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Apologies if this has been linked Before: http://uk.businessinsider.com/urs-holze-talks-google-cloud-beat-search-2015-11?r=US&IR=T

 

"Urs Hölzle, Google's eighth employee and overall cloud boss, thinks that within the next five years, the company's Google Cloud Platform revenues could surpass Google's advertising revenue."

 

Any realism to this? I guess margins are much lower for Cloud than Ads. But if his belief becomes true it would still be a major source of value.

 

Google Cloud Platform Global User Conference live currently:

https://cloudplatformonline.com/NEXT2016.html

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Hi Gio it seems like you shifted your content creation.  From passionately defending your positionalities to giving value via press releases. Interesting shift. Good move from a historical perspective.

 

Well… I have discovered Twitter! Ahah!! ;)

Imo Twitter is a good way to share ideas through very brief messages, while attaching a link to an article or a picture to delve more deeply into the matter at hand.

I think it is a better use of time than writing very long posts.

 

Cheers,

 

Gio

 

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I think Google definitely has the lead over Microsoft in Artificial Intelligence. While Google is training its AIs to play Go at the world championship level, Microsoft managed to train its latest AI to love Hitler and hate Jews.  My guess is that Twitter won't be a widely used training method for AI in the future.

 

Microsoft's 'teen girl' AI turns into a Hitler-loving sex robot within 24 hours

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So Alphabet is pushing the non-Google subs for products/revenues/results. Possibly influence of the new CFO.

 

Possibly good for shareholders.

 

Possibly bad for moonshot people and people who admired Google for getting involved in the moonshots.

 

I'm conflicted about this per above.

As a human being I'd rather see Google prevent death than increase Youtube ads 50%.

As a shareholder... well screw Youtube ads! I want fricking driverless cars, walking robots and no death!  8)

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While Google is training its AIs to play Go at the world championship level, Microsoft managed to train its latest AI to love Hitler and hate Jews.

 

Google is using 1980/90's AI tech which Hinton himself admitted. I remember when I went to Grad School in 2004, I would talk to people about Neural networks and they thought at that time it was old-fashioned. One guy was telling me then that graphical models like Neural Networks, Bayesian Networks and other ideas were deeply related. I think he was talking about this paper:

http://www.psi.toronto.edu/~psi/pubs2/2001/frey2001factor.pdf

 

Anyways its pretty funny to me that people think Google is ahead. No one is ahead. People have just realized that computational power has made a lot of old algorithms feasible.

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While Google is training its AIs to play Go at the world championship level, Microsoft managed to train its latest AI to love Hitler and hate Jews.

 

Google is using 1980/90's AI tech which Hinton himself admitted. I remember when I went to Grad School in 2004, I would talk to people about Neural networks and they thought at that time it was old-fashioned. One guy was telling me then that graphical models like Neural Networks, Bayesian Networks and other ideas were deeply related. I think he was talking about this paper:

http://www.psi.toronto.edu/~psi/pubs2/2001/frey2001factor.pdf

 

Anyways its pretty funny to me that people think Google is ahead. No one is ahead. People have just realized that computational power has made a lot of old algorithms feasible.

 

It's not because an idea or a technique was first invented a long time ago that it hasn't evolved since.

 

Radio waves were discovered a while ago, but gigabit wifi isn't the same as morse code.

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While Google is training its AIs to play Go at the world championship level, Microsoft managed to train its latest AI to love Hitler and hate Jews.

 

Google is using 1980/90's AI tech which Hinton himself admitted. I remember when I went to Grad School in 2004, I would talk to people about Neural networks and they thought at that time it was old-fashioned. One guy was telling me then that graphical models like Neural Networks, Bayesian Networks and other ideas were deeply related. I think he was talking about this paper:

http://www.psi.toronto.edu/~psi/pubs2/2001/frey2001factor.pdf

 

Anyways its pretty funny to me that people think Google is ahead. No one is ahead. People have just realized that computational power has made a lot of old algorithms feasible.

 

Oh yes that is correct.  No one could be ahead in computing either since Alonzo Church wrote a paper on lambda calculus way back in the 1930s.  Its all just a bunch of nonsense and rehashing of old ideas.

 

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Anyway, there have been significant changes in how they do neural networks based on the capabitility of current machines.  In old style neural networks it was basic understood guidance that you should use as few synapses as possible, with maybe 1 hidden layer.  This is *dramatically* different under the newer treatment of deep neural networks.

 

The basics of how you think of it, yeah, that isn’t really different…but the brain has been around a long time too.

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