Pm, according to this 23andMe ancestry composition. I'm 57% African, 19%
Ashkenazi, 18% Persian and 5% Native American. In other words, I'm kool,
smart and sexy. Just think of a younger, smarter version of Barack Obama :)

I don't think AGI is impossible. Ben G has some good Ideas. So do a lot of
people. But they are missing pieces here and there.



On Fri, Apr 4, 2014 at 7:44 AM, Piaget Modeler <[email protected]>wrote:

>  @  [the big]  Azzzz,
>
> You're not Black.
>
> #1-  Black people use capital B's to describe themselves;
> #2 - they prefer to use the words "African" or "African-American" to
> Black;
> #3 - they don't define themselves by their ability to use  expletives;
>  and finally
> #4 - they know that spelling cool with a k isn't.
>
> So I'd appreciate you being yourself, and being real.
>
> You're reminding me a lot of Mike Tintner--only he said AGI couldn't be
> done because
> it is impossible, no one will ever know how.  Now you're saying AGI can't
> be done
> because other people currently don't know how, but you do.
>
> Omoshiroi...
>
> ~PM
>
>
>
> ------------------------------
> Date: Fri, 4 Apr 2014 01:10:46 -0700
> Subject: Re: [AGI] Jeff Hawkins says 2014 is the year !
> From: [email protected]
> To: [email protected]
>
>
> "I'm not sure I'd drop so many f-bombs"
>
> That's because you're not black or kool like me ;).
>
>
> On Thu, Apr 3, 2014 at 3:51 PM, Sergio Donal <[email protected]> wrote:
>
> I also read it several years ago and do not remember pretty much either,
> but the thought that comes to my mind is that he was speaking that we are
> basically predicting the environment, either spatially, temporally or any
> other feature. So prediction is a form of "completion the scene" and there
> is where creativity comes up, we predict the current scene based in our
> past observations (and completions) but since the scene may be new, we are
> applying past experience to solve new problems. Or something like that...
>
> Now I realize, doesn't this sound kind of Bayesian?
>
>
>
>
> On Thu, Apr 3, 2014 at 11:28 PM, Mike Archbold <[email protected]>wrote:
>
> I'm not sure I'd drop so many f-bombs, but I had the feeling he's got
> a good compression/pattern match overall command scheme, and not
> math-heavy to boot, but not sure if he's got the ability to solve
> general problems.  In other words, what is the processing structure
> for solving problems?  I've read On Intelligence, 10 years ago, but
> have at present only a superficial understanding of his approach.
>
> On 4/3/14, Azn A <[email protected]> wrote:
> > He doesn't have is a fully temporal semantic database structure with a
> > generative normalization pattern matcher/vectorized scale free
> calculation
> > minimizer... I.e. the G in AGI. In other words, he's missing the minimal
> > concept basis for processing that has an optimal scalability while
> > minimizing complexity, without that it's a crap shoot if someone will
> ever
> > succeed in making a better than human level AGI that isn't just brute
> > forcing human intelligence by putting too much human knowledge in a
> system
> > and claiming it is better than human level intelligence while it is
> > actually less than human level due to a complete lack of creativity.
> >
> > Even worse, the deepest problem that nobody ever thinks about is the
> > knowledge representation system... they all have static/fragile designs,
> > Hawkins' products are really bad even in the sorta neural-net form he has
> > is fucking self-crippling in the number of associations that can be built
> > up. I've never seen a fucking neural-network capable of self-reflection
> and
> > differentiation, among many other conceptual paradoxical forms humans
> have
> > no problems thinking about..
> >
> >
> >
> >
> > On Thu, Apr 3, 2014 at 1:44 PM, Mike Archbold <[email protected]>
> wrote:
> >
> >> Long article, but interesting.  It sounds like he's built the input
> >> but not the output, the motor control.  I don't think there is any
> >> convincing argument about what paradigms to use for strong AI / AGI
> >> since there isn't a working such thing yet.  Some math-first
> >> approaches seem like they want to lose you with the formula, otherwise
> >> I like math....
> >>
> >> On 4/3/14, John Rose <[email protected]> wrote:
> >> > You don't have enough math here.
> >> >
> >> >
> >> >
> >> > People are now looking more at the mathematical formalisms of software
> >> > systems. There are so many and of such variety.
> >> >
> >> >
> >> >
> >> > Hawkins has one approach not the only approach.
> >> >
> >> >
> >> >
> >> > He's hardcoding the components mimicked from biological intelligence.
> >> > Are
> >> > there more efficient and easier to build components and are there
> >> > components
> >> > that morph? His don't morph. It looks to me like hardcoded AI BUT I
> >> haven't
> >> > studied the system.
> >> >
> >> >
> >> >
> >> > John
> >> >
> >> >
> >> >
> >> >
> >> >
> >> > From: Azn A [mailto:[email protected]]
> >> >
> >> >
> >> >
> >> > http://www.theregister.co.uk/2014/03/29/hawkins_ai_feature
> >> >
> >> >
> >> >
> >> > "These are complex biological systems that were not designed by
> >> > mathematical
> >> > principles [that are] very difficult to formalize completely," he told
> >> us.
> >> >
> >> >
> >> >
> >> > "This reminds me a bit of the beginning of the computer era," he said.
> >> "If
> >> > you go back to the 1930s and early 1940s, when people first started
> >> > thinking
> >> > about computers they were really interested in whether an algorithm
> >> > would
> >> > complete, and they were looking for mathematical completeness, a
> >> > mathematical proof. If you today build a computer, no one sits around
> >> > saying
> >> > 'let's look at the mathematical formalism of this computer.' It
> reminds
> >> me
> >> > a
> >> > little about that. We still have people saying 'You don't have enough
> >> math
> >> > here!'
> >> >
> >> >
> >> >
> >> >
> >> >
> >> >
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