What are some great resources for learning the skills and knowledge necessary to start a career as an AI engineer?
Gracias!
Ask HN: How to Break into AI Engineering
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Re: Ask HN: How to Break into AI Engineering
#2https://a16z.com/2023/05/25/ai-canon/
Covers a lot of ground
Re: Ask HN: How to Break into AI Engineering
#3Assuming 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.
Re: Ask HN: How to Break into AI Engineering
#4Has anyone here transitioned into an ai dev adjacent role, akin to something a bit more involved than "prompt engineering" potentially the "product eng" equivalent of AI?
Re: Ask HN: How to Break into AI Engineering
#5Assuming 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.
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...
Re: Ask HN: How to Break into AI Engineering
#6I would recommend AI Applications Engineering (e.g., applying LLMs as a unit of compute).
Start with reading AI Canon and setting up projects like PrivateGPT and AutoGPT locally, then working with LocalAI to serve up HuggingFace models in place of OpenAI models.
Re: Ask HN: How to Break into AI Engineering
#7Assuming 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.
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 start ALLLL the way back at algrebra in 5th grade and work forwards ALLL the way up to linear algebra/calculus etc.
There's just too many tiny things and subtle details that are missed that I find. It makes any example require 10 times more brain power just to do simple things I don't remember, like the rules of factorization etc. So I'll go learn that thing which is simple, go back and 2 mins later I'm off trying to find some other simple thing. Mainly the idea of learning 5th grade math and such is so boring I just never have actually done it, so really instead of what I do, I would just learn the ENTIRE freaking thing.
Learning stuff like gradient descent and stuff is easy, but that's not even where all the hard stuff lies. I feel like trying to understand the math deeply behind those topics where youre not just glossing over explanation is where it gets difficult, and to do that you pretty much need the most solid math background without gaps.
Re: Ask HN: How to Break into AI Engineering
#8Has anyone here transitioned into an ai dev adjacent role, akin to something a bit more involved than "prompt engineering" potentially the "product eng" equivalent of AI?
I moved into content moderation, which basically does all the engineering around ML models (logging, queuing, caching, databases, etc.) with limited opportunities to create my own models. Unfortunately, the barrier to entry is high, and it has been difficult for me to find the time to step out of my comfort zone.
Re: Ask HN: How to Break into AI Engineering
#91. Log onto OpenAI
2. Prompt ChatGPT for "how do I make a pytorch program that learns to do "
3. Ask ChatGPT for code and for it to explain the code
4. Run the code on Google colab, if it doesn't work, ask ChatGPT why and keep rerunning it until it does
5. If you find some API that's too new for ChatGPT to know about, just paste in the API documentation and then ask ChatGPT to propose some code using it
ChatGPT is wrong a lot, but if you keep badgering it, eventually you will get a solution that works. It's like having a tutor standing next to you that you can ask questions to, I can't think of a better way to learn even if it's wrong on occasion.
Re: Ask HN: How to Break into AI Engineering
#10Assuming 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 worry that even if self-taught, I wouldn't have the credentials (job experience or degree), to do a full-time ML job.
Our my concerns unfounded?