5 ms·

I can't be the only one that considers all these AI articles just smoke and mirror puff pieces to prop up a company's value by capitalizing on the hype (hysteri

by lowglow 11y ago

I can't be the only one that considers all these AI articles just smoke and mirror puff pieces to prop up a company's value by capitalizing on the hype (hysteria?), can I? I think the first flag is that the journalists don't seem to really understand the technical capabilities or limitations of current ML/AI applications. They accept grandiose claims at face value because there is no way to measure the real potential of AI (which the promise of seems limitless, so anything appears plausible especially coming from a big company like GOOG). I think there are a couple of really overhyped areas right now, AR/AI/ML and IoT/IoE. Now while I don't mind the attention and money being thrown at tech, I can't help but feel we're borrowing more against promises, hopes, and dreams, while simultaneously under-delivering and I think that's going to hurt tech's image and erode investor confidence sooner than later.

hiddencost 11y ago
A lot of things that were impractical 5-10 years ago are now moving out of the domain of the biggest companies to the smaller ones. Applications involving computer vision and speech recognition are now buildable by small companies, which will hopefully yield a proliferation of really interesting novel applications. Sure, we don't have terminator-style AI, but honestly people using the term AI need to shut up, a lot. There is no AI, these days, just massively creaky giant ML systems with a host of ph.d's being thrown onto the fire to keep them running. But the ML applications are super cool.
- Houshalter 11y ago
  We lost the word "AI" literally decades ago. Everything from search algorithms to machine learning to genetic algorithms to video game bots are called AI. The cool kids use the word "AGI" now. There is a common expression that "AI is whatever computers can't do yet." At one time computers couldn't play board games or do vision, so those things were called AI.
  - throwaway873719 11y ago
    It seems like your first and second paragraphs express opposite opinions. In the former you seem dismayed by the over-application/overhyping of the term "AI"; in the latter you seem frustrated by the high and ever-increasing bar for categorizing systems as "AI". Am I misinterpreting you?
    - Houshalter 11y ago
      My comment can be read two ways, and neither way is wrong. I wasn't really expressing an opinion as much as bringing up relevant facts. People label things that we don't know how to do yet "AI". And then when these hard problems are solved, they seem like they are not really "intelligent". This leads to both overuse and trivialization of the word, but also moving goal posts for the field. And actual progress isn't taken seriously, because nothing feels like intelligence when you understand it. It's all a Mysterious Answer (http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_questions/ http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_...), a codeword for magic (http://lesswrong.com/lw/ix/say_not_complexity/ http://lesswrong.com/lw/ix/say_not_complexity/).
- joe_the_user 11y ago
  The Chinese curse might be now updated to "may you wind-up dependent on 'really interesting novel applications'..." Machine learning-derived applications are impressive and give a good show until one winds up in a situation where they are expected to work reliably. Sure, it's nice that the insurance company's phone-based, voice-recognition-driven, registration/etc system can understand 99% of the choices people give them - except total failure in that 1% is actually going to leave a large population unserved and angry. Of course the company has keypad backup - except they don't 'cause that would cost the money they claimed voice recognition could save, etc. Machine learning apps are great for situations where 1) You don't expect 100% reliably and the degree of non-reliably doesn't have to even be quantified. 2) Either you are accept that they'll degrade over time and have an army of tuners and massive data collect to keep that from happening OR you are dealing with an environment you completely control. This is kind of the conditions for regular automation - except even more so.
xxs 11y ago
>>I can't be the only one that considers all these AI articles just smoke and mirror puff pieces to prop up the companies value by capitalizing on the hype (hysteria?) You're not. So far I have not seen/heard anything remotely resembling AI. Neural nets are just weighted graphs.
- voodoomagicman 11y ago
  Yeah, but maybe that is all brains are too?
  - riffraff 11y ago
    they might be, but * we still don't know if they are * we still don't know how they effectively work * the scale of the things is far from the computational capabilities of my phone (10^11 neurons and 10^15 synapses for a human brain) (But of course AI means a lot of things, not just "thinking androids")
    - oilywater 11y ago
      Well, in 2025 it will be exactly at the computational capability of a brain.
- vonnik 11y ago
