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My story as a self-taught AI researcher

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Re: My story as a self-taught AI researcher

#41

Post by drongoking »

wigl wrote: post #39

This reeks of survivorship bias to me. I much prefer Andreas Madsen's more sober and self-conscious take on independent research [0]. > I’d spend 1-2 months completing Fast.ai course V3, and spend another 4-5 months completing personal projects or participating in machine learning competitions... After six months, I’d recommend doing an internship. Then you’ll be ready to take a job in industry or do consulting to se…

> So what really mattered was self-promotion, good timing, and luck.

Yes. He seems like someone who is good at self-promotion and networking. Well, good for him, but I think he underplays the role these have in his success.

> Why does the author have to present his life like one would in a fucking college essay?

I guess that's the self-promotion. And humble-bragging. Like this bit:

"I started working as a teacher in the countryside, but after invoking the spirit of their dead chief, they later annotated me the king of their village."

Re: My story as a self-taught AI researcher

#42

Post by echelon »

TrainedMonkey wrote: post #5
woah wrote: post #3

Earlier quoted context omitted.

On the other hand, the lack of data for independent researchers may encourage the development of low data techniques which is much more exciting in the long term since humans are able to learn with much less data than required by most machine learning techniques

Arguably humans have a lifetime of data which was used to develop a model of the world that is amazingly efficient at interpreting new data.

Humans can transfer learn across domains because we can draw on an incredible wealth of past experience. We can understand and abstractly reason about the architecture of problem landscapes and map our understanding into new spaces.

That isn't even counting our hardwired animal intelligence.

Re: My story as a self-taught AI researcher

#43

Post by andreyk »

K0SM0S wrote: post #20
andreyk wrote: post #18

Earlier quoted context omitted.

wrt the data point, to be fair most research is still coming out of universities where students have access to the same data as anyone else. So from a research perspective it's not a huge deal, much as with compute industry can scale up known techniques while individual researchers do more interesting stuff.

So if I understand correctly, to reformulate in my own words/views: while the "big data" (datasets) formed and thus owned by big-tech, big-ads, big-brother, etc. may be instrumental to build at-scale solutions for real-world usage (for profit, knowledge, control, whatever actionable goal), fundamental research itself, as done in universities, can move forward without these datasets: using what's publicly available is…

yep, you read that right. Source: I am a PhD student at Stanford at the Stanford Vision and Learning lab (http://svl.stanford.edu/) and read a ton of AI papers. The vast majority of papers are done with datasets anyone can just download / request, as far as I've seen.

Re: My story as a self-taught AI researcher

#44

Post by ssivark »

rmah wrote: post #38

Is this guy actually a researcher in the way most people would think of it? That is, someone who pushes the boundaries of science; who develops new AI techniques or finds the hard boundaries of existing AI techniques; who finds new ways compose multiple AI techniques cohesively; who explores the theoretical foundations of AI. Or is he someone who uses AI techniques to solve problems (and then wrote a paper about it)?…

For better or worse, the definition of researcher has morphed into a combination of

1. Solves previously unsolved problems

2. Publishes papers sharing those solutions

without regard to the kind/spirit/scope of problems solved.

Since conference publications don’t have the same number constraints as journal papers, and are accepting of application-specific results, this explosion of what is considered “research” is somewhat inevitable. Also, there are a lot of people chasing this given the prestige associated with the title.

Re: My story as a self-taught AI researcher

#45

Post by lallysingh »

TrainedMonkey wrote: post #5
woah wrote: post #3

Earlier quoted context omitted.

On the other hand, the lack of data for independent researchers may encourage the development of low data techniques which is much more exciting in the long term since humans are able to learn with much less data than required by most machine learning techniques

Arguably humans have a lifetime of data which was used to develop a model of the world that is amazingly efficient at interpreting new data.

Is that in a csv.gz I can torrent somewhere?

