Answers.Body: <p>Our current approaches to AI are too inefficient to result in anything remotely close to what an average human would perceive as artificial senient beings.</p>
  
  <p>Current approaches to AI involve a simulation of our own capacity for learning by creating fully functional computation machines capable of re-programming themselves. While that's definitely a good start with respect to understanding the nature of intelligence, it's still a far cry from actually creating genuine artificial intelligence.</p>
  
  <p>It is not just our capacity to learn that evolved. Our very brains themselves evolved from rudimentary biochemical components at the intra-cellular level to the fascinating, complex organs they are today, along with our bodies as a whole evolving from simple single cell life to homo sapiens. So to create genuine artificial intelligence, it may actually make most sense to first start with replicating that process : creating artificial life with the capacity to evolve. It may actually make most sense to first start with creating artificial DNA and artificial cells, and move on from there.</p>
  
  <p>Anyway, in <a href="http://www.alexstjohn.com/WP/2015/06/24/no-azimov-ai/" rel="nofollow">this article</a> as well as <a href="http://www.alexstjohn.com/WP/2016/06/15/things-dont-compute/" rel="nofollow">this article</a>, Silicon Valley renegade <a href="https://en.wikipedia.org/wiki/Alex_St._John" rel="nofollow">Alex St John</a> goes in greater detail on why something like <a href="https://en.wikipedia.org/wiki/Skynet_(Terminator)" rel="nofollow">Skynet</a>, <a href="http://irobot.wikia.com/wiki/VIKI" rel="nofollow">V.I.K.I.</a> or anything like it is unlikely in the near future and may even never be within our grasp and why our current approach to artificial intelligence is a bad one.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T08:33:55.047Z
Answers.Text: A simulation of a proof *is* a proof. Whether a simulation of intelligence *is* intelligence is an open question which (with our current knowledge of physics) appears impossible to answer in the negative based purely on theoretical arguments, but could empirically be answered positively via something such as the Turing Test.
Answers.UserDisplayName: NietzscheanAI
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T08:53:02.963Z
Answers.Text: @NietzscheanAI : The article I referenced explains in greater detail why a simulation of intelligence isn't the same as actual intelligence.
Answers.UserDisplayName: John Slegers
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T08:59:48.110Z
Answers.Text: I read it. Many leading physicists (e.g. David Deutsch) believe that the universe is a quantum computer, which can be simulated by a classical computer.
Answers.UserDisplayName: NietzscheanAI
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T09:18:02.680Z
Answers.Text: @NietzscheanAI : Yes, the universe does appear to be a giant quantum computer. I agree with you here. The problem with our current approaches to AI isn't so much that artificial brains are impossible, but that we're trying to create brains without first understanding how brains are created in living beings. Starting with creating artificial life that can evolve towards higher forms of existence may be a better approach to developing AI, as that is how we got here today... See also [this other article](http://www.alexstjohn.com/WP/2016/06/15/things-dont-compute/) by the same author.
Answers.UserDisplayName: John Slegers
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T09:22:00.383Z
Answers.Text: the argument about 'starting with simpler forms of life' is well-established in the AI community,  originating with work by Rodney Brooks in the 1990s that established the 'New AI' of 'embodied cognition'. See the papers 'Elephants don't play chess', 'Intelligence without Representation' and the book 'Pre-Cambrian Intelligence' for more details.
Answers.UserDisplayName: NietzscheanAI
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T09:34:29.280Z
Answers.Text: ->The universe is a quantum computer (maybe)
  -> The universe has developed intelligence, in our understanding, by starting with simple life and guiding it towards something more complicated by Darwinian principles
  -> Starting with simple forms and guiding them is, as Nietz points out, well-established.
  -> Quantum evolutionary algorithms are already heralded for a speedup (e.g. https://arxiv.org/ftp/arxiv/papers/1303/1303.1243.pdf). 
  
