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Ask HN: How to Break into AI Engineering

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Re: Ask HN: How to Break into AI Engineering

#51

Post by f38zf5vdt »

chrsig wrote: post #41
jahsome wrote: post #33

Earlier quoted context omitted.

Highjacking for self-edification as you led with math... Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves? I ask because I'm quite math averse (dyscalulia). I am self-taught engineer, largely because it became glaringly obvious I wasn't going to be able to comp…

>Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves? I'm definitely not any authority on the matter -- also self taught, but I don't think so. Having a conceptual understanding of the math is probably a really good idea, but I imagine there's quite a bit that can…

The maths are not actually that complicated. 99% of what pytorch is doing is matrix multiplication and addition with n-dimensional arrays (tensors). For backprop you need a very limited understanding of calculus. [1] Stuff like sigmoid/softmax is also straightforward and you can grok it from a 5 minute youtube video. [2] If something doesn't make sense, just ask ChatGPT to walk you through it.

There is a lot of other complicated math that you will need when reading papers because people writing AI papers like to overcomplicate a lot of things that can be represented in 5 lines of pytorch.

[1] https://towardsdatascience.com/understanding-backpropagation...

[2] https://www.youtube.com/watch?v=Qn4Fme1fK-M

Re: Ask HN: How to Break into AI Engineering

#52

Post by flashgordon »

jahsome wrote: post #33
__rito__ wrote: post #21

- Have crystal clear Mathematical foundations, as in why this formula/method the way it is, rather than being able to solve college/HS test problems. Really solid footing in Differential Calculus and Linear Algebra is necessary. - Know the Statistical language that you learn from a basic college-level Stat 101 course. Be able to translate normal sentences into those using Statistical notation, and be able to read eas…

Highjacking for self-edification as you led with math... Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves? I ask because I'm quite math averse (dyscalulia). I am self-taught engineer, largely because it became glaringly obvious I wasn't going to be able to comp…

Til I learnt about discalulia!! Interesting. I know math can cause anxiety in kids as/when there is an external "reward/loss" contingent on it. I wonder if that exists when those external incentives are removed?

I did a ee and cs degree in college and I hated the eng part of it. It was because I hated the exams which was mostly rote stuff. When I finished college though and started working in a job that had no linkage to ee I one day just picked up courses (which were just arbitrary web 1.0 sites by random folks) and started going through the (signal processing/kalman filtering/convolution) problems and implementing them in software which was a lot of fun to see in action.

Reason for that long winded one was, I was thinking in your case, would the anxiety still be there as now you (might) have a reason to develop passion for the math than back in school where it was forced without a reason?

Re: Ask HN: How to Break into AI Engineering

#53

Post by maypop »

__rito__ wrote: post #21

- Have crystal clear Mathematical foundations, as in why this formula/method the way it is, rather than being able to solve college/HS test problems. Really solid footing in Differential Calculus and Linear Algebra is necessary. - Know the Statistical language that you learn from a basic college-level Stat 101 course. Be able to translate normal sentences into those using Statistical notation, and be able to read eas…

Great post - thank you.

What directions can you head in AI Eng these days if you _dont_ want big tech?

Re: Ask HN: How to Break into AI Engineering

#54

Post by achileas »

jstx1 wrote: post #45
santiagobasulto wrote: post #13

AI 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 act…

> AI Engineering is basically Data Engineering focused on AI. I work in machine learning and this isn't how I see it at all. Data engineering specifically evolved as a term to differentiate the people who work with data but don't work on ML/AI.

I work in machine learning and also in data engineering, and for most of my career the data engineering title was for people doing everything in the lifecycle outside of R&D workflows (building the models/model architecture itself). It's only very recently differentiated to MLE/DE, and even that is far from being a standard.

The skillset is largely the same, but with some specialized knowledge for ML data work.

