Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

The Economics of AI Today

thegradient.pub

Post reply on HN
Print view View original

11–20 of 20 posts

Re: The Economics of AI Today

#11

Post by ksec »

netcan wrote: post #9

At least in my bubble, AI discussions have been going in predictable ways.. and getting grounded in the same places. First, we try to build the (proverbial) foundation: What is AI? What is intelligence? Is it general? Lots of places to get stuck here. Can machines understand meaning? Is general intelligence statistical. Can it be? No real way of settling these, so we have poor foundations. Then we ask: What can it do…

>Computerisation of offices has not measurably increased productivity since the 80s/90s[1],

As far as I can tell. It isn't AI, or whatever technology that is not getting productivities increases in business. When was the last time you saw a CRM / ERP replacement that had any productivities increase? It seems there is a very clear divider in between all Technology Companies vs Other non-tech company. It is that No one knows how to best integrate the two to maximise potentials. Only the one which have their feet on both side ( Amazon ) seems to understand it.

Re: The Economics of AI Today

#12

Post by netcan »

ksec wrote: post #11
netcan wrote: post #9

At least in my bubble, AI discussions have been going in predictable ways.. and getting grounded in the same places. First, we try to build the (proverbial) foundation: What is AI? What is intelligence? Is it general? Lots of places to get stuck here. Can machines understand meaning? Is general intelligence statistical. Can it be? No real way of settling these, so we have poor foundations. Then we ask: What can it do…

>Computerisation of offices has not measurably increased productivity since the 80s/90s[1], As far as I can tell. It isn't AI, or whatever technology that is not getting productivities increases in business. When was the last time you saw a CRM / ERP replacement that had any productivities increase? It seems there is a very clear divider in between all Technology Companies vs Other non-tech company. It is that No one…

I think it runs deeper than "can't figure out how to X."

We're very good at figuring out productivities when dealing with a factory or somesuch. A transport authority or facebook "business headquarters" doesn't interplay with technology in the same ways.

Re: The Economics of AI Today

#13

Post by ArtWomb »

Well-sourced conference report. Actually saves me a lot of time. To summarize: it's still the Wild West in AI. But there is broad recognition that governance is essential

I'll just add one more report, as if the dozens already mentioned were not enough. It's from Berkeley's Center For Long-Term Cybersecurity. And it addresses the enormous challenge of securing AI systems from adversarial attack. A glimpse into the vortex of how the "industrialization of AI" creates a self-perpetuating, fractal-like cycle of eternal dependencies. Requiring us to create ever stronger AI to protect and serve the AI on which our new engineering platforms will be founded upon

https://cltc.berkeley.edu/wp-content/uploads/2019/02/CLTC_Cu...

It stands to reason then, the ultimate AI-mediated prediction problem is predicting the impacts of AI itself ;)

Re: The Economics of AI Today

#14

Post by trycrmr »

Had hoped an article like this would shed some light on the environmental impacts of the additional compute required to build and maintain a feature backed by AI. My understanding is it takes significantly more compute + data, and therefore electricity, to build and maintain a feature baked by AI. As AI becomes increasingly accessible, particularly through offerings from cloud providers, the power consumption would increase faster than when folks were exclusively writing scripts/uploading binaries to process transactions. My hope is it's negligible. Haven't had the time to crunch numbers to figure this out as it's out of my daily lane.

Maybe I skimmed the article too fast and missed it while enjoying my coffee and bagel sandwich. Let me know if that happened.

Re: The Economics of AI Today

#15

Post by trycrmr »

trycrmr wrote: post #14

Had hoped an article like this would shed some light on the environmental impacts of the additional compute required to build and maintain a feature backed by AI. My understanding is it takes significantly more compute + data, and therefore electricity, to build and maintain a feature baked by AI. As AI becomes increasingly accessible, particularly through offerings from cloud providers, the power consumption would i…

*backed

Re: The Economics of AI Today

#16

Post by ksec »

netcan wrote: post #12
ksec wrote: post #11

Earlier quoted context omitted.

>Computerisation of offices has not measurably increased productivity since the 80s/90s[1], As far as I can tell. It isn't AI, or whatever technology that is not getting productivities increases in business. When was the last time you saw a CRM / ERP replacement that had any productivities increase? It seems there is a very clear divider in between all Technology Companies vs Other non-tech company. It is that No one…

I think it runs deeper than " can't figure out how to X. " We're very good at figuring out productivities when dealing with a factory or somesuch. A transport authority or facebook "business headquarters" doesn't interplay with technology in the same ways.

>I think it runs deeper than "can't figure out how to X."

Yes. I wish there is an in depth article to explain some of these observation we see in real life.

Re: The Economics of AI Today

#17

Post by unishark »

Animats wrote: post #2

That's kind of broad. Also, the robots shown have very little "AI". Maybe machine learning has reached a peak. It's routine now to make classifiers that are about 90% accurate, and really hard to get much beyond that. What we really have are systems which extract lots of signals from an input set and construct a statistical model that maps signals to results. This works moderately well with enough data, but hits a li…

Don't know anything about the amazon robots specifically, but manufacturing robots commonly use computer vision methods which perform a lot better than 90 percent. I don't really agree with the claims of 99.9% accuracy and being generally superior to humans in this area. But in practical terms a vast number of new vision tasks are solved problems now, a really huge achievement.

Though on the "curve fitting" versus "general intelligence" argument, I agree with you. The robots still can only do exactly what we tell to do, we just don't need to be quite so exact in telling them how to do it. But for the most part, this is only gained by having to show them very very thoroughly how to do it by using tons of data.

Re: The Economics of AI Today

#18

Post by unishark »

TulliusCicero wrote: post #5
Animats wrote: post #2

That's kind of broad. Also, the robots shown have very little "AI". Maybe machine learning has reached a peak. It's routine now to make classifiers that are about 90% accurate, and really hard to get much beyond that. What we really have are systems which extract lots of signals from an input set and construct a statistical model that maps signals to results. This works moderately well with enough data, but hits a li…

> Also, the robots shown have very little "AI". That's what happens when you change what "AI" means every time there's a breakthrough.

The bar has been getting raised overall though, as more computer tasks get taken for granted. Unless your requirement is nothing short of scifi machine consciousness.

Re: The Economics of AI Today

#19

Post by Animats »

2sk21 wrote: post #7
Animats wrote: post #2

That's kind of broad. Also, the robots shown have very little "AI". Maybe machine learning has reached a peak. It's routine now to make classifiers that are about 90% accurate, and really hard to get much beyond that. What we really have are systems which extract lots of signals from an input set and construct a statistical model that maps signals to results. This works moderately well with enough data, but hits a li…

Even the best attempts at task-oriented dialog currently using purely ML techniques are pathetically bad. Having worked in the field for a while, one thing that I have observed is that chatbots simply discard the bulk of the useful information that user provide them. They then fall back to asking users direct questions. Apart from this, they can only handle limited information retrieval tasks for which training data…

I know; I've been playing around with "Rasa", a chatbot system based on Tensorflow. All the ML part does is match up canned answers with incoming questions. Someone has to provide all the answers and a few questions for each answer, then look at errors from user input and manually classify them for retraining. The rest of the system is just a template system for implementing phone trees.

Interestingly, MIT's START questioning-answering system is pretty good.[1] That project started in 1993, before machine learning, and it's more "traditional AI". Try it and comment.

[1] http://start.csail.mit.edu/index.php

Post reply on HN