  Leaves you wondering if the argument goes full circular doesn't it?
Answers.UserDisplayName: Tim Atkinson
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T10:09:52.457Z
Answers.Text: @NietzscheanAI : Our current approaches to AI are too inefficient to ever result in anything remotely close to what an average human would perceive as artificial senient beings. St John's point was - and I tend to agree - that it makes more sense to first start with artificial DNA and artificial cells with evolutionary capacities and set move on from there.
Answers.UserDisplayName: John Slegers
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T11:29:57.267Z
Answers.Text: @Atkrye : I modified my initial answer to add more clarification on my position.
Answers.UserDisplayName: John Slegers
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T08:29:23.513Z
Answers.LastActivityDate: 2016-08-24T12:04:52.007Z
Answers.LastEditDate: 2016-08-24T12:04:52.007Z
Answers.UserDisplayName: John Slegers
Answers.Body: <p>Based on the success of IBM Watson and the amazing advances in tackling numerous hard tasks using deep learning in the past 3 years, I think a large high-tech company like Google or Amazon will create a useful conversational bot in no more than 10 years.  (I've worked on the fringes of AI for 25 years and have followed the tech for even longer.  These are exciting times.)</p>
  
  <p>Initially, your very own AI companion ("Her"?) won't be capable of deeper philosophical conversation or insightful interpretation of novels or the human condition.  But it will be able to write / speak in full paragraphs on topics like the best choice among 5 possible routes between point A and B, or summarizing the plot of a book or the gist of a news story, or why one product is better than another (e.g. based on assessing hundreds of Amazon reviews).  And yes, it will be able to understand full spoken sentences from you, and generate both queries and answers.</p>
  
  <p>I'm convinced such a bot <em>will</em> be useful enough that most of us will want one.  Of course you won't need to buy a special piece of hardware, like the Amazon Echo.  It'll be available via software on your smartphone, though the computing is likely to reside on the cloud (since that's where the data is).  </p>
  
  <p>Frankly, I think this is where the next innovations in smartphones will arise -- verbal interfaces that do a better job hearing and speaking and disambiguating using context about you and the kinds of questions you are likely to ask.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-23T15:21:07.420Z
Answers.LastActivityDate: 2016-08-23T15:21:07.420Z
Answers.UserDisplayName: Randy
Answers.Body: <blockquote>
    <p>"heavier-than-air flying machines are impossible" <em>_ Lord Kelvin 1895</em> </p>
  </blockquote>
  
  <p>7 years later the Wright brothers built one.</p>
  
  <hr>
  
  <p>Currently we have many powerful narrow AI (good at special tasks) but we have no idea how to unify them into a single system like in a biological brain. </p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-06T20:30:10.680Z
Answers.LastActivityDate: 2016-08-07T07:02:48.480Z
Answers.LastEditDate: 2016-08-07T07:02:48.480Z
Answers.UserDisplayName: Conor Cosnett
Answers.Body: <p>We are absolutely nowhere near, nor do we have any idea how to bridge the gap between what we can currently do and what is depicted in these films.</p>
  
  <p>The current trend for DL approaches (coupled with the emergence of data science as a mainstream discipline) has led to a lot of popular interest in AI.</p>
  
  <p>However, researchers and practitioners would do well to learn the lessons of the 'AI Winter' and not engage in hubris or read too much into current successes.</p>
  
  <p>For example:</p>
  
  <ul>
  <li>Success in transfer learning is very limited. </li>
  <li>The 'hard problem' (i.e. presenting the 'raw, unwashed environment' to the machine and having it come up with a solution from scratch) is not being
  addressed by DL to the extent that it is popularly portrayed: expert human knowledge is still required to help decide how the input should be framed, tune parameters, interpret output etc.</li>
  </ul>
  
  <p>Someone who has enthusiasm for AGI would hopefully agree that the 'hard problem' is actually the only one that matters. Some years ago, a famous cognitive scientist said "We have yet to successfully represent <em>even a single concept</em> on a computer". </p>
  
