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Learning to Love the AI Bubble

sloanreview.mit.edu

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Re: Learning to Love the AI Bubble

#21

Post by cr0sh »

nostalgk wrote: post #12
lkrubner wrote: post #9

Right now there are 5 comments on this post, and all 5 focus on the issue of how to invest in AI. That suggests something about how Hacker News has changed over the years. There is a larger focus on “what stock can I buy” and somewhat less focus on working with the actual tech.

If I wanted to get started learning about machine learning/AI, where is the best place to do that? I'm a functional programmer who's learned mostly everything about software engineering on the job, and I feel like I don't have the background I need to get started on it; I struggle immensely with math, but have had no problem with my career in software yet thus. I am going to be traveling for a machine learning conven…

I'm biased, because I took the course when it was called "ML Class" in 2011:

https://www.coursera.org/learn/machine-learning

Everything is done in Octave (ie - open-source matlab-like language); primitives are vectors and matrices - so you'll have to wrap your head around that.

But that course gave me the first explanation as to how neural networks actually worked that I could understand; I had been reading about neural networks for years from various sources - books, online, videos, etc - and nothing ever "clicked" for me (mainly around how backprop worked). For some reason, this did it for me.

Since then, I have taken other MOOCs centered around ML and Deep Learning, mainly with a focus on self-driving vehicles.

Oh - ML Class also led one individual to implement this during the course, as the ALVINN vehicle was mentioned in more than a few ways:

https://blog.davidsingleton.org/nnrccar/

While Singleton does mention its "vintage-ness", I still think it's a sound project for inspiration and learning how to apply a neural network to a simple self-driving vehicle system, not to mention the fact that it replicated a system from the 1980s using today's commodity hardware; I recall reading about ALVINN when I was a kid, with wonderment about how it "worked" - it was one of several 1980s projects in the space that got me hooked on wanting to learn how to make computers learn.

Re: Learning to Love the AI Bubble

#22

Post by epr »

> Not all bubbles have negative consequences for the economy

Unless we are using a different definition of "bubble" than it would seem (to me) most people intend when they use that word, this is a factually incorrect statement.

If widespread misallocation of investment capital does not "hurt" the economy, then what does? If capital is invested with a positive outcome for the wrong reasons, then that certainly would not fit the definition.

First applicable definition from a google search:

Bubble: used to refer to a significant, usually rapid, increase in asset prices that is soon followed by a collapse in prices and typically arises from speculation or enthusiasm rather than intrinsic increases in value.

Re: Learning to Love the AI Bubble

#24

Post by muerdeme »

epr wrote: post #22

> Not all bubbles have negative consequences for the economy Unless we are using a different definition of "bubble" than it would seem (to me) most people intend when they use that word, this is a factually incorrect statement. If widespread misallocation of investment capital does not "hurt" the economy, then what does? If capital is invested with a positive outcome for the wrong reasons, then that certainly would n…

You may find this perspective interesting: https://thehill.com/opinion/finance/356376-black-monday-less...

Defining "bubble" can be surprisingly difficult and in some cases the illusion of a bubble persists after history proves the speculation or enthusiasm to have been correct despite an earlier collapse in prices. So one interpretation of "Not all bubbles have negative consequences for the economy" is that there are events that are widely perceived to have been bubbles that were not, in fact, widespread misallocations of investment capital.

Re: Learning to Love the AI Bubble

#25

Post by seanmcdirmid »

bluGill wrote: post #7
acollins1331 wrote: post #6

Earlier quoted context omitted.

I personally would put my money on Nvidia when it comes to most value in AI projects, but I don't have inside knowledge with either company.

Nvidia makes shovels. They stand to make a lot of money no matter what AI works out (possibly more than anyone else), all that without having to do any AI themselves.

Making shovels for the AI crowd is also a lot safer than making them for the bit miners.

Re: Learning to Love the AI Bubble

#26

Post by colinmhayes »

nostalgk wrote: post #12
lkrubner wrote: post #9

Right now there are 5 comments on this post, and all 5 focus on the issue of how to invest in AI. That suggests something about how Hacker News has changed over the years. There is a larger focus on “what stock can I buy” and somewhat less focus on working with the actual tech.

If I wanted to get started learning about machine learning/AI, where is the best place to do that? I'm a functional programmer who's learned mostly everything about software engineering on the job, and I feel like I don't have the background I need to get started on it; I struggle immensely with math, but have had no problem with my career in software yet thus. I am going to be traveling for a machine learning conven…

Machine learning is literally just math. You could learn some plug and play without understanding the math, but I'm not sure you would be able to solve any real problems.

Re: Learning to Love the AI Bubble

#28

Post by 6gvONxR4sf7o »

I think this bubble's a weird one in that it's a very different size depending on your point of view. Everything is getting rebranded as AI. Taking averages, grouped by something? That's AI now. Using algorithms to do different things for different people? That's AI now. At least it will be in your press coverage.

One thing is AI to the press and public, another thing is AI to investors, yet another thing for nontechnical workers, and not even a single cohesive thing to people building it all. Wherever you personally draw your lines between AI and not AI, the boundaries do keep expanding. Does that mean the bubble is growing? There are undoubtably more people doing machine learning, and there are more people doing statistics, and more people solving optimization problems, and each other thing that we call AI, but the "AI" label is growing faster than all that. It's a weird bubble. If it pops, does that mean there will be fewer jobs for people like me, or does it just mean people will just stop calling it AI? Or is this just a word's meaning changing and not a large bubble?

This story comes to mind: http://web.archive.org/web/20190626012618/https://gen.medium...

Re: Learning to Love the AI Bubble

#29

Post by tim333 »

epr wrote: post #22

> Not all bubbles have negative consequences for the economy Unless we are using a different definition of "bubble" than it would seem (to me) most people intend when they use that word, this is a factually incorrect statement. If widespread misallocation of investment capital does not "hurt" the economy, then what does? If capital is invested with a positive outcome for the wrong reasons, then that certainly would n…

Some economists argued the dot com bubble was a net positive for the economy. While tanking dot coms lost money for their investors the positive externalities like funding broadband networks outweighed that.

Along the lines that Webvan may have tanked but we ended up with Google and Wikipedia. I imagine likewise that most of the present AI startups will tank but we'll end up with useful AI of serious value.

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