#dontstop

#thatsnotwhatyouasked

Pet peeve – use of “literally.”

If you don’t understand literally vice figuratively, #artificialintelligence can set you straight. Rule#2 of #AI is everything is literal. AI does exactly as you tell it.  That can be annoying from a child or spouse or customer service chatbot. AI doesn’t have the contextual preferences of humans – which emotes angst and joy in the uncovering. Given a problem, AI is going to take the tasking literally. For example:

I hooked a neural network up to my Roomba. I wanted it to learn to navigate without bumping into things, so I set up a reward scheme to encourage speed and discourage hitting the bumper sensors. It learnt to drive backwards, because there are no bumpers on the back. – @smingleigh

This is an interesting concept because the “bugs” that you deal with your computer, your phone, your network, your business are likely a synergy of literal translation. Code knows 0 or 1, and coders get that.  The rest of us are swimming in “why the hell is this broken” when the answer is a literal question return.

#saywhatyoumean #meanwhatyousay

AI Bots on Billie Eilish

#Imabiscuit #billieeilish

In my last post, i talked about how #artificialintelligence is NOT the super borg/being that could take over the world. So why not?  #AI is #machinelearning and we are the teachers. 

One of the earliest and prolific examples is Google translate.  Instead of using rules based learning: vocabulary + grammar = new language, AI consumes the Internet’s volumes of translations online, eating everything, idioms and nuances.  The human level equivalent for a single language would be blind, total immersion. Go to a country knowing nothing of the language and simply listen, read and repeat, making mistakes along the way. 

Humans have to train the data too, teaching it right from wrong.  #AIbots don’t know – and don’t care – what the output is – as your text auto completion can attest. What comes out as a result is sometimes odd and sometimes beautiful – kinda like its human creators.

If you’re thinking wow, how cool, and wouldn’t something that can learn language better than we can take over the world? Not so much. The #trialanderror is as large as the training data set (100 billion translations as of 2016).  The results of a single translation are a lottery ticket sample size. #youtube abounds with examples of how #googletranslate doesn’t quite figure it out.

Check out “I’m a biscuit.” Better known as #badguy

The Skinny on Artificial Intelligence

#C3PO

#R2D2

#skynet 

#Hal

#Wall-E

The pop fiction visions of #artificialintelligence bifurcate to optimism or pessimism. #AI is either going to take over the world or it’s going to become a better best friend than real people. These fictitious characters are examples of artificial general intelligence (#AGI) .  Although it makes for great movie substance, the reality of AGI is further away than Mars travel and likewise some argue, impossible. 

What generates numerous effects in your daily life now is Artificial Narrow Intelligence (#ANI).  ANI finishes your sentences in Gmail or texts. ANI filters your spam and selects music for you. #Siri ANI answers your questions.

ANI – the AI we have today – can do specialized tasks far better than we can, but that’s all it can do.  As Janelle Shane puts it though, “machines have been superior to humans at specific tasks for a while now. A calculator has always exceeded humans’ ability to perform long division – but it still can’t walk down a flight of stairs.” – You Look Like a Thing and I Love You.

So oddly, the ability to walk and chew gum still pays off 😉