will become bullet points on a job requirements list.

Re: The Rise of the AI Engineer

#106

Post by ducharmdev »

riku_iki wrote: post #67
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.

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.

Re: The Rise of the AI Engineer

#107

Post by fuddle »

cbm-vic-20 wrote: post #7

I'm a natural skeptic, and I believe we're still on the rising edge of the "AI" hype cycle. Five years ago, it was "blockchain", and everyone was trying to ram blockchain into everything, attracting lots of VC and media attention, etc. It seems that blockchain is beyond the honeymoon phase: I haven't seen an NFT or even a Bitcoin headline in HN for a while. So I'm trying to wrap my head around what an "AI Engineer" i…

Bitcoin is probably a better comparison - https://trends.google.com/trends/explore?date=today%205-y&ge...

Re: The Rise of the AI Engineer

#108

Post by oblio »

mschuster91 wrote: post #79
swyx wrote: post #45

Earlier quoted context omitted.

(author here) There are at least 4 killer apps ($100m/yr revenue potential) so far: 1. Generative Text for writing - Jasper AI going 0 to $75m ARR in 2 years 2. Generative Art for non-artists - Midjourney has by some accounts $80m ARR 3. Copilot for knowledge workers - GitHub’s Copilot has roughly 50-80m ARR as well 4. Conversational AI UX - ChatGPT probably has >$100m ARR by now, Bing Chat has brought $m's worth of…

I'd add these use cases: 5. automated processing of unstructured paperwork and ingestion into ERP systems. Basically, upload any kind of bill and get all of the information into the system, not just "find out the total amount". That can save so much in accounting it's not even funny any more. 6. related to this, something that sorts incoming emails. Classify stuff into "look into it now " vs "look into it later" vs "…

My problem with this is that AI at the moment is a kind of 80% thing.

And you want to plug that into ERPs and accounting?!?

We don't even really understand its failure modes.

Re: The Rise of the AI Engineer

#109

Post by 0xEFF »

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.

Yes, it’s meaningful. If Google doesn’t fix search in the next decade then Bing (or some other winner) will be the service earning Google’s ARR in 11 hours.

Re: The Rise of the AI Engineer

#110

Post by bedobi »

ignoramous wrote: post #101
senko wrote: post #89

Earlier quoted context omitted.

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…

> If you have React engineers, why couldn't you have AI engineers? We most definitely could. That's one way to prop up a cottage industry, stay relevant, command hefty salaries, and maintain that charade of importance through complexity by creating Frankenstein features in search of problems and promotions.

like the canned messages that are increasingly finding themselves into any app where you can send messages to people, be it email, whatsapp, tinder, whatever

"Hey John! I see you like traveling, I love traveling too! What are some of the most memorable trips you've had?"

like, who would want to receive such an obviously canned message lol?

soon, it will just be the apps talking to each other, no humans required

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