Re: Ask HN: How to Break into AI Engineering

#55

Post by achileas »

itake wrote: post #40
tjpnz wrote: post #25

Earlier quoted context omitted.

ML is a relatively new field. How do you think current engineers got their start?

5 years ago, you needed a masters or phd to qualify for a Data Science role. At my current company, that is still the case. Has that change?

DS roles aren't the only roles in the field available.

Re: Ask HN: How to Break into AI Engineering

#56

Post by __rito__ »

n4r9 wrote: post #36
jahsome wrote: post #33

Earlier quoted context omitted.

Highjacking for self-edification as you led with math... Is math going to become more important for software engineers in general, as AI is adopted in to more and more aspects of the SDLC, even if said engineers aren't working directly on the AI systems themselves? I ask because I'm quite math averse (dyscalulia). I am self-taught engineer, largely because it became glaringly obvious I wasn't going to be able to comp…

> Are my days numbered? Only in the sense that ultimately everyone's days are numbered. LLMs can suggest bits of code but there's no reason to believe that it can undertake large-scale, novel software engineering projects. In fact the lack of an underlying mental model makes me doubt that the LLM paradigm will ever get to that point. For the forseeable future I think there will always be a role for the person who can…

Copilot can absolutely do the jobs of Data Scientists who got hired based on some minimal skills that were considered valuable even three years back.

I have tried applying Copilot to my own work where it spews- garbage. But I use Copilot a lot to generate some example data, or write repetitive code- I needed a basic Flask frontend and I used Copilot to do 70% of the job. But it cannot yet solve Vision tasks.

> " I think there will always be a role for the person who can turn around and say"

These roles, if and when they start to exist, will exist in extremely tiny numbers. And they will all likely be hired from Stanford/Oxbridge/MIT/Caltech, and they will have PhDs.

If this scenario plays out, then, I am afraid for my future, too.

Re: Ask HN: How to Break into AI Engineering

#57

Post by rch »

techwizrd wrote: post #20
wlesieutre wrote: post #12

Earlier quoted context omitted.

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...

I'm familiar, but that definition wasn't well thought out.

Other approaches have been more widely adopted, like FINRA certs for working with trading infrastructure.

I'd much rather include knowledgeable individuals with professional authority in the loop than rely entirely on box checking as with various ISO standards, HIPPA, FedRAMP etc.

Re: Ask HN: How to Break into AI Engineering

#58

Post by dragonmouse »

electrondood wrote: post #24

Can you elaborate on what "AI engineer" means to you?

I left the question a bit open ended to see the diversity of the field and to hopefully gather advice that could benefit others as well.

That said, primarily _for me_ it's more defined in what it doesn't mean - Which is software engineering _using_ AI (eg - LLMs) and prompt engineering. I'm already a self-taught web/mobile developer with 10+ years experience, and have built some toy projects using LLMs and image diffusion models. Where I believe I have more interest is in the research scientist route. I have prior education in biology/ecology/behavior, and would love to combine the fields.

Re: Ask HN: How to Break into AI Engineering

#59

Post by sn9 »

Exuma wrote: post #7
dragonmouse wrote: post #5

Earlier quoted context omitted.

And would you consider this resource to contain "the math and algorithmic background" necessary? Or is it overkill/missing some things? https://www.freecodecamp.org/news/all-the-math-you-need-in-a...

I'm not qualified to answer this, but I would state nothing is really "overkill" I've been "filling in the gaps" in math for almost a year now to learn machine learning stuff casually. I don't even need to use it, I am just obsessed with learning and I read about it for nearly an hour a day, and its still not enough. Being self-taught at math introduces so many painful problems. If I were to do this seriously I would…

> Being self-taught at math introduces so many painful problems. If I were to do this seriously I would start ALLLL the way back at algrebra in 5th grade and work forwards ALLL the way up to linear algebra/calculus etc.

If you want to do this, these books are great and have complete solutions manuals available: https://artofproblemsolving.com/store/recommendations

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