[HN Gopher] AI Engineer Reading List
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AI Engineer Reading List
Author : ingve
Score : 185 points
Date : 2025-01-13 18:11 UTC (4 hours ago)
(HTM) web link (www.latent.space)
(TXT) w3m dump (www.latent.space)
| nickpsecurity wrote:
| This is a great survey. Combine it with the courses below for
| best results:
|
| https://www.trybackprop.com/blog/top_ml_learning_resources
| joshdavham wrote:
| Awesome list!
| kamikazeturtles wrote:
| I don't know what an "AI Engineer" is, but, is reading research
| papers actually necessary if the half life of the relevancy of
| many of these papers is only a few months until the next
| breakthrough happens?
|
| I have a feeling, unless you're dabbling at the cutting edge of
| AI, there's no point in reading research papers. Just get a feel
| for how these LLMs respond then build a pretty and user friendly
| app on top of them. Knowing the difference between "multi head
| attention" and "single head attention" isn't very useful if
| you're just using OpenAI or Groq's API.
|
| Am I missing something here? I'd love to know where I'm wrong
| feznyng wrote:
| There's research papers on system design involving llms that
| would definitely be useful in practical contexts.
| eKIK wrote:
| I consider myself to be an (occasional) user of AI services
| like the ones OpenAI and others provide. I've learned how to
| consume the services reasonably effectively, and make good use
| of them, but that's about it. I am not an AI engineer.
|
| Similarly I know how to call cryptography libraries to get my
| passwords hashed using a suitable cipher before storing them. I
| don't understand the deep math behind why a certain cipher is
| secure, but that's fine. I can still make good use of
| cryptographic functions. I'm not a cryptography engineer either
| :).
|
| My take on it is that if you should call yourself any kind of
| "XYZ Engineer", you should be able to understand the inner
| workings of XYZ.
|
| This reading list is most likely (mostly) for those who want to
| get a really deep understanding and eventuellt work on
| contributing to the "foundational systems" (for a lack of a
| better word) one day.
|
| Hope that helps.
| swyx wrote:
| i mostly agree w you, but theres a wide spectrum of
| "understand the inner workings" given rising complexity.
|
| consider:
|
| - does a React/frotnend engineer need to know everything
| about react internals to be good at their job?
|
| - does a commercial airline pilot need to know every single
| subsystem in order to do their job?
|
| - do you, a sophisticated hackernewsian, really know how your
| computer works?
|
| more knowledge is always (usually) better but as a thing
| diffuses into practice and industry theres a natural stopping
| point that "technician" level people reach that is still
| valuable to society bc of relative talent supply and demand.
| FanaHOVA wrote:
| We covered that too: https://www.latent.space/p/ai-engineer
| randcraw wrote:
| A nice overview. In short, I would describe an AI Engineer as
| someone who integrates existing AI tools and libraries into a
| reliable system that is fielded in a production environment.
| They also must know how to tune AI components and assess them
| for performance, decline/drift, and failure. Most AEs have a
| MS or less (CS, data science, statistics, etc), since it's
| not really a research role. Finally, AI Engineers don't
| invent AI tools or fix what's missing/broken within them.
| That's the role of an AI scientist.
| jsight wrote:
| I think you need to have a pretty good understanding of the
| underlying workings of at least a couple of modern models. You
| should also follow along closely enough to see if major changes
| happen in the way they are built.
|
| But watching every new paper? Nah, that's mostly only useful if
| you have a large enough amount of compute to try them out. And
| most of us don't have that anyway.
| lolinder wrote:
| > I don't know what an "AI Engineer" is, but, is reading
| research papers actually necessary
|
| Let's put it this way: if even half the people who call
| themselves "AI Engineers" would read the research in the field,
| we'd have a lot less hype and a lot more success in finding the
| actual useful applications of this technology. As is, most "AI
| Engineers" assume the same thing you do and consider "AI
| Engineering" to be "I know how to plug this black box into this
| other black box and return the result as JSON! Pay me!".
| Meanwhile most AI startups are doomed from the start because
| what they set out to do is known to be a bad fit.
| wnmurphy wrote:
| > I know how to plug this black box into this other black box
| and return the result as JSON!
|
| To be fair, most of software engineering is this.
| gazchop wrote:
| Careful now. Don't want to upset the future generation of
| unemployed prompt engineers.
| richardw wrote:
| The terms are being diluted hard. Everyone from a plumber with
| a no-code RAG automation tool to a FAANG phd can and have
| claimed the role "AI engineer", and it can be true depending on
| the context.
| jimbokun wrote:
| The new "Data Scientist"!
| swyx wrote:
| hi! author here.
|
| > Just get a feel for how these LLMs respond then build a
| pretty and user friendly app on top of them.
|
| as you know, "just" is a very loaded word in software
| engineering. The entire thesis of AI Eng is that this attidude
| of "just slap a UI on an LLM bro whats so hard" is a rapidly
| deepening field, with its own stack and specialization (which,
| yes, some if not much of which is unnecessary, vc funded hypey
| complexity merchantism, but some of which is also valid), and
| if you do not take it seriously, others will, and do so running
| rings around those who have decided to not even try to push
| this frontier, passively waiting for model progress to solve
| everything.
|
| i've seen this play out before in underappreciated subfields of
| engineering that became their own thing, with their own
| language, standard stack, influencers, debates, controversies,
| IPOs, whole 9 yards.... frontend eng, mobile eng, SRE, data
| eng, you name it. you just have to see the level and quality of
| work that these people are doing that is sufficiently distinct
| from MLE and product/fullstack webdev to appreciate that it
| probably deserves its own field of study, and while it will
| NEVER be as prestigious as AI research, there will be a ton
| more people employed in these roles than there can be in
| research and thats a perfectly fine occupation too.
|
| I'm even helping instruct a course about it this week as it
| happens if you want to see what a practical syllabus for it
| looks like https://maven.com/noah-hein/ai-engineering-intro
| swyx wrote:
| also my biz partner would be mad if i didnt also mention the
| conference im putting on next month
|
| https://www.latent.space/p/2025-summit
| swyx wrote:
| hi! author here! putting together a list like this is
| intimidating - for every thing i pick there are a dozen other
| suitable candidates so please view this as a curriculum with
| broadly prescriptive weightings, with the understanding that the
| CURRENTLY_RELEVANT_PAPER is always a moving pointer rather than
| fixed reference.
|
| we went thru this specific reading list in our paper club:
| https://www.youtube.com/watch?v=hnIMY9pLPdg
|
| if you are interested in a narrative version.
| andrekorol wrote:
| I appreciate the effort put into curating and maintaining this
| list, good job on that!
|
| I'm curious, is there also some specific existing "AI
| Researcher Reading List" you would personally recommend? Or do
| you plan on making and maintaining one?
| swyx wrote:
| im no researcher so no, but i would start with the llm
| courses at stanford, uc berkeley, stanford, and princeton.
| bbor wrote:
| Heh, always fascinating to see how the term "AI" has been
| swallowed nigh-completely by the recent exciting developments in
| DL. All those papers and not a single mention of Russell &
| Norvig, Minsky, Shannon, Lenat, etc.!
|
| I'm sure it's a great list for what it is, I just wanted to be
| pedantic for a bit ;). If you're interested in an introduction to
| AI as a broader topic, most graduate courses use the same book
| (Russel & Norvig) and others may publish their syllabi online.
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