  <p>In my opinion, recent research trends have done little to change this.</p>
  
  <p>All of this perhaps sounds pessimistic - it's not intended to. None of us want another AI Winter, so we should challenge (and be honest about) the limits of our current techniques rather than mythologizing them.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-26T01:26:35.383Z
Answers.Text: You said in the deleted comments that it was Douglas Hofstadter who said "We have yet to successfully represent even a single concept on a computer". Where can I find a reference that supports that?
Answers.UserDisplayName: nbro
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2016-08-06T18:54:48.577Z
Answers.LastActivityDate: 2016-08-06T19:04:52.397Z
Answers.LastEditDate: 2016-08-06T19:04:52.397Z
Answers.UserDisplayName: NietzscheanAI
Body: <p>Are there any research teams that attempted to create or have already created an AI robot that can be as close to intelligent as these found in <a href="https://en.wikipedia.org/wiki/Ex_Machina_(film)" rel="nofollow noreferrer"><em>Ex Machina</a></em> or <em><a href="https://en.wikipedia.org/wiki/I,_Robot_(film)" rel="nofollow noreferrer">I, Robot</em></a> movies?</p>
  
  <p>I'm not talking about full awareness, but an artificial being that can make its own decisions and physical and intellectual tasks that a human being can do?</p>
  
Tags: <research><agi>
Title: How close are we to creating Ex Machina?
UserDisplayName: kenorb
ThreadText: # How close are we to creating Ex Machina?
  
  (Asked by: username_0 on 2016-08-06)
  
  Are there any research teams that attempted to create or have already created an AI robot that can be as close to intelligent as these found in [*Ex Machina*](https://en.wikipedia.org/wiki/Ex_Machina_(film)) or *[I, Robot](https://en.wikipedia.org/wiki/I,_Robot_(film))* movies?
  
  I'm not talking about full awareness, but an artificial being that can make its own decisions and physical and intellectual tasks that a human being can do?
  
  **Tags:** research, agi
  
  
  ---
  
  ## 4 answers
  
  ### Answer by username_2 on 2016-08-06. Score: 23 | Accepted answer
  
  We are absolutely nowhere near, nor do we have any idea how to bridge the gap between what we can currently do and what is depicted in these films.
  
  The current trend for DL approaches (coupled with the emergence of data science as a mainstream discipline) has led to a lot of popular interest in AI.
  
  However, researchers and practitioners would do well to learn the lessons of the 'AI Winter' and not engage in hubris or read too much into current successes.
  
  For example:
  
  * Success in transfer learning is very limited.
  * The 'hard problem' (i.e. presenting the 'raw, unwashed environment' to the machine and having it come up with a solution from scratch) is not being
    addressed by DL to the extent that it is popularly portrayed: expert human knowledge is still required to help decide how the input should be framed, tune parameters, interpret output etc.
  
  Someone who has enthusiasm for AGI would hopefully agree that the 'hard problem' is actually the only one that matters. Some years ago, a famous cognitive scientist said "We have yet to successfully represent *even a single concept* on a computer".
  
  In my opinion, recent research trends have done little to change this.
  
  All of this perhaps sounds pessimistic - it's not intended to. None of us want another AI Winter, so we should challenge (and be honest about) the limits of our current techniques rather than mythologizing them.
  
  > **Comments:**
  > **username_6**: You said in the deleted comments that it was Douglas Hofstadter who said "We have yet to successfully represent even a single concept on a computer". Where can I find a reference that supports that?  
  
  ---
  
  ### Answer by username_1 on 2016-08-23. Score: 1
  
  Our current approaches to AI are too inefficient to result in anything remotely close to what an average human would perceive as artificial senient beings.
  
  Current approaches to AI involve a simulation of our own capacity for learning by creating fully functional computation machines capable of re-programming themselves. While that's definitely a good start with respect to understanding the nature of intelligence, it's still a far cry from actually creating genuine artificial intelligence.
  
  It is not just our capacity to learn that evolved. Our very brains themselves evolved from rudimentary biochemical components at the intra-cellular level to the fascinating, complex organs they are today, along with our bodies as a whole evolving from simple single cell life to homo sapiens. So to create genuine artificial intelligence, it may actually make most sense to first start with replicating that process : creating artificial life with the capacity to evolve. It may actually make most sense to first start with creating artificial DNA and artificial cells, and move on from there.
  
  Anyway, in [this article](http://www.alexstjohn.com/WP/2015/06/24/no-azimov-ai/) as well as [this article](http://www.alexstjohn.com/WP/2016/06/15/things-dont-compute/), Silicon Valley renegade [Alex St username_1](https://en.wikipedia.org/wiki/Alex_St._John) goes in greater detail on why something like [Skynet](https://en.wikipedia.org/wiki/Skynet_(Terminator)), [V.I.K.I.](http://irobot.wikia.com/wiki/VIKI) or anything like it is unlikely in the near future and may even never be within our grasp and why our current approach to artificial intelligence is a bad one.
  