Re: My story as a self-taught AI researcher

#46

Post by rlayton2 »

rmah wrote: post #38

Is this guy actually a researcher in the way most people would think of it? That is, someone who pushes the boundaries of science; who develops new AI techniques or finds the hard boundaries of existing AI techniques; who finds new ways compose multiple AI techniques cohesively; who explores the theoretical foundations of AI. Or is he someone who uses AI techniques to solve problems (and then wrote a paper about it)?…

Research needs people at the entire spread of the spectrum - from those making fundamental improvements to underlying theory, all the way to people running the thing to see if it works on actual problems people have (obviously in a robust and verifiable way).

Re: My story as a self-taught AI researcher

#47

Post by rhizome »

TrainedMonkey wrote: post #5
woah wrote: post #3

Earlier quoted context omitted.

On the other hand, the lack of data for independent researchers may encourage the development of low data techniques which is much more exciting in the long term since humans are able to learn with much less data than required by most machine learning techniques

Arguably humans have a lifetime of data which was used to develop a model of the world that is amazingly efficient at interpreting new data.

Are you referring to empiricism?

Re: My story as a self-taught AI researcher

#48

Post by ssivark »

hogFeast wrote: post #16
bluetwo wrote: post #8

The thing that disappoints me about the aspirations of being a researcher is that the goal is to get paid to study AI, not solve real-world problems. I would rather build a small company by solving a real problem than work for a big company spinning my wheels.

Why I didn't go into academia but GL convincing other people of the value in that. I am sure there are cultural differences here but where I am, the goal of most people who study CS is: leave me alone while I mess about with X (evidence: the local college was doing speech processing/nlp in the 60s, they actively turned down paid work...unsurprisingly, they got left in the dust, professors are now being encouraged int…

(American) Academia is a complicated matter, so I’ll elide commenting on that.

For a thoughtful counterpoint to the necessity argument, see: https://jnd.org/technology_first_needs_last/ (previously discussed on HN)

Re: My story as a self-taught AI researcher

#49

Post by wigl »

drongoking wrote: post #41
wigl wrote: post #39

This reeks of survivorship bias to me. I much prefer Andreas Madsen's more sober and self-conscious take on independent research [0]. > I’d spend 1-2 months completing Fast.ai course V3, and spend another 4-5 months completing personal projects or participating in machine learning competitions... After six months, I’d recommend doing an internship. Then you’ll be ready to take a job in industry or do consulting to se…

> So what really mattered was self-promotion, good timing, and luck. Yes. He seems like someone who is good at self-promotion and networking. Well, good for him, but I think he underplays the role these have in his success. > Why does the author have to present his life like one would in a fucking college essay? I guess that's the self-promotion. And humble-bragging. Like this bit: "I started working as a teacher in…

> Well, good for him, but I think he underplays the role these have in his success.

Exactly. Good for Emil, but it's always frustrating to hear survivorship bias preaching. Even the interviewer starts off by saying:

"By the way, I really love your CV - the quirks section was especially fun to read."

It's even more frustrating when I hear non-POC's talk about their journey to some non-western country (and subsequent conquering of fantastical goals like gaining the approval of locals) or pursuit of some sense of foreign culture. It's almost a given that they have internalized and appropriated the ideas (i.e. Buddhism or even worse post-retreat Buddhism). Good for the author to receive such positive feedback for such signaling, but it makes me sad to know that I might not receive the same.

Re: My story as a self-taught AI researcher

#50

Post by ineedasername »

I think in these sorts of discussions two concepts with the same name tend to get conflated, so I think it's important to make a distinction between:

1) AI Research as applying/tweaking known ML/DL methods to a novel problem. I would term these something like "AI Engineering Research"

2) AI Research as examining the theoretical frameworks & approaches to ML/DL in a way that may itself lead to shifts in the understanding of ML/DL as a whole and/or develop fundamentally new tools for the purpose of #1. What might be termed "basic" or "pure" research.

I'm not placing one of these above the other in terms of importance. They are both necessary, and they form a virtuous feedback loop between the two that, one without the other, would see the other wither on the vine.

In the example of this particular person, Emil Wallner, he appears to be doing #1, and perhaps doing so in a way that might help inform more of #2.

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