I predict Cognitive Engineer / Cognitive Architect will become a thing.
And it will have nothing to do with actual cognitive science, just like neural networks, artificial intelligence, and machine learning.
The Rise of the AI Engineer
141–150 of 159 posts
Re: The Rise of the AI Engineer
#142There'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…
You could have just read the article to see what the author meant by AI Engineers. You also would have seen that the entire article was addressing a point you tried to make, and you could have responded to the arguments made in the article instead of, ya know, just sounding off based on having read nothing but the headline
I have read the article (though I will admit, quite quickly). The author's definition for AI is by any means not the single one out there, as they outlined themselves. I disagree with the premise that this will be the job of the decade, and I disagree with the premise that it is inherently different from the rest of software as a service. This is a tool, that can be used to solve certain problems, I doubt there is a useful differentiation. That's my point of view, it is antagonistic to what is presented there, and I don't see why you think it departs from usefully commenting on the article.
Re: The Rise of the AI Engineer
#143I'm not sure I agree with their reasoning. There are a lot of generalist backend/infra engineers who are working in the AI space. What is the special skillset that distinguishes them from all others? If you say that they are "AI engineers" because they are working on AI as a product, then should we also have "advertising engineers", "billing engineers", "API engineers"? The reality is that tons of people just build a…
Tech companies ARE doing that.
I have met "Customer Success Engineers" and other managerial or marketing related roles with the moniker Engineer. People want to call themselves engineers.
Re: The Rise of the AI Engineer
#144Earlier quoted context omitted.
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 extra…
You are talking from a top-down point of view. Of course they can make an error any time, after all they stochastically sample the output. All approaches to information extraction are upper bounded at 90-95% accuracy, I have extensive experience with this task and run many evaluations on invoices, receipts, forms and other doctypes. Human in the loop is still required.
But in practice you can rely on good copying and excellent ability to parse names, addresses and various values as good or better than other approaches. LLMs reduce the number of corrections, and they are easier to deploy - instead of labeling hundreds of documents you can just query with the field name.
Re: The Rise of the AI Engineer
#145Earlier quoted context omitted.
Imagine comparing blockchain and AI.
It'll be fun to look back on these comments in a few years. It will be like looking back on the internet skeptics of the 90s. Most people have forgotten about those. Of course, there was a big boom and bust cycle back then too, but just like then, this cycle is nowhere near its peak.
That's what they said about the coins and the tokens too.
Re: The Rise of the AI Engineer
#146Tl; dr: a bunch of know-nothing plumbers swerve their digital cars from last years buzzword (blockchain) towards AI, narrowly missing a collision with a crowd of VCs. Upon arriving at the AI convention they switch hats to AI where they list themselves as experts (they can use the Chat-GPT API.) How any of this works or what problems may arise are a job for the cleanup crew (paid less, they aren't calling themselves e…
This is unnecessarily combative though it’s also probable I’m reading too much into this since I’m one of those swervers - from cloud computing guru to AI aficionado.
Personally, my mental bent is towards tinkering - I like wiring things up to make them work. I used to do that with wires and screwdrivers as a kid, now I read api docs and do the same thing.
The point being, it’s likely that I’ll continue connecting things to each other just to see how they work and offer that as a service until the day I die.
You need people who invent the algos, people to wire up algos to each other, people to sell this service to people, people to want to pay for that service, and so on. None is better than the other. They’re all necessary for people to put food on the table and live the life they want. Sneering at them is pointless.
Re: The Rise of the AI Engineer
#147Earlier quoted context omitted.
Imagine comparing blockchain and AI.
LLMs and GenAI are already useful at scale but the current hype that they will lead to infinitely generalizable models, myriad groundbreaking applications in all fields and industries, or even AGI could be overblown - let's at least admit that as a possibility.
If AGI reached "human level" capabilities and took off from there how in the world could that possibly be overblown? That would change everything, comparing it to discovering fire would probably be apt, and maybe the first time in recorded history that making that statement isn't overly dramatic.
Re: The Rise of the AI Engineer
#148Earlier quoted context omitted.
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.
LLMs today are great for certain use cases, which is amazing when it suits your needs. Need to extract a hotel name, city, address and confirmation number from emails and return it as JSON? Not a problem. Need it to validate postal codes in Canada? It's the wrong tool.
Re: The Rise of the AI Engineer
#149Earlier quoted context omitted.
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.
The thing is it can be used to get rid of the tedious and error-prone busywork. Instead of having highly paid accountants manually type monetary amounts into SAP, the accountants can now just look over and check if the AI was accurate in transcription.
Re: The Rise of the AI Engineer
#150Earlier quoted context omitted.
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.
The thing is it can be used to get rid of the tedious and error-prone busywork. Instead of having highly paid accountants manually type monetary amounts into SAP, the accountants can now just look over and check if the AI was accurate in transcription.
Why AI, though? Why not OCR and regular software? What does AI bring to this table?
Except for VC money.