I've been talking up the idea of finally settling on a PE certification for software engineers (in the U.S.). It seems like most of the risks and responsibilities being discussed in the context of government regulations could be addressed with mechanisms similar to what we rely on for aircraft, bridges, power plants, etc. -- all those areas have processional credentialing in addition to bureaucratic oversight.
Ask HN: How to Break into AI Engineering
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Re: Ask HN: How to Break into AI Engineering
#12I've been talking up the idea of finally settling on a PE certification for software engineers (in the U.S.). It seems like most of the risks and responsibilities being discussed in the context of government regulations could be addressed with mechanisms similar to what we rely on for aircraft, bridges, power plants, etc. -- all those areas have processional credentialing in addition to bureaucratic oversight.
They tried it from 2013 to 2019 with a total of 81 candidates, and it's been discontinued for lack of interest.
Re: Ask HN: How to Break into AI Engineering
#13AI Engineering is basically Data Engineering focused on AI. When in "traditional" Data Engineering you create pipelines that store processed data in something like a Data Lake, in AI Eng. your end storage might be a specialized Feature Storage (like Feast or GCP Vertex AI).
There are some AI Engineers with strong scientific/mathematical background, but that's rare. Usually, you're paired with these ML people that actually develop and evaluate the models.
So my advice is to start with Data Engineering and then find a specialization AI. You should have a VERY solid foundation on scripting and programming, specially Python. Also, a lot of concepts of "data wrangling". Understanding how data flows from point A to point B, how the intermediate storages and streaming engines work, etc. Functional programming is key here.
Re: Ask HN: How to Break into AI Engineering
#14Assuming you have the math and algorithmic background, I would start by reading the “attention is all you need” paper. After reading, attempt to build a baby transformer model in PyTorch. After that, consider constructing some of the building blocks without libraries to understand how they work.
I read this exact advice often here on HN and I can’t help but wonder.
Is the person writing it just repeating something they read? Is it just because they like the ´coding from first principles’ aesthetics?
I mean let’s imagine that someone does read that paper, and manage to replicate the code (quite an effort from someone coming from outside AI and academia).
Then what? I doubt it’s particularly illuminating. That doesn’t really qualify for a job by itself. So what’s the goal there? Is it just a thing to say to look like a cool hacker that code from scratch?
Re: Ask HN: How to Break into AI Engineering
#15Assuming you have the math and algorithmic background, I would start by reading the “attention is all you need” paper. After reading, attempt to build a baby transformer model in PyTorch. After that, consider constructing some of the building blocks without libraries to understand how they work.
I read this exact advice often here on HN and I can’t help but wonder. Is the person writing it just repeating something they read? Is it just because they like the ´coding from first principles’ aesthetics? I mean let’s imagine that someone does read that paper, and manage to replicate the code (quite an effort from someone coming from outside AI and academia). Then what? I doubt it’s particularly illuminating. That…
The goal here is to actually understand the mechanics of the model and begin the process of intuitively understanding the space. I would put the effort here at a few weekends of focus.
Also will add the models turned out to be a lot simpler to understand than I expected going in.
Re: Ask HN: How to Break into AI Engineering
#16I wrote something a bit ago to answer this question: https://llm-utils.org/AI+Learning+Curation
It was previously popular on HN though only inside a comment thread, and I haven't submitted it as a link post yet.
Re: Ask HN: How to Break into AI Engineering
#17Assuming you have the math and algorithmic background, I would start by reading the “attention is all you need” paper. After reading, attempt to build a baby transformer model in PyTorch. After that, consider constructing some of the building blocks without libraries to understand how they work.
I read this exact advice often here on HN and I can’t help but wonder. Is the person writing it just repeating something they read? Is it just because they like the ´coding from first principles’ aesthetics? I mean let’s imagine that someone does read that paper, and manage to replicate the code (quite an effort from someone coming from outside AI and academia). Then what? I doubt it’s particularly illuminating. That…
I’m an ML engineer and frankly that paper is not very good in my opinion. It’s quite confusing. The BERT paper is much more approachable.
Re: Ask HN: How to Break into AI Engineering
#18Check out the Huggingface NLP course: https://huggingface.co/learn/nlp-course/chapter1/1
Huggingface has a bunch of courses, but that's a good one to start with. You can do the exercises on your own computer or on a cloud server if you want access to a more powerful GPU. If you go through these courses and pay attention you'll be in a really good position.
Re: Ask HN: How to Break into AI Engineering
#19Maybe a little bit of a contrarian idea, but I would be really leery of trying to become an "AI engineer" now. There is a possibility that we are at the apex of this cycle of AI (if you look at history, you will see AI goes in cycles), and we will run into more and more limitations.
Instead, of targeting AI engineering, I would focus on obtaining a solid mathematics background (calculus, linear algebra, discrete mathematics) and a solid computer science background (algorithms, data structures, distributed systems, databases/data storage/data retrieval).
Then with those skills, you can easily become a "SW Engineer who leverages AI" which in my guess will be a much better job and more stable than "AI Engineer"
Re: Ask HN: How to Break into AI Engineering
#20I've been talking up the idea of finally settling on a PE certification for software engineers (in the U.S.). It seems like most of the risks and responsibilities being discussed in the context of government regulations could be addressed with mechanisms similar to what we rely on for aircraft, bridges, power plants, etc. -- all those areas have processional credentialing in addition to bureaucratic oversight.
They tried it from 2013 to 2019 with a total of 81 candidates, and it's been discontinued for lack of interest.
Source for folks: https://ncees.org/ncees-discontinuing-pe-software-engineerin...