I don't read any of the papers because there is basically no way to re-implement them or independently verify them. People can feel shocked, surprised, amazed or enlightened all they want while reading the paper but in truth people still have no idea how any of this truly work.

Before at least you had a mathematical model to work with which shows that even at small-scale this idea can lead to something that work as promised on a larger-scale ML model.

Nowadays OpenAI can claim that Jesus came back and cleaned the data for their model and we would actually have no way to actually verify the veracity of this claim.

Absolutely not. These ethicists can find "bias" all day and everyday, but become practically mute when it comes to condemning how their companies are in bed with capitalism and military-industrial complex that are far more dire to the fate of humanity.

My friend just went through an interview where they were asking them about some pandas operator. And it was one of those big companies.

I do believe that many ML interviewers are mentally insane.

>I really don't know why that happened.

Once upon a time there was a google engineer who wrote a book called the "crack the coding interview" and the rest is just layers upon layers of BS piled on top of the dogma teachings of that book, until red-and-black trees and divide-and-conquer are no different than some relics you find in a cult.

>But today why should I invest my free time into leetcode, instead of learning something useful?

If it is not useful for creating profits, then it is not useful - logic of capitalism 101.

That's just capitalism bro.

1. you always need to prove your capacity to work; doesn't matter if you've been doing this for dozens of years
2. you are always one life event away from losing all of it
3. your every living moment is squeezed into turning a profit for random strangers
4. you put on a fake smile, go to work, and pretend with everybody else that the system is normal or even "not so bad" or "could be worse"

There are some people who have published as first author in their bachelors. From what I've seen, they are extremely talented and/or with good connection to some key people in the field.

However, their work usually shows a clear lack in awareness of the research that has already been done on the problem that they are now working on. It is kind of obvious, but this is something that could slip through the cracks.

As first author, extremely hard.

Essentially, to become a first author, you need to do these things:

1. have a good awareness of the state of the literature
2. find something worthwhile on top of all that literature
3. solidly show that your ideas work

More math may help you with 1, 2, 3. More programming may help you with 2, 3. Number 1 and 2 will trip beginners without people who know the field very well.

Ha! If only. Capitalism will just try to start wars overseas and direct all excess humans into the war effort.

Until every soldier is replaced by a drone that is...

People here are way too optimistic.

The goal of technology within capitalist systems is to cut cost and inefficiencies for the capitalists. It has been a very very long project to eliminate the human from capital accumulation. The start of it was the removal of peasants and indigenous people from their land because "they not using (the land) (farming) (digging for gold) (...) efficiently".

At some point physical labor became hugely replaceable (mainly due to automatic control). So the only thing that is of value is people's creative minds: their ability to code, to design, to create art or music.

We are in the phase that the latter inefficiencies are going to get eliminated. This is the intended function of capitalism. It is the river that guides the current.

The final stake in the heart is coding itself. I know huge amount of CS majors who are now doing automated code generation because it is "challenging". It is like painting glitter on ourselves because it looks "interesting" without caring about where all those glitter end up.

We as scientists, researchers, people who work in technology are digging a grave for ourselves in pursuit of "knowledge". Our goals have been hijacked by people who want nothing more than more money. People who care nothing for science or knowledge or any meaningful questions. People like that apple exec like to drive "fancy cars" and "fondle big breasted women" doesn't give a rat's ass about the information bottleneck; yet hundreds of ML/software/hardware engineers work under him.

Also observe how most ML researchers are literally doing research at places with huge concentration of homeless people, poverty and social inequality. It is too late.

Yeah but those are also the most well connected people in the ML world. It is easy to be impactful when you are having tea with Hinton, LeCun and Bengio every afternoon.

I keep on trying to find one thing that she published that's considered to be successful and I find myself having to very narrowly define success. This was when I was doing a general survey on RL techniques.

But ADAM paper was wrong, so. It is no better than cooking up an equation, which I guess is impressive, but if you know the right people then the overall contribution is very low. Like ADAM was literally 1 or 2 steps away from whatever Hinton was doing, and Hinton was literally the co-author's (forgot his name) supervisor or something.

Not to rag on Chelsea Finn, who I am certain is brilliant but,

1. I can't understand her. She falls into the classic ML research habit of defining very specialized new terms or new frameworks without bothering to explain it in the context of what everybody else is already familiar with.
2. In the same vein, basically no comment on how their methods compete with say, traditional methods. You are doing a robot grasping, I'm not sure if you are the first one to do this.
3. All the robot money comes from DARPA and Office of Naval Research, which I guess comes from killing brown people overseas? Yes...DARPA/ONR is part of America's big weapon's industry. They literally have .mil in their website names.