I never said anything about not getting the current memes and jokes.
I was alluding to the current mix of the content on reddit. It has gotten more political and less entertaining if you look at the default feed whether you create an account or browse anonymously.
And in any political or open ended discussion, unless it is scientific, the discussions are shallow.
I will however concede that non-scientific/technical discussions were always shallow.
The discussion quality is unbelievably shallow in most of the subreddits.
Unless it's a niche and technical subreddit such as mathematical topics, bio science subtopic, the discussion is quite shallow and in some cases simply misinformed.
For e.g., a recent question about "is this person racist?", everyone jumped on the bandwagon and said "yes!", "100%", "obviously" without citing any sources. They simply paraphrased a small segment of a video of what that person said.
It turned out the thing they paraphrased it was completely out of context and in fact proved it was opposite of what people were believing.
There were a couple of people who pointed this out but they were downvoted into obvilion: -50 downvotes or something like that.
So these comments were hidden by default.
This is what makes reddit an ecochamber. Now just imagine people coming in and reading this post without any prior knowledge, and taking away the wrong conclusion.
This happens ALL the time.
I used to enjoy reddit back in 2011-2013 when it was all about silly memes and jokes.
EDIT: "They simply paraphrased it" --> "They simply paraphrased a small segment of a video of what that person said."
Seriously, what's going on there ? Why is it so different from others? Is it just behind technologically/training wise or it's using something fundamentally different?
> A tensor is nothing but a flat array of numbers, plus some metadata telling you how to interpret those numbers as a multi-dimensional object.
Yikes! No.
I mean even for the intents and purposes of using this definition in ML, this might not be right.
I am trying not to be pedantic, so I will not go with the official/mathematical definition of a tensor as that could be incredibly confusing (look it up!!!).
But a tensor is a LOT more than that. Essentially it's a multilinear map that transforms a set of basis vectors in a certain way, and is coordinate agnostic.
This is not even half its definition so you can see how much the author left out.
Having said that, this is still a good way to start getting intuition into it and I urge the author to continue refining the definition as he/she learns more.
Disclaimer: MS in Math with concentration of GR.
EDIT: Also tensor aren't simply "flat" array of numbers. They are multidimensional. A grounded example, a rank 3 tensor is a collection of 2d matrices. Think of it as a bunch of 2d matrices stacked on top of each other. You need 3 indices to keep track of numbers --- sure in a programming language, it can be represented as a 1d array as well with 0s filling up empty spaces, but you get the idea.
I am not sure if you are being sarcastic because I don't know how people view IEEE "digital badges", but anything from MOOCs on LinkedIn stopped being valuable a long time ago, if it ever was.
The "vocabulary resolution being low" basically just means within our own limited context, it's low. But that doesn't mean it's a good measure. Heck, I'd say it isn't.
If one were to go about translating brain waves from dogs to meaning, we'd run into a big problem immediately: vocabulary resolution.
What I mean by that is we'll have a very limited number of words to which a dog's brainwaves can be translated to since we aren't able to understand them beyond their basic instincts of food, survival, fear, affection towards their owner etc.
There is just no way to go past what we have already observed by their behavior since dogs can't talk or write.
I do wonder how animals think. Perhaps this resolution would also be the theoretical maximum?
I wonder in the case of Francesca Gino, how much of that was driven by Harvard.
I remember it was technically initiated by the Harvard business school, but it was probably triggered by data colada launching their own investigation.
I don't think an economic model would work. Only a political one would work where the government would redirect a lot of funds towards this, making it a lucrative profession.
Adtech works because there is a lot of money in it. There is a lot of money in it because people seek quick entertainment, and we have a LOT of people driving the demand.
Now compare that to cancer research. There's no short term gratification about it.
> we shouldn't stop insisting that things change for the better
I never said we shouldn't.
What I meant by "Change will always be coming. Embrace it.", is to accept it as a reality, be ready for it and prepare for it. That means, be ready to resist negative change and accept positive change.
Even after successfully resisting negative change, the end state may still be different than before. This is what we have to accept and be ready for, mentally.
Nothing lasts forever. Good times will come and go and so would bad times.
I think as humans we are used to small time frames which are proportional to our own lifetime.
But the world: say climate, population, geology etc. moves at a much different cycle, if at all you can call it a cycle since none of the iterations are exactly the same.
So the lesson is this: change is coming. Change will always be coming. Embrace it.
If you like something, you have to struggle to preserve it as much as you can, for as long as you can, but you can never make it permanent.
I was alluding to the current mix of the content on reddit. It has gotten more political and less entertaining if you look at the default feed whether you create an account or browse anonymously.
And in any political or open ended discussion, unless it is scientific, the discussions are shallow.
I will however concede that non-scientific/technical discussions were always shallow.