Education has never been free
Education has always been free.
(where I live, during my lifespan and I'm grateful for that - I was very lucky).
Just saying, not trying to go into any ideological debate about how it should or it should not be.
From school to PhD and postdoctoral, there are even scholarships for the very good students. In theory this could be abused by freeloaders to stay in school forever, in practice it is not that easy, adulthood has its own rules and demands.
Of course, after the fall of the Iron Curtain in 1989, private universities appeared in Romania, too, and now there are payed classes, too, not only the free ones. But here it is quite different, and many still sees the payed study as a second class diploma, because those who don't pass the admission exams for the free universities usually does not give up, and go for a payed university, where the entry bar is lower, or sometimes there is no entry requirements other than having a high school diploma.
The end result is that nowadays an employer will rather prefer to have employees coming from free universities. Nobody is saying that out loud, but the preference is obvious.
Anyway, since I know nothing about NN (Neural Networks), ML (Machine Learning) and AI (Artificially Intelligence), I feel entitled to share my ignorance.
From what I've seen (by just keeping an eye on the field over the years, later watching free youtube classes, etc.)
- it was a big fizz about NN 50 years ago, or so
- then somebody managed to convince everybody else that NN will never work as hoped (I think it was something related with the XOR function, but don't blame me if it was not that)
- the pessimism spread and the field was abandoned for a few decades (the so called "AI winter" era)
- then everybody realized that proof was wrong, in the sense that it doesn't really matter
- meanwhile the hardware was making huge progresses in terms of computing power and available memory, and suddenly everybody was playing with NN and AI again
- the joy was big, hopes were yet again higher than never, research money start to pour in the AI field again, DARPA $1 million+ range prizes competitions for unis and individuals, etc.
- there was only one thing still missing for the AI to fully unleash, and that was the lack of data. A NN is useless without training, just like a computer is useless without software. There are many ways of AI training, but all of them boils down to exposing the NN to piles and piles of data, hundreds to billions of examples to teach the NN what to do and what not to do
- and here it comes the need for data harvesting. Again, the times are just right for the data harvesting frenzy we are living in right now. Ubiquitous Internet access, a computer in any pocket, hive connectivity for the masses.
- the moment seems just right technologically, decent computing power, cheap hardware, big data
We were hunters and gatherers tribes, then agriculturists and salesmans, than craftworkers and mechanicists, then electronists and programmers. Guess now we are heading to the AI era.
The future is now!
So where's my flying car!?
Oh, and all the NN is about fitting curves through the data while learning, then just crunching numbers during inference, when the function of that curve we just fit is applied to each dataset in order to compute the outcome.
Training is the hard thing to do (in a reasonable amount of time), same as learning with humans. This is where most of the effort is now, and IMHO there will be no magic trick here, just hard work.
The big hope is that once a NN training is done, we know how to replicate that learning as cheap as would be to copy a file, and suddenly we can have a flood of top notch expertise available to everyone, like we have now the flood of data since "the Internet".
Home
Help
Search
Login
Register