  Is anyone arguing that machine learning is not AI? The gist of the article is that Google is leaning toward ML/DL and away from the rules engines/Knowledge Graph. The headline is a shorthand, which, although it could be more precise, is not inaccurate.
  - igravious 11y ago
    Interesting that you feel that. The article mentions nothing about Google's Knowledge Graph. I don't have any privileged insight into Google, just the same surface data as the rest of you all - but I would say that, if anything, Google's Knowledge Graph can fit with _both_ a rules engine strategy and a machine learning one. How is Google going to "organise the world's information" unless it has a model of how all the facts in the world line up? That model is the Knowledge Graph. How does Google intend to map queries that it has never seen before to pages in its vast index? With the help of the Knowledge Graph and natural language processing and machine learning. I'm going to try to articulate something here that I've not fully worked out but that I'm sort of intuiting so cut me some slack for the next paragraph :) People keep banging on about machine learning and the impact that it is having. This is undeniable. But we can see even from AlphaGo that a hybrid approach that combines artificial neural nets with some sort of symbolic system outperforms neural nets on their own. For AlphGo that symbolic system is tied to the mechanics of the game of Go. For internet search that symbolic system is a generalised knowledge graph. Do you get what I mean? I'd love to hear what others think …
hh2222 11y ago
And ... I can't be the only one that thinks Google search results just aren't that good anymore.
- scholia 11y ago
  I also think the quality has gone down. But it seems to me it's at least partly deliberate: the quality has gone down because "freshness" has gone up.
  - bones6 11y ago
    Sometimes I get the vibe that it's a weird self-fulfilling prophesy of terrible SERPs. You reward freshness too much, so then people play that game. But you also punish duplicate content at the same time so the best content, if it already exists but is not fresh, naturally has to fall off.
- jbhatab 11y ago
  I couldn't disagree more. They have only gotten better every single year for me. Undeniably better every year.
- awqrre 11y ago
  I really wish that I could switch back to google's algo from 10 years ago...
  - minwcnt5 11y ago
    That is pure nostalgia talking. I strongly suspect that if you did you would be appalled and want to switch back after only a few searches. Search in 2016 is leaps and bounds beyond what it was in 2006.
    - CaptSpify 11y ago
      This is very much a YMMV thing, but what improvements have you seen?
bduerst 11y ago
We've had artificial intelligence since you could play a computer at chess, but the expectation has always been a mechanized Arnold Schwarzenegger or Hal 9000. The difference today is the scale at which it operates in our daily lives, and the accelerated rate at which it is growing.
teaneedz 11y ago
Thank you. Exactly my feelings.
Fiahil 11y ago
You can add to this, the gigantic misuse of the term "AI" when journalists really want to say "robotics". I don't mind clever shortcuts when you need to explain something abstract or invisible to non-technical people, but, at some point, somebody will have to tell them they're two completely different fields.
rsingel 11y ago
I thought the same thing when I saw the title. And then I saw the byline: Cade Metz. And I read the story. Metz understands tech. Metz got this story right. So while you may be right that many AI articles are smoke-and-mirrors from journalists who don't get the tech, I think you picked the wrong article to make that point about.
- SixSigma 11y ago
  > The truth is that even the experts don’t completely understand how neural nets work. That is not understanding.
smira7 11y ago
The funny part is that it's not illegal for AI to foment.
tim333 11y ago
I wouldn't say this particular article is a smoke and mirror puff piece to prop up the companies value. Now other ones you could argue that. 'The Grid' springs to mind. (https://www.quora.com/Has-anyone-heard-about-the-Grid-AI-websites-that-design-themselves-Does-it-really-work-and-can-it-replace-the-manual-way-of-building-a-website https://www.quora.com/Has-anyone-heard-about-the-Grid-AI-web...)
putaside 11y ago
Winter is coming.
paganel 11y ago
> I think there are a couple of really overhyped areas right now, AR/AI/ML and IoT/IoE. Now while I don't mind the attention and money being thrown at tech, I can't help but feel we're borrowing more against promises, hopes, and dreams, while simultaneously under-delivering and I think that's going to hurt tech's image and erode investor confidence sooner than later. I became interested in natural language processing in the early 2000s, more as a hobby and as part of my personal projects, but even so, I remember that back then most of the AI-related discussions on things like forums and mailing lists were mentioning the AI winter as the big bad wolf that had killed an entire industry. It also killed LISP, they were saying. Interesting to see that that memory seems to have faded away to the distant past.
bitcuration 11y ago
yep, this apparently has been a wall street operation than anything else. Google needs the capital to transform and sustain the decline of web search revenue.

