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Posts Tagged ‘AI’

Do You Love Me?

The video below is owned by “Boston Dynamics” and is located on their YouTube channel (https://www.youtube.com/user/BostonDynamics).  I make no claim to the video (which is great) or the song (which is also great)!  I am sharing this because watching it made me happy (and I love the song)…
I found the above video of robots dancing amazing.  It was only when I read some of the comments I realized how “programmed” we (humans) have become to fear the future.  Maybe “Blade Runner” and “Terminator” are not that far away.  For now, I’m amazed and can’t wait until a robot can improvise when dancing.  The robots in the video appear (to me) to be programmed for this song and seem synchronized (timing and distance) with each other.
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On This Day In:
2020 Still Willing
2019 Another Prayer
2018 After Silence
2017 Are You Looking Forward To A Trump Presidency?
2016 Three Errors From Eureka
2015 Limiting Choices
2014 Praise The Lord And Pass The Hypocrisy
That Sound
2013 Still Waiting For Answers
2012 Informal Leadership
2011 A Little More Progress
2010 Bec’s Gone Again…

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On the phone, I ask Li if she imagines there could have been a way to develop AI differently, without, perhaps, the problems we’ve seen so far.  “I think it’s hard to imagine,” she says.  “Scientific advances and innovation come really through generations of tedious work, trial and error.  It took a while for us to recognize such bias.  I only woke up six years ago and realized ‘Oh my God, we’re entering a crisis.’ ”
On Capitol Hill, Li said, “As a scientist, I’m humbled by how nascent the science of AI is.  It is the science of only 60 years.  Compared to classic sciences that are making human life better every day — physics, chemistry, biology — there’s a long, long way to go for AI to realize its potential to help people.”  She added, “With proper guidance AI will make life better.  But without it, the technology stands to widen the wealth divide even further, make tech even more exclusive, and reinforce biases we’ve spent generations trying to overcome.”  This is the time, Li would have us believe, between an invention and its impact.
  —  Fei-Fei Li  (being quoted)
Quoted by: Jessi Hempel
From her article:  “The Human In The Machine
Appearing in: Wired Magazine, December 2018
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On This Day In:
2018 MAGA?
2017 Neutral
Family Over Ego
2016 Hard Learners
2015 Goals
2014 Switch To Dogs…
2013 Times Change
2012 Ashes Not Dust
2011 A Handful From Saudi
None Of This Happened
Take Responsibility

