Submitted by beezlebub33 t3_xxyeun in MachineLearning
3jckd t1_ireitny wrote
Why do you even need to understand everything? FOMO?
Either you work on fairly general topics, or more generally applicable things, and then you don’t need to read a bazillion papers that propose yet another flavour of attention.
Or you work on something more specific within one domain, e.g. NLP, and then you don’t need to know the details of e.g. image generation that you brought up.
Pro-tip: high level understanding of the field as a whole, and solid understanding of your specific niche is what you’re after.
GFrings t1_irelmbh wrote
This. We need to start treating ML as a collection of fields with synergies. Just like they teach in engineering school, you're going for a T shaped skill tree. Be generally knowledgable about what's out there, but do a deep dive of one particular niche that interests you.
Also, it should be said that if you're not a researcher, one of the hardest parts of AI is the data. Everyone gets this wrong, particularly when they start chasing the latest backbone, or loss function, or a hundred things that see dozens of publications per week on. The ML engineering around standing up a good experiment, regardless of what you're actually putting into the model slot of this experiment, is where 90% of the effort should be going.
beezlebub33 OP t1_ireprux wrote
>Why do you even need to understand everything? FOMO?
FOMO is part of it. I'm interested in ML in general, and think that AI is coming (really unsure when) and I want to be part of all of it. I have this fear that someone is going to do something very important and I just won't know about it.
There is also the expectation (at least where work) that when you are a 'Machine Learning Engineer' that you have a pretty good grasp on the field as a whole. You don't want someone to say 'What do you think of Random Forests, how do they work?' and you go 'What's a Random Forest?' (hyperbolic example). I kind of sucks when you are the 'ML Guy' in a pretty big company so people come to you with (random) questions.
Finally, I'm old enough that I think that when ML started, I did know most of it. Having been raised on Duda and Hart and then was around when backprop made it's second renaissance, I remember when Elements of Statistical Learning came out. So, perhaps it's a sadness that the field has blossomed beyond me.
nullbyte420 t1_irethse wrote
To answer questions from normal people you don't need to know the latest thing. You need to understand the basics really well, because that's what they don't 🙂 Anyone can read the latest paper but not everyone can put it into context and compare it to existing models.
csreid t1_irg0y7f wrote
I kinda get where OP is coming from, though. With all the pop-sci ML stuff and big press releases for popular consumption hitting really shortly after actual publication, there's always a risk that some manager will be like "hey I just read about stable diffusion on Twitter, can we use it to do this?" and then you're a deer in headlights bc you weren't at the press conference where they introduced it and you have no idea what the manager is even talking about.
Ulfgardleo t1_irg3wty wrote
"This is a fairly new model and I do not know the details. If you seriously consider this, I can read up on the most recent work and then we have a meeting next week and discuss whether and how it could help us".
The awesome thing about solid basics is that you can do exactly this.
csreid t1_irjtm3b wrote
But this bit:
>"This is a fairly new model and I do not know the details"
is hard! I understand having anxiety about being The ML Guy and not being able to immediately answer questions.
Ulfgardleo t1_irm2bsq wrote
yes. I think at this point it is important to realize that in the exact moment you got hired by a company, your role changed.
You were the guy with a PhD straight from university who did top-notch research. Now, you are the guy hired to make this project work.
If your job description does not include "active research" or "follow the most recent advances in ML research" then it is not your job to know what is up - especially if it is an advancement in a subfield of ML your project is not actively interested in.
AliceHwaet t1_irh3fnq wrote
It's not necessarily FOMO. look at job postings these days. They want the kitchen sink, the counter it was built into, the floor plan, the carpenter who did the rough framing of the whole damn house, how did you acquire the property to build the house, where did you get the money, prove it, and on.
Someone newish to the field thinks all these things are important because job posters just throw every damn AI/ML skill they've ever heard of or googled into the JD.
That needs to stop and the person describing the T method is right. Business and hiring managers have it bass ackwards.
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