by lowglow 11y ago

hiddencost 11y ago

A lot of things that were impractical 5-10 years ago are now moving out of the domain of the biggest companies to the smaller ones. Applications involving computer vision and speech recognition are now buildable by small companies, which will hopefully yield a proliferation of really interesting novel applications. Sure, we don't have terminator-style AI, but honestly people using the term AI need to shut up, a lot. There is no AI, these days, just massively creaky giant ML systems with a host of ph.d's being thrown onto the fire to keep them running. But the ML applications are super cool.

Houshalter 11y ago
We lost the word "AI" literally decades ago. Everything from search algorithms to machine learning to genetic algorithms to video game bots are called AI. The cool kids use the word "AGI" now. There is a common expression that "AI is whatever computers can't do yet." At one time computers couldn't play board games or do vision, so those things were called AI.
- throwaway873719 11y ago
  It seems like your first and second paragraphs express opposite opinions. In the former you seem dismayed by the over-application/overhyping of the term "AI"; in the latter you seem frustrated by the high and ever-increasing bar for categorizing systems as "AI". Am I misinterpreting you?
  - Houshalter 11y ago
    My comment can be read two ways, and neither way is wrong. I wasn't really expressing an opinion as much as bringing up relevant facts. People label things that we don't know how to do yet "AI". And then when these hard problems are solved, they seem like they are not really "intelligent". This leads to both overuse and trivialization of the word, but also moving goal posts for the field. And actual progress isn't taken seriously, because nothing feels like intelligence when you understand it. It's all a Mysterious Answer (http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_questions/ http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_...), a codeword for magic (http://lesswrong.com/lw/ix/say_not_complexity/ http://lesswrong.com/lw/ix/say_not_complexity/).
joe_the_user 11y ago
The Chinese curse might be now updated to "may you wind-up dependent on 'really interesting novel applications'..." Machine learning-derived applications are impressive and give a good show until one winds up in a situation where they are expected to work reliably. Sure, it's nice that the insurance company's phone-based, voice-recognition-driven, registration/etc system can understand 99% of the choices people give them - except total failure in that 1% is actually going to leave a large population unserved and angry. Of course the company has keypad backup - except they don't 'cause that would cost the money they claimed voice recognition could save, etc. Machine learning apps are great for situations where 1) You don't expect 100% reliably and the degree of non-reliably doesn't have to even be quantified. 2) Either you are accept that they'll degrade over time and have an army of tuners and massive data collect to keep that from happening OR you are dealing with an environment you completely control. This is kind of the conditions for regular automation - except even more so.

xxs 11y ago

>>I can't be the only one that considers all these AI articles just smoke and mirror puff pieces to prop up the companies value by capitalizing on the hype (hysteria?) You're not. So far I have not seen/heard anything remotely resembling AI. Neural nets are just weighted graphs.

voodoomagicman 11y ago
Yeah, but maybe that is all brains are too?
- riffraff 11y ago
  they might be, but * we still don't know if they are * we still don't know how they effectively work * the scale of the things is far from the computational capabilities of my phone (10^11 neurons and 10^15 synapses for a human brain) (But of course AI means a lot of things, not just "thinking androids")
  - oilywater 11y ago
    Well, in 2025 it will be exactly at the computational capability of a brain.
vonnik 11y ago
Is anyone arguing that machine learning is not AI? The gist of the article is that Google is leaning toward ML/DL and away from the rules engines/Knowledge Graph. The headline is a shorthand, which, although it could be more precise, is not inaccurate.
- igravious 11y ago
  Interesting that you feel that. The article mentions nothing about Google's Knowledge Graph. I don't have any privileged insight into Google, just the same surface data as the rest of you all - but I would say that, if anything, Google's Knowledge Graph can fit with _both_ a rules engine strategy and a machine learning one. How is Google going to "organise the world's information" unless it has a model of how all the facts in the world line up? That model is the Knowledge Graph. How does Google intend to map queries that it has never seen before to pages in its vast index? With the help of the Knowledge Graph and natural language processing and machine learning. I'm going to try to articulate something here that I've not fully worked out but that I'm sort of intuiting so cut me some slack for the next paragraph :) People keep banging on about machine learning and the impact that it is having. This is undeniable. But we can see even from AlphaGo that a hybrid approach that combines artificial neural nets with some sort of symbolic system outperforms neural nets on their own. For AlphGo that symbolic system is tied to the mechanics of the game of Go. For internet search that symbolic system is a generalised knowledge graph. Do you get what I mean? I'd love to hear what others think …

hh2222 11y ago

And ... I can't be the only one that thinks Google search results just aren't that good anymore.

scholia 11y ago
I also think the quality has gone down. But it seems to me it's at least partly deliberate: the quality has gone down because "freshness" has gone up.
- bones6 11y ago
  Sometimes I get the vibe that it's a weird self-fulfilling prophesy of terrible SERPs. You reward freshness too much, so then people play that game. But you also punish duplicate content at the same time so the best content, if it already exists but is not fresh, naturally has to fall off.
jbhatab 11y ago
I couldn't disagree more. They have only gotten better every single year for me. Undeniably better every year.
awqrre 11y ago
I really wish that I could switch back to google's algo from 10 years ago...
- minwcnt5 11y ago
  That is pure nostalgia talking. I strongly suspect that if you did you would be appalled and want to switch back after only a few searches. Search in 2016 is leaps and bounds beyond what it was in 2006.
  - CaptSpify 11y ago
    This is very much a YMMV thing, but what improvements have you seen?

bduerst 11y ago

We've had artificial intelligence since you could play a computer at chess, but the expectation has always been a mechanized Arnold Schwarzenegger or Hal 9000. The difference today is the scale at which it operates in our daily lives, and the accelerated rate at which it is growing.

teaneedz 11y ago

Thank you. Exactly my feelings.

Fiahil 11y ago

You can add to this, the gigantic misuse of the term "AI" when journalists really want to say "robotics". I don't mind clever shortcuts when you need to explain something abstract or invisible to non-technical people, but, at some point, somebody will have to tell them they're two completely different fields.

rsingel 11y ago

I thought the same thing when I saw the title. And then I saw the byline: Cade Metz. And I read the story. Metz understands tech. Metz got this story right. So while you may be right that many AI articles are smoke-and-mirrors from journalists who don't get the tech, I think you picked the wrong article to make that point about.

SixSigma 11y ago
> The truth is that even the experts don’t completely understand how neural nets work. That is not understanding.

smira7 11y ago

The funny part is that it's not illegal for AI to foment.

tim333 11y ago

I wouldn't say this particular article is a smoke and mirror puff piece to prop up the companies value. Now other ones you could argue that. 'The Grid' springs to mind. (https://www.quora.com/Has-anyone-heard-about-the-Grid-AI-websites-that-design-themselves-Does-it-really-work-and-can-it-replace-the-manual-way-of-building-a-website https://www.quora.com/Has-anyone-heard-about-the-Grid-AI-web...)

putaside 11y ago

Winter is coming.

paganel 11y ago

> I think there are a couple of really overhyped areas right now, AR/AI/ML and IoT/IoE. Now while I don't mind the attention and money being thrown at tech, I can't help but feel we're borrowing more against promises, hopes, and dreams, while simultaneously under-delivering and I think that's going to hurt tech's image and erode investor confidence sooner than later. I became interested in natural language processing in the early 2000s, more as a hobby and as part of my personal projects, but even so, I remember that back then most of the AI-related discussions on things like forums and mailing lists were mentioning the AI winter as the big bad wolf that had killed an entire industry. It also killed LISP, they were saying. Interesting to see that that memory seems to have faded away to the distant past.

bitcuration 11y ago

yep, this apparently has been a wall street operation than anything else. Google needs the capital to transform and sustain the decline of web search revenue.