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Sometimes it is the people no one imagines anything of who do the things that no one can imagine.
  —  Alan Turing
Codebreaker” (2011)  —  movie review
Codebreaker is a “docu-drama” about the life of Alan Turing, the famous mathematician who lead the team which developed the computer which broke the “Enigma” German code machine back in World War II.  Turing is played by Ed Stoppard.  The “drama” portion of this film is mostly from the journals of Dr. Franz Greenbaum, who was the psychiatrist Turing was forced to see for counseling. Dr. Greenbaum is played by Henry Goodman.
This film was made for TV and was aired in 2011 in the UK under the title: “Britian’s Greatest Codebreaker“.  The title was changed and the film had a limited theatrical release in the US in 2012, so you may find it noted with either year of release.
The documentary portion of the film is interspersed into the drama and features a series of interviews with relatives of both Turing and Greenbaum, a few of Turing’s colleagues / contemporaries and some otherwise famous folks from mathematics and the computer industry.
Of course the “psych” interviews delve into Turing’s childhood, schooling and his homosexuality.  The documentary interviews try to give a lay-person’s explanation of some of Turing’s main computer breakthroughs.  For those who don’t know, Turing is considered one of the creators of both digital computers / computing, and of artificial intelligence (AI).
Turing is reputed to have died from suicide by poisoning.  This film does nothing to explicitly contradict that conclusion, but it offers slim insights into the conspiracy theory that Turing might have been killed off by the British government in the interest of state secrecy.  In any case, some 50 years after the fact, Turing was given a full pardon for his “crime” (indecent acts) as well as a formal apology from the British government.
Final recommendation: Strong to highly recommended.  Although no where near the “movie” which followed in 2014 (see below) for production value or drama, this made for television movie was just as interesting and probably more informative.  If you are interested in computers, AI or the history surrounding WWII, I think you’ll enjoy this film.
The Imitation Game”  (2014)  —  movie review
This is my third or fourth time viewing this movie and my initial review can be found here.
This movie is based on the book / biography: “Alan Turing: The Enigma” written by Andrew Hodges.  The movie is a dramatized version of “basically” historical events with liberties taken for “drama”.  Benedict Cumberbatch stars as Alan Turing, (Alex Lawther plays a young Alan Turing), Keira Knightley plays Joan Clarke (the female / “love” interest), Allen Leech plays John Cairncross (a Russian agent / collegue of Turing on the project), Rory Kinnear plays Detective Robert Nock, Mark Strong plays Stewart Menzies (the MI6 super-spy), Matthew Goode plays Hugh Alexander (one of the brilliant collegues), Charles Dance plays Commander Denniston (Turing’s commanding officer at Bletchley Park ).  The basic premise is that a brilliant Turing invents a general purpose computer to defeat the Nazi coding machine “Enigma”, thus saving lives by helping to end the war faster.  Their work is performed at Bletchley Park.  Turing (and the team) are successful, but because it is all TopSecret, there is no record of his achievements until much later (several decades) and Turing has committed suicide in the meantime.
The movie (and presumably the book) is based on fact. Turing was a real person; he was brilliant, he did come up with this codebreaking machine.  Also, he was homosexual; he was subject to hormonal “treatment” to “cure” his desires; he did die in 1954.  Beyond that, there are a number of points which are probably better handled in the “Codebreaker” TV movie reviewed above.  To begin with, I don’t believe he was autistic (as is implied in this movie).  I gather he had a mild stutter, but nothing like what is implied in the movie.  He was homosexual, but he was not as closeted as the movie implies.  My understanding is while he was open about it with his friends and colleagues, he was not what would be described as “flaming”.  He was “in love” with Joan Clarke and did propose to her and later break off the engagement.  By “in love” I mean he cared for her deeply, although it appears the relationship was more than Platonic but less than physical.  At any rate, as portrayed in the film, Turing does tell her he is gay and she did appear to not care (in real life) about his sexual preferences.
There are also a number of other factual inconsistencies: the character Hugh Alexander did handle most of the supervisory / administrative duties for the team.  He was not “really” Turing’s supervisor and Turing was uninterested in those duties and most office (and real) politics.  The character John Cairncross may or may not have been a Russian agent.  In either case, he and Turing did not work together and I’ve read it’s unlikely they even met or knew each other.  Finally, Turing was not add odds with Commander Denniston, but it seems there was some issue with funding, a letter was sent to Churchill by the team and Turing’s name was on the letter, but it was from the whole of the team, not just from Turing.
Okay.  So after all that, was the movie any good and did I enjoy it?  Yes and very much so.  I admit I am a fan of both Cumberbatch and Knightley. I also quite like Mark Strong as I see him in more things (the “Kingsman” series is top of this list).  Because I spent a career in computing, I already knew of Turing and some of his accomplishments, so it was nice to see it dramatized and put up on a big screen film.  Final recommendation: (still) highly recommended.  I am a fan of the two leads, the specific (codebreaking / history) and general (computing / WWII) topics are also of personal interest, so I had a natural predisposition to enjoy this film.  But, beyond my personal interests (biases), I do think this was a good film / drama and worth the time of anyone who happens to view it.
For those wondering about the movie’s title…  Turing wrote a paper about computing and artificial intelligence which proposed that if a person sat in front of typing instrument (what we today would call a terminal or workstation) and could type in a series of sentences and questions to “someone” at another workstation using normal language and could not tell the responses came from a machine, then the machine, was in fact, intelligent.  This is the simplified version.  The more complete version had three participants: the human testing / judging, a human responding, and a computer responding.  In this case, the judge had to decide which responder was human and which was the machine.  In some variations, the judge isn’t advised one responder is a machine until after completing several question / response cycles.  Basically, the test was evolving to add a blind control situation: the judge didn’t know there was a test or what was being tested until after the cycles.  I found it interesting that the producers of the movie would try to educate the audience about this aspect of computing and AI even though it had little to do with the premise of the movie, that is, a long-suffering individual genius breaking the German code machine.
As an aside (and final note), the movie shows Turing out running cross-country several times.  What isn’t specified is that he was a world class distance runner who nearly qualified for the British Olympic team in the marathon.  Again, nothing earth shaking, but I found the detail interesting.
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On This Day In:
2018 Until Integrity, Decency, Wisdom, And Humility Return
Just Tell (And Re-tell) The Big Lie Often Enough On Fox News
2017 To Laws, Not Office Or Individuals
Beast / General / Civil
2016 Patronage
2015 For Blogs, Too!
2014 Righteous Anger
2013 An Irish Blessing
2012 But Is It Worth It?
2011 Let Us Start

