A) Education has never been this accessible - see https://www.coursera.org/, youtube, MOOCs, blog posts etc. which did not exist anywhere for free even 10 years ago
B) APIs and abstractions make a lot of this quite accessible (e.g. AWS, tensorflow etc.), yes these are "magical" APIs, but you could make the same argument regarding a C compiler going to binary, all the way down to logic gates and electrical pulses
33 is young in terms of education, I would highly doubt you're progressing slowly due to your age, probably more your attitude that is holding you back.
It doesn't mean I have to read every single line of Tensorflow but being able to do that when it's needed. So that such tools won't be magical black box for me.
I would recommend reading "I, Pencil" http://www.econlib.org/library/Essays/rdPncl1.html to help put your mind at ease.
Not to overdo analogies but you dont need to rebuild your own internal combustion engine in a unique way to drive a car or to contribute improvements to a car. The more you understand how and why tensorflow works the more you can do with it. It depends whether you want to build on top of that platform and use it, or build on the concepts for something else.
Even though I lack the name for that level, here's how I would describe in qualitative terms some of its attributes:
- Knowing the basic lay of the land all the way down. That is, at least knowing most of the black boxes and what they do, even if you don't exactly know how they do it.
- Being able to solve your own problems, instead of running around like a headless chicken every time you hit a speed bump in your work.
- Being able to reason from that first-ish principles. You're able to sketch solutions within the scope of the extended domain, and as you begin implementing it and need to understand various blackboxes in more depth, the basic shape of your solution isn't usually invalidated by gained knowledge.
In every field the total knowledge set is always increasing, which is both empowering, because we stand on the shoulders of giants, and diminishing, because there is less low-hanging fruit. There is always more low-hanging fruit though, the trick is to see it hanging there. ML is a wonderful opportunity because the magical api’s can do far more than they’re currently used for.
That's a really interesting analogy, I'm wondering what other think about it?
And does it really make a difference? I don't understand compilers, but it still took me a long time to understand how to write correct input for a compiler, and debug the output.
There is no age that you can't do anything you want to do. But in common ground with what you are saying, the older you get the less time you have. The older you get, the more adrift you become of like minded individuals. The older you get, the tougher, less excited, and less patient you become with learning new things. But at the same time, you become "more" in so many other ways.
All creatures are not only created equal, but remain equal even as time progresses and skills/attitudes/energies are gained/learned and lost.
Isn't that what most of modern software development is like already? Many common use cases have been implemented in frameworks, and usually a developer's job consists mostly of tacking pieces of framework together. The days where a person single-handedly implements a state-of-the-art game from scratch are long over. On the other hand, you could still create a game by yourself using all the available open source tools. You can still be creative and do exiting things all you want, the type of work is just different.
Also, you don't have to be a genius to understand machine learning either. But you do have to learn some math!
You do. Today you can play with Keras or Scikit-learn to do magic that was undreamed of back then.
edit: more sick, the said young researchers are financed by society than get sucked to private corps where their work is locked behind IPs.
Even in the case there is a small company having any progress they would get swallowed up right away.
Yes Keras and Sickit-learn are open source and available to everyone but it's like telling me, look you have access to pen and paper but you need to pay if you want to read the books, the metaphor here being access to data is equivalent to middle age's access to books...
On the other hand, think about it: what do Google and FB have that we don't? Personal data. What they have is data that is useful to target ads. If your interest in AI goes beyond ads, then you don't need that data.
Yeah ? like the tons of photos they harvest from people. Most of the progress they did in training computer vision is based on that. Should I build facebook or google to get access to it ?
What about language modeling ? They have access to conversational data and billions of search queries, both of which there is no way to access them from outside.
What about health ? Well if I'm not somehow working with some big pharma how could I access this kind of data ?
I can go on and on. The point is, yes I can crawl the web, but what "web" is there left ? everything is locked behind paywalls and private clouds. If the real vision of an open internet was fulfilled, all data generated on it would be accessible to crawl indeed.
I'm not saying it's not possible to get data and use it. I'm saying you cannot get the kind of data only monopolies have and you will never be able to compete with them.
Language modeling: hacker news, public mailing lists, wikipedia, github.
Health: you can usually get data if you work at a hospital as an md or researcher. Just need a reasonable idea and an IRB. If you want the pharmacy data, I imagine you could get at it by going to work as a researcher in pharma, insurance, or retailer.
alphago was built using publicly available games of go pros. Alphagozero didn't even depend on data at all.
For AI, the limiting factors are ideas, code, time, hardware.
More a political statement than a statement of relevance to the workplace.
You need not worry that "they" will hold you back. It is unlikely that analyzing monopolys' data will explain how early man built flint tools, Joe the mechanic repairs his car, fifth-grade Fred solves his geometry problems or van Gogh painted. ML, including AutoML, appears to be a long way from solving most AI problems. There's no need to feel that "they" are holding you back by witholding data. And then remember:
"Be careful what you wish for, it might just come true." - old saying
As for your key point, defining yourself let alone your future relative to the paths other people took is pointless. Look at things from a different perspective. Notch built a game of no great technical sophistication where you play with blocks. He did it during his spare time after work. And became a billionaire in the process. Does the fact that you could probably build it from scratch now mean anything about your future? No, not really. Would it mean anything if you could not? Again, no not really. You alone determine your future, or at least heavily influence the probability distributions of it.
On the other hand, I feel sad for myself because me and many others left so far behind. I have strong feeling that such technologies would lead to concentration of power of such mega-corporations like Alphabet as well as complete monopoly for any creative work. So very few of us who managed to become cutting-edge researchers would be proud to be creative humans, others will do just a monkey job using magical APIs.
In 80s, two people could create state-of-the-art game written in assembly with it's own tiny game AI (hello to Elite [1] which has intelligent opponents who engage in their own private battles and police who take an active interest in protecting the law).
In 90s, a small team could create state-of-the-art game written in pure C with some cool AI (hello to Quake III Arena [2] which has pretty strong bots [3]).
https://en.wikipedia.org/wiki/Elite_(video_game)
https://en.wikipedia.org/wiki/Quake_III_Arena
https://www.researchgate.net/publication/240430519_The_Quake...
In both of these cases, you don't have to be genius to be able to understand whole thing alone.
I'm 33 and I progress very, very slowly. I feel I might be on the level close enough to understand Q3A entire source code. I think I would have great future if today is 1994. Unfortunately for me today is 2017 and I do realize that I don't have any exciting future at all.