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One data scientist on the hype around artificial intelligence (2017)

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Re: One data scientist on the hype around artificial intelligence (2017)

#11

Post by rm999 »

This is a negative value article. It spends a lot of time dwelling on a low-value semantic argument that "when people in business say 'AI' they really mean machine learning". Sure, but these words have been used synonymously for a long time - my grad degree ~15 years ago concentrating in machine learning was called "AI"; who cares? Then the article goes on to claim:

>I anticipate that after this passes, we can start to do the right thing — focusing on using machine learning to build things that are meaningful and realistic.

UGHHH. Why did you hide this in a long article making the 180 degree contradictory point that AI (which really means machine learning, remember?) is dumb?

This article is a disservice to its reader because it downplays a huge shift in the world that any ML practitioner should understand very well: machine learning/AI will ultimately replace a lot of what humans do, and it's moving at a faster pace than ever. I've led several small-ish projects (1-2 people, 3-6 months) that could replace dozens or even 1000s of experts in their respective fields. There are thousands of people like me, and there are more every day. The buzz may wear off, in the same way Time Magazine stopped talking about how the internet was going to take over the world after the dot-com crash, but the effects and the efforts will continue unabated.

Re: One data scientist on the hype around artificial intelligence (2017)

#14

Post by selljamhere »

> artificial intelligence (AI), a sub-branch of machine learning

I could have a failed mental model, but I'm under the impression that the relationship is the other way around. AI is a broad field encompassing various strategies to build intelligent machines. ML is one particular strategy where large volumes (think Big Data) of training data is used to teach by example. (Which makes Deep Learning a subset of ML, where "deep" neural networks are at play.)

Re: One data scientist on the hype around artificial intelligence (2017)

#15

Post by psyc »

rm999 wrote: post #11

This is a negative value article. It spends a lot of time dwelling on a low-value semantic argument that "when people in business say 'AI' they really mean machine learning". Sure, but these words have been used synonymously for a long time - my grad degree ~15 years ago concentrating in machine learning was called "AI"; who cares? Then the article goes on to claim: >I anticipate that after this passes, we can start…

Whenever there's a big controversy, especially when it's about whether a "this" is or isn't a "that", the first thing I assume is that people are trying to make a taxonomy out of a continuum. I believe AI is like that. Just as there's a continuum from replicating molecule to god-like alien, there's an analogous continuum from a NAND gate to strong AI.

Re: One data scientist on the hype around artificial intelligence (2017)

#16

Post by solomatov »

This is not hype. See here: https://rajpurkar.github.io/SQuAD-explorer/

In this benchmark people or models are given a text, and later asked a number of questions. Questions are quite real. See for example here: https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/S...

Models already have performance which are as good as human's. This is real. This is not hype.

Re: One data scientist on the hype around artificial intelligence (2017)

#17

Post by solomatov »

ghaff wrote: post #10
strebler wrote: post #6

This is a really good article, I'm impressed. If you read only one deep learning article this month, make it this one. I'm going to borrow that analogy of "teenagers perceptions of sex" - it's hilariously accurate for deep learning.

I fully agree that big data has essentially been renamed to AI. Which makes sense because AI today ~= ML/DL which require lots of data. And, as someone who went through the data warehousing fad in the late 90s, there's a lot of naive belief in pouring in a lot of data and magic happening. That said, there has been a lot of advance that, once it's happened, we just don't call it AI any longer. Route optimization (Goog…

Big data is not AI. Big data is processing of a giant datasets with quite classic models, such as Logistic Regression in a distributed way. That's what frameworks such as Spark and Hadoop do. AI or deep learning is different. Usually, they don't distribute across many machines so well.

Re: One data scientist on the hype around artificial intelligence (2017)

#19

Post by mark_l_watson »

solomatov wrote: post #16

This is not hype. See here: https://rajpurkar.github.io/SQuAD-explorer/ In this benchmark people or models are given a text, and later asked a number of questions. Questions are quite real. See for example here: https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/S... Models already have performance which are as good as human's. This is real. This is not hype.

I agree! The question answering datasets, and some of the models built with them are getting good. I work on GAN and general classifiers at work, but on my own time my main interest is in sequential language models.

Re: One data scientist on the hype around artificial intelligence (2017)

#20

Post by microtherion »

strebler wrote: post #6

This is a really good article, I'm impressed. If you read only one deep learning article this month, make it this one. I'm going to borrow that analogy of "teenagers perceptions of sex" - it's hilariously accurate for deep learning.

The teenage sex joke used to be a C++ joke: https://simplesassim.wordpress.com/2004/01/07/c-is-like-teen...
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