Ever, never
|
|
Ever means 'at any time'. It is the opposite
of never.
We generally use ever in questions. |
Do you ever drink coffee?
Have you ever been to Paris? |
Never means 'at no time'.
|
He has never visited me.
I'll never forget how kind he has been. I never drink tea with milk. |
Never and ever go immediately
before the main verb.
Exceptions are the verb be and modal
verbs.
|
I never eat meat.
Do you ever go cycling?
I am never late.
I can never remember his name. You should never drink and drive. |
When speaking about our past, we use the present perfect
with ever and never.
|
I have never been to America.
Have you ever been to America? It was the best wine I have ever tasted. |
BBC
WILL WE EVER?| 16 May 2012
Will we ever... pass the Turing Test for computers?
As the latest set of contestants fail the infamous Turing
Test, John Pavlus explores what it will take to create a computer that can
think like a human.
Is it possible to create true artificial intelligence and,
if so, how close are we to doing so, asks mathematician Professor Marcus du
Sautoy.
How can you tell if a computer can think? In 1950, Alan
Turing – the father of computer science – suggested a simple test. Step one:
design a computer program that can simulate human conversation. (Which was no mean
feat, given how primitive the computers of the mid-twentieth century were.)
Step two: place it behind a screen or otherwise conceal it from view. Step
three: invite a human being to converse with the computer in the form of text
messages. Step four: Ask the person whether their unseen interlocutor is a
fellow human or a machine.
If he or she mistakes the computer-generated conversation
for a human, then voila: the computer, according to Turing, can be said
"to think".
It sounds more like a parlour game than a thought
experiment, and many in the field regard it as just that. Nevertheless, this
"Turing test" went on to drive decades of research on artificial
intelligence. It even spawned an annual contest since 1991 called the Loebner
Prize, where judges hold short conversations with concealed
artificial-intelligence programs and humans, and then have to decide which is
which. (In the absence of any program passing the test, a smaller prize is
given to the most “humanlike” one.)
Turing predicted that a computer would successfully fulfill
his thought experiment before the year 2000, but to this day, no computer
program has passed the test – not even yesterday’s winner of the 2012 Loebner
Prize, Chip Vivant. This is partly due to the mushy parameters of the test
itself – for instance, how long must the computer engage in freewheeling
conversation before the human passes judgment on its identity? Five minutes?
Three hours? Turing never says – but also because flawlessly imitating human
conversation turns out to be more complicated than anyone expected. So what
would it take to build a machine that can pass Turing's infamous test?
Mind your language
One thing is for sure: brute-force logic will not do the
trick. In the early days of artificial intelligence research,
"thinking" was assumed to be simple matter of connecting symbols
together using discrete rules. "There was this idea in the 1960s of
cutting the world up into objects and actions that you can name: book, table,
talking, running," says Robert French, a cognitive scientist at The French
National Centre for Scientific Research. "All the words in the dictionary
are symbols that refer to the world. So if you put them all together in a
careful manner, intelligence should emerge, roughly."
Except it doesn't. This approach, called "symbolic
AI," snaps like a twig when subjected to the slightest bit of ambiguity.
After all, no dictionary rule can tell a computer how to appropriately respond
to the casual question, "What's up?" (If you answer "Up is the
opposite of down," you have just failed the Turing test.) A densely
interconnected database may contain "intelligent" information, but it
is not intelligent itself. As Brian Christian, author of The Most Human Human:
What Artificial Intelligence Tells Us About Being Alive, puts it: "When we
read a book, we don't think the book has the ideas."
A much better way to simulate human conversation is to
sidestep logic and aim for a quality called "statelessness". In a
stateless conversation, each response only has to vaguely reference the one
that came immediately before it. This behaviour is much easier to program into
a computer, which is why so-called “chatbots” have become so prevalent online.
In the mid-1960s, ELIZA, one of the world's first chatbots,
effectively impersonated a psychotherapist by parroting users' language back at
them. In the 2000s, a more sophisticated chatbot called ALICE won the Loebner
Prize three times by using essentially the same technique. Still, these
stateless interactions are hardly what anyone would call
"intelligent" – ironically, it is their almost total vacuousness that
makes them seem so human. But not human enough, it seems: ALICE may have
outperformed other chatbots, but it still could not fool human judges
consistently enough to pass the Turing test.
So if knowing plenty of facts and making hollow small talk
are not skills that allow a computer to pass the Turing test, what aspect of
"human-like intelligence" is being left out? The one thing we have
that computer programs do not: bodies.
Total recall
According to French, intelligence actually floats on a
"huge sea of stuff underneath cognition" – and most of it consists of
associative sensory experiences, the "what it's like"-nesses built up
by a physical body interacting with a physical world. This
"subcognitive" information could include the memory of falling off a
bike and skinning your knee, or biting into a sandwich at the beach and feeling
sand crunch between your teeth. But it also includes more abstract notions,
like the answer to the following question: "Is 'Flugly' a better name for
a glamorous actress or a teddy bear?"
Even though "flugly" is a nonsense word, almost
any English-speaking human would pick the teddy bear, says French. Why? "A
computer doesn't have a history of embodied experience encountering soft teddy
bears, pretty actresses, or even the sounds of the English language,"
French says. "All these things allow human beings to answer these
questions in a consistent way, which a computer has no access to." Which
means any disembodied program has an Achilles heel when it comes to passing the
Turing test.
But that may soon change. French cites
"life-capturing" experiments, like MIT researcher Deb Roy's ongoing
efforts to record every waking second of his infant son's life, as a possible
way around the embodiment problem. "What would happen if a computer were
exposed to all of same the sights and sounds and sensory experiences that a
person was, for years and years?" French says. "We can now collect
this data. If the computer can analyse it and correlate it correctly, is it
unreasonable to imagine that it could answer 'Flugly'-type questions just like
a human would?"
French does not think on-the-fly analysis of such a massive
dataset will be possible anytime soon. "But at some point in time, we're
going to get there," he says. At which point – assuming it works, and a
computer program passes the Turing test – what will this mean in practical
terms? Will we deem the device intelligent? Or will we simply add “have a convincing
conversation” to the ever-growing list of interesting things that computers can
do, like “beat humans at chess” (as IBM’s Deep Blue did in a match with Garry
Kasparov in 1997) or “play Jeopardy! on television” (as Watson did in 2011)?
The renowned computer scientist Edsger Dijkstra said that
"the question of whether machines can think is about as relevant as the
question of whether submarines can swim." Semantics and philosophy of
"intelligence" aside, a computer that can pass the Turing test can do
exactly one thing very well: talk to people like an individual. Which means
that the Turing test may simply be replaced by a different question, one that
is no less difficult to answer. "We can imitate a person," says Brian
Christian. "But which one?"
Advantages and Disadvantages of Future Technologies
Choose one of the inventions below and take opposite sides
about whether it would be a
good or bad thing for life/ society, taking turns to speak
until someone can’t think of any
new points. The last person to speak wins.
OR
Choose one of the inventions below that you think has only
advantages or only
disadvantages. Your partner gets one point for each thing
that you will accept is actually
an opposing point, e.g. each thing that is actually an
advantage if you thought there were
only disadvantages. If they can’t think of anything at all,
you get three points.
OR
Work together to brainstorm as many advantages and
disadvantages as you can for one
thing, then come to a conclusion.
Inventions to speak about
100% effective missile defence shields
100% effective toothpaste/ Fully plaque-resistant
artificial teeth
99% of personal data in the cloud
A beam which can immobilise people and objects
A cure for the common cold
A technological fix for the hole in the ozone layer
All devices linked to the internet
All telephone and video communication via the internet
Androids which look exactly like people
Being able to freeze your body and defrost when a cure for
your disease is invented
Being able to program your dreams
Being able to read minds
Bionic eyes with a zoom function and ability to record
what you see
Breeding of extinct animals, including pre-historic ones
such as mammoths and dinosaurs
Bridges or tunnels between all continents and between
continents and all islands
Bullet-proof clothes
Car-free cities or countries
CGI character indistinguishable from real actors
CGI-generated dead actors and famous people appearing in
completely life-like films
Colonisation of other planets
Communication with life on other planets
Complete genetic manipulation of foods
Computer chips in your brain
Computer-generated music top of the charts
Deafness fully curable
Driverless cars
Drugs which cure most criminals of their desire to commit
crimes
Electricity generation from normal human motion, e.g. from
your watch to your smartphone or from the pavement to the street lights
Enhanced hearing
Enhanced intelligence
Eradication of mosquitoes from entire cities
Eternal life
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