  > **Comments:**
  > **username_2**: A simulation of a proof *is* a proof. Whether a simulation of intelligence *is* intelligence is an open question which (with our current knowledge of physics) appears impossible to answer in the negative based purely on theoretical arguments, but could empirically be answered positively via something such as the Turing Test.  
  > **username_1**: @username_2 : The article I referenced explains in greater detail why a simulation of intelligence isn't the same as actual intelligence.  
  > **username_2**: I read it. Many leading physicists (e.g. David Deutsch) believe that the universe is a quantum computer, which can be simulated by a classical computer.  
  > **username_1**: @username_2 : Yes, the universe does appear to be a giant quantum computer. I agree with you here. The problem with our current approaches to AI isn't so much that artificial brains are impossible, but that we're trying to create brains without first understanding how brains are created in living beings. Starting with creating artificial life that can evolve towards higher forms of existence may be a better approach to developing AI, as that is how we got here today... See also [this other article](http://www.alexstjohn.com/WP/2016/06/15/things-dont-compute/) by the same author.  
  > **username_2**: the argument about 'starting with simpler forms of life' is well-established in the AI community,  originating with work by Rodney Brooks in the 1990s that established the 'New AI' of 'embodied cognition'. See the papers 'Elephants don't play chess', 'Intelligence without Representation' and the book 'Pre-Cambrian Intelligence' for more details.  
  > **username_3**: ->The universe is a quantum computer (maybe) -> The universe has developed intelligence, in our understanding, by starting with simple life and guiding it towards something more complicated by Darwinian principles -> Starting with simple forms and guiding them is, as Nietz points out, well-established. -> Quantum evolutionary algorithms are already heralded for a speedup (e.g. https://arxiv.org/ftp/arxiv/papers/1303/1303.1243.pdf).   Leaves you wondering if the argument goes full circular doesn't it?  
  > **username_1**: @username_2 : Our current approaches to AI are too inefficient to ever result in anything remotely close to what an average human would perceive as artificial senient beings. St username_1's point was - and I tend to agree - that it makes more sense to first start with artificial DNA and artificial cells with evolutionary capacities and set move on from there.  
  > **username_1**: @Atkrye : I modified my initial answer to add more clarification on my position.  
  
  ---
  
  ### Answer by username_4 on 2016-08-23. Score: 1
  
  Based on the success of IBM Watson and the amazing advances in tackling numerous hard tasks using deep learning in the past 3 years, I think a large high-tech company like Google or Amazon will create a useful conversational bot in no more than 10 years. (I've worked on the fringes of AI for 25 years and have followed the tech for even longer. These are exciting times.)
  
  Initially, your very own AI companion ("Her"?) won't be capable of deeper philosophical conversation or insightful interpretation of novels or the human condition. But it will be able to write / speak in full paragraphs on topics like the best choice among 5 possible routes between point A and B, or summarizing the plot of a book or the gist of a news story, or why one product is better than another (e.g. based on assessing hundreds of Amazon reviews). And yes, it will be able to understand full spoken sentences from you, and generate both queries and answers.
  
  I'm convinced such a bot *will* be useful enough that most of us will want one. Of course you won't need to buy a special piece of hardware, like the Amazon Echo. It'll be available via software on your smartphone, though the computing is likely to reside on the cloud (since that's where the data is).
  
  Frankly, I think this is where the next innovations in smartphones will arise -- verbal interfaces that do a better job hearing and speaking and disambiguating using context about you and the kinds of questions you are likely to ask.
  
  
  ---
  
  ### Answer by username_5 on 2016-08-06. Score: 0
  
  > "heavier-than-air flying machines are impossible" *\_ Lord Kelvin 1895*
  
  7 years later the Wright brothers built one.
  
  ---
  
  Currently we have many powerful narrow AI (good at special tasks) but we have no idea how to unify them into a single system like in a biological brain.
  
  
  ---
  
  