Here is an answer to the question, (Rephrased from Xyed Abz) "Isn't consciousness the only algorithm we need to build to create a artificial general intelligence like humans or animals?"
Xyed Abz: I like your question because it not exactly those "How do you build an AGI, Muahaha?"-type of fluffy topic. At least you thought about "consciousness" is important in building intelligent machine.
Many members at Coursera deeplearning.ai ask about if a Coursera certificate is something useful. So I want to sum up couple of my thoughts here:
* The most important thing is whether you learn something in the process. And there are many ways to learn. Taking a course is good because usually the course preparer would give you a summary of the field you are interested in.
* So the purpose of certification is mostly a way of motivation so that you can *finish* a class. Note that it is tough to *finish* a class, e.g. Coursera statistics suggest that completion rate is ~9-13%. This number might be smaller at Coursera because it doesn't cost you much to click the enroll button. But you go to understand finishing a class is no small business. And certification is a way to help you to do so. (Oh, because you paid $ ?)
* Some also ask whether a certificate is useful for resume. It's hard to say. So for now, there is a short supply of university-trained deep learning experts. If you have a lot of non-traditional experience from Coursera and Kaggle, you do get an edge. But as time goes on, when more learners have achieved status similar to yours, then your edge will fade. So if you think of certificates as part of your resume, be ready to keep on learning.
For people who got stuck in Course 1. Here are some tips:
- Most assignments are straight-forward. And you can finish it within 30 mins. The key is not to overthink it. If you want to derive the equations yourself, you are not reading the question carefully.
- When in doubt, the best tool to help you is the python print statement. Check out the size and shape of a python numpy matrix always give you insights.
- I know a lot of reviewers claim that the exercise is supposed to teach you neural network "from scratch". So .... it depends on what you mean. Ng's assignment has bells and whistles built for you. You are really doing these out of nothing. If you write everything from C and has no reference. Yeah, then it is much harder. But that's not Ng's exercise. Once again, this goes back to the point of the assignment being straight-forward. No need to overthink them.
Hope this helps!
> git clone https://github.com/bitcoin/bitcoin.git
>git checkout v0.14.2
>./configure --without-gui --disable-tests --disable-wallet
> make -j 4
As always, AIDL admin routinely look at whether certain post should stay to our forum. Our criterion has 3 pillars: relevancy, non-commercial and accurate. (Q13 of AIDL FAQ)
This time I look at "The Post-Quantum Mechanics of Conscious Artificial Intelligence", the video was brought up by an AIDL member, and he recommend we started from the 40 mins mark.
So I listened through the video as recommended.
Indeed, the post is non-commercial for sure. And yes, it mentioned AGI from Roger Penrose. So it is relevant to AIDL. But is it accurate though? I'm afraid my lack of physics education background trip me. And I would judge that "I cannot decide" on the topic. Occasionally new science comes in a form no one understand yet. So calling something inaccurate without knowing is not appropriate.
As a result this post stays. But please keep on reading.
Saying so, I don't mind to give a *strong* response to the video. Due to the following 3 reasons:
1, According to Wikipedia, most of Dr. Jack Sarfatti's theory and work are not *peer-reviewed*. He has left academia from 1975. Most of his work is speculative. And most of them are self-published(!). There's no experimental proof on what he said. He was asked several times about his thought in the video. He just said "You will know that it's real". That's a sign that he doesn't really evidence.
2, Then there is the idea of "Post-Quantum Mechanics". What is it? The information we can get is really scanty. Since I can only find a group which seems to dedicate to such study, as in here. Since I can't quite decide if the study is valid. I would say "I can't judge." But I also couldn't find any other group which actively support such theory. So may be we should call the theory at best "an interesting hypothesis". And Sarfatti build his argument on the existence on "Post Quantum Computer". What is it? Again I cannot quite find the answer on-line.
Also you should be aware that current quantum computer have limited capability. D-Wave quantum computing is based on quantum annealing, with many disputed whether it is true quantume computing. In any case, both "conventional" quantum computing and quantum annealing has nothing to do with Post-Quantum Computer. That again you should feel very suspicious.
3a, Can all these interesting theory be the mechanism of the brain or AGI? So in the video, Sarfatti mentioned brain/AGI for four times. His point are two, I would counter them right after, first is that if you believe in Penrose's theory that neurons is related to quantum entanglement, then his own theory-based on post quantum mechanics would be huge. But then once you listen to serious computational neuroscientists, they would be very cautious on whether quantum theory as the basis of neuronal exchange of information. There are many experimental evidence that neurons operate by electrical signal or chemical signal. But they are in a much bigger scale than quantum mechanics. So why would Penrose suggested that have make many learned people scratch their heads.
3b, Then there is the part about Turing machine. Sarfatti believes that because "post-quantum Computer" is so powerful so it must be the mechanism being used by the brain. So what's wrong with such arguments? So first thing: no one knows what "post quantum-computer", that I just mentioned in point 2. But then even if it is powerful, that doesn't mean the brain has to follow such mechanism. Same can be said with our current quantum computing technologies.
Finally, Sarfatti himself believes that it is a "leap of faith" to believe the consciousness is wave. I admire his compassion on speculating the world of science/human intelligence. Yet I also learn by reading Gardner's "Fads and Fallacies" that many pseudoscientists have charismatic personality.
So Members, Caveat Emptor.
Here's an awesome post from Prof. Tao:
Some misadventures on MacOS X:
- Making System Calls From Assembly in Mac OS X from FiloScottie. (Felix's Blog is pretty good too.)
- AT&T vs Intel Syntax
- gcc -v
- radare2 is better to be compiled from source.
- Your system nasm is probably too old, but then a compilation can easily solve the problem.
Some gist about fasttext:
- Basically 3 packages, wordvector, text classification and compression.
- Text classifications is really comparable with other deep methods. Another Web's wisdom is here.
- Running the tasks are trivial for proficient unix users. So I don't want to repeat them here. The examples also run end-to-end and they are fast.
- Unlike what I thought though, fasttext doesn't quite setup a deep-learning-based word-classification, but as I said, that's not the point.
- Compression was known to be so good such that it can fit to be embedded devices.
- Users also got granted patents to use the source code freely. So good stuffs.
Some other nice resources one can follow: