Tag Archives: computer

When will you be replaced by a computer?

I have written before about extending our minds by using external computing power in our mobile phones [see ‘Science fiction becomes virtual reality‘ on October 12th, 2016; and ‘Thinking out of the skull‘ on March 18th, 2015]; but, how about replacing our brain with a computer?  That’s the potential of artificial intelligence (AI); not literally replacing our brain, but at least taking over jobs that are traditionally believed to require our brain-power.  For instance, in a recent test, an AI lawyer found 95% of the loopholes in a non-disclosure agreement in 22 seconds while a group of human lawyers found only 88% in 90 minutes, according to Philip Delves Broughton in the FT last weekend.

If this sounds scary, then consider for a moment the computing power involved.  Lots of researchers are interested in simulating the brain and it has been estimated that the computing power required is around hundred peta FLOPS (FLoating point Operations Per Second), which conveniently, is equivalent to the world’s most powerful computers.  At the time of writing the world’s most powerful computer was ‘Summit‘ at the US Oak Ridge National Laboratory, which is capable of 200 petaFLOPS.  However, simulating the brain is not the same as reproducing its intelligence; and petaFLOPS are not a good measure of intelligence because while ‘Summit’ can multiply many strings of numbers together per second, it would take you and me many minutes to multiply two strings of numbers together giving us a rating of one hundredth of a FLOP or less.

So, raw computing power does not appear to equate to intelligence, instead intelligence seems to be related to our ability to network our neurons together in massive assemblies that flicker across our brain interacting with other assemblies [see ‘Digital hive mind‘ on November 30th, 2016]. We have about 100 billion neurons compared with the ‘Summit’ computer’s 9,216 CPUs (Central Processing Unit) and 27,648 GPUs (Graphic Processing Units); so, it seems unlikely that it will be able to come close to our ability to be creative or to handle unpredictable situations even accounting for the multiple cores in the CPUs.  In addition, it requires a power input of 13MW or a couple of very large wind turbines, compared to 80W for the base metabolic rate of a human of which the brain accounts for about 20%; so, its operating costs render it an uneconomic substitute for the human brain in activities that require intelligence.  Hence, while computers and robots are taking over many types of jobs, it seems likely that a core group of jobs involving creativity, unpredictability and emotional intelligence will remain for humans for the foreseeable future.

Sources:

Max Tegmark, Life 3.0 – being human in the age of artificial intelligence, Penguin Books, 2018.

Philip Delves Broughton, Doom looms over the valley, FT Weekend, 16 November/17 November 2019.

Engelfriet, Arnoud, Creating an Artificial Intelligence for NDA Evaluation (September 22, 2017). Available at SSRN: https://ssrn.com/abstract=3039353 or http://dx.doi.org/10.2139/ssrn.3039353

See also NDA Lynn at https://www.ndalynn.com/

Digital limits analogue future

Feet on Holiday I 1979 Henry Moore OM, CH 1898-1986 Presented by the Henry Moore Foundation 1982 http://www.tate.org.uk/art/work/P02699

Feet on Holiday I 1979 Henry Moore OM, CH 1898-1986 Presented by the Henry Moore Foundation 1982 http://www.tate.org.uk/art/work/P02699

Digital everything is trendy at the moment.  I am as guilty as everyone else: my research group is using digital cameras to monitor the displacement and deformation of structural components using a technique called digital image correlation (see my post on 256 Shades of grey on January 22nd, 2014) .  Some years ago, in a similar vein, I pioneered a technique known as ‘digital photoelasticity’ (se my post on ‘Cow bladders lead to strain measurement‘ on January 7th, 2015..  But, what do we mean by ‘digital’?  Originally it meant related to, resembling or operated by a digit or finger.  However, electronic engineers will refer us to A-to-D and D-to-A converters that transform analogue signals into digital signals and vice versa.  In this sense, digital means ‘expressed in discrete numerical form’ as opposed to analogue which means something that can vary continuously .  Digital signals are ubiquitous because computers can handle digital information easily.  Computers could be described as very, very large series of switches that can be either on or off, which allows numbers to be represented in binary.  The world’s second largest computer, Tianhe-2, which I visited in Guangzhou a couple of years ago, has about 12.4 petabytes (about 1016 bytes) of memory which compares to 100 billion (1012) neurons an average human brain.  There’s lots of tasks at which the world’s largest computers are excellent but none of them can drive a car, ride a bicycle, tutor a group of engineering students and write a blog post on the limits of digital technology all in a few hours.  Ok, we could connect specialized computers together wirelessly under the command of one supercomputer but that’s incomparable to the 1.4 kilograms of brain cells in an engineering professor’s skull doing all of this without being reprogrammed or requiring significant cooling.

So, what’s our brain got that the world latest computer hasn’t?  Well, it appears to be analogue and not digital.  Our consciousness appears to arise from assemblies of millions of neurons firing in synchrony and because each neuron can fire at an infinite number of levels, then our conscious thoughts can take on a multiplicity of forms that a digital computer can never hope to emulate because its finite number of switches have only two positions each: on and off.

I suspect that the future is not digital but analogue; we just don’t know how to get there, yet.  We need to stop counting with our digits and start thinking with our brains.

Smart machines

violinMy enthusiasm for the concert we went to some weeks ago is only just beginning to fade [see Rhapsody in Blue posted on 5th February, 2014].  I have one of Michel Camilo’s pieces still going around in head [listen here].  On the subject of playing the piano, people are trying to build robots that can play the piano using rubbery fingers although they have had more success with a robot that can play a violin [see this Youtube clip].

These robots might be clunky or primitive compared to a maestro like Michel Camilo, but nevertheless smart machines are coming.  Professor Noriko Arai is developing a computer, called Todai-Kun, that could ace college entrance exams.  She hopes that by 2021 Todai-Kun will pass the entrance exam for Tokyo University, which is the top university in Japan.  It is tough for graduates to find jobs at the moment, so imagine what it will be like if computers are as smart as graduates!

Mechanisation destroyed jobs on the farm, robots have replaced assembly-line workers and now smart computers are going to replace white collar workers.  In the future, if you want a well-paid job you are likely to need niche skills that involve a combination of creativity, innovation, problem-solving and leadership.  I am probably biased but that sounds like a professional engineer.

In the same context, David Brooks has suggested that, what he calls the ’emotive traits’ will be required for success, i.e. a voracious lust of understanding, an enthusiasm for work, the ability to grasp the gist and an empathetic sensitivity for what will attract attention, which with the exception of the last one also sound like the attributes of a professional engineer.

I have used the violin playing robot as the focus for a 5E lesson plan on the Kinematics of Rigid bodies in 3-dimensions see: 5EplanNoD10_Kinematics_of_rigid_bodies_in_3D .  Not quite an ‘Everyday Example’ but one with which many students can connect.

Sources:

http://www.nytimes.com/2013/12/30/world/asia/computers-jump-to-the-head-of-the-class.html?_r=0

http://www.nytimes.com/2014/02/04/opinion/brooks-what-machines-cant-do.html?_r=0