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Capitalism, however, has been here before.  One of its great historic strengths has been its ability to reform and change shape as social needs and democratic demands shift.  In the late 19th century, parties of the right in Europe brought in a wave of progressive reforms to suit the times, from expanded union rights to the social insurance that began the creation of the modern welfare state.  In these cases, there was a pragmatic and also a moral imperative at work to improve the lives of ordinary citizens.
Yet today, politicians and thinkers have largely stopped making the case for capitalism as a moral good.  What we have instead are abstract ideas about the supremacy of markets.  At the same time, the surges in inequality seen in country after country are corroding the moral principles that underpin capitalism.  The ethical basis for capitalism must be that it offers better life chances for a majority of citizens.  If it is failing to do that, what is the justification for its dominance as an economic system?  Little wonder that a Gallup poll found only 45% of U.S. young adults view capitalism positively, a 12-point decline in just two years.
Artificial intelligence has the potential to alter our lives to an even greater extent.  AI is best understood not as an upgrade of our existing structures but as a general-purpose technology (GPT), like electricity or the steam engine.  GPTs are transformative in their social and economic impacts, reaching into every aspect of life.  “Some people believe that it’s going to be on the scale of the Industrial Revolution,” says Demis Hassabis, the AI expert who co-founded the pioneering machine-learning company DeepMind.  “Other people believe it’s going to be the class of its own above that.”
The crucial factor for managing these changes is time.  In 1900, the proportion of the U.S. population who worked in agriculture was 38% and the proportion who worked in factories was 25%.  Today only 1.5% of the population works in agriculture and 7.9% in factories.  So there’s been a catastrophe of unemployment?  Absolutely not: the losses were more than made up for by growth in other sectors of the economy, which went from providing 24 million jobs in 1900 to some 150 million today.  Most of the new varieties of work simply didn’t exist at the dawn of the last century.  Given time, we know from experience that a society can manage this kind of transition.  The question is, do we have that time?
…Think about what the working life will be of a person who can expect to live for a full century.  What can we say about the likely span of her economic and political life?  The only absolute certainty is that it will involve change.  It will not be static.  It will not involve doing the same thing in the same place over and over again.  Unless we are all prepared for change, we are not prepared for the coming world of work.
At the individual level, the prescription for what we should do to prepare for this new landscape is relatively straightforward.  For a life of multiple careers and skills, people need an education that prepares them for a lifelong process of training and retraining.  They will need, more than anything else, to learn how to learn.  Flexibility and resilience will be crucial.  It won’t be easy, but at least we can see it clearly.  At the level of society it is harder.  Let’s be honest: this is a vision of insecurity, projected across a working life.  It is a clear principle of economic and political history—one we’re relearning today — that humans hate insecurity.
What we need is to rethink the relationship between the individual, the corporate sector and the state.  In recent decades, we have seen a “great risk shift” — to borrow the term of the Yale social scientist Jacob Hacker.  Individuals in temporary, insecure, giglike employment are taking on risks that used to belong to the corporate sector.  Not coincidentally, the share of GDP going to the corporate sector as profits has risen and the share accruing to labor as pay has gone down.
That trend, and that risk transfer, are not sustainable over time.  We need a social safety net focused on career support rather than just simple unemployment benefits.  Companies and individuals and the state must work together to build an enhanced and more flexible version of the welfare state that overlaps with lifelong training and education.
The architects of this new industrial revolution, by the way, agree with this proposition.  Yann LeCun, the chief AI scientist at Facebook and one of the pioneers of deep learning, said recently that every economist he has spoken to agrees that governments must take measures to compensate for rising inequality brought about by technology.  “All of them believe this has to do with fiscal policy in the form of taxing, and wealth and income distribution.”
We also need a functioning marketplace.  The collapse of U.S. government action in the area of antitrust and competition law has led to a damaging concentration across most industries — from cable TV to airlines, online advertising and farming.  While a new generation of robber barons controls huge sections of the U.S. economy, corporate profits surge, wages stagnate, and fewer ordinary workers have reason to believe in the capitalist system.
The final component of what we do next concerns not what we do but what they do — “they” meaning the elites who have profited most from the trends of recent decades.  Quite simply, those elites have to pay their taxes.  They have to stop using offshore havens and accounting tricks to hide their wealth from the societies in which they live and from which they make their profits. Instead of founding think tanks and gorging on discussions about improving distant lives, they have to attend to the lives around them in the places they actually live.
A new emphasis on the role of the nation-state; a new partnership between the state and the private sector and the individual; new action on lifelong learning and training; higher and fairer taxes; less security for big corporations: these things shouldn’t be unthinkable.  It is strange and sad that the least likely thing on my wish list is the idea that elites will change their behavior.
But elites may have to change if they don’t want change to be imposed on them.  This coming wave of technological transformation has the potential to be the most serious challenge modern capitalism has faced.  For people who don’t have the chance to change and adapt and reskill, a pitiless world ruled by algorithms and machine learning, in which they have no utility, no relevant skills and no security, could look completely unlivable.  Facing that prospect, the populations of the developed world may do things that make the current populist moment look polite, low-key and lawful.
— John Lanchester
From his article in Time Magazine (dtd: Feb4/11, 2019): “Economy: Leveling The Playing Field
The article also appears online as: “The Next Industrial Revolution Is Coming.  Here’s How We Can Ensure Equality
The link to the entire online version is: http://time.com/collection/davos-2019/5502589/next-industrial-revolution/
[Please note: This article is extensively quoted without permission from the author or from Time Magazine.  I personally subscribe to the physical version of Time Magazine and have done so for almost 50 years now.  I make no claim to ownership of the article or its ideas.  I do NOT normally post so extensively from an article, but this was (to me) a powerful article about the future of civilization, so I have made an exception.  The ellipses indicate where I have edited out portions of the article.  I hope neither the author nor Time Magazine will object to my editing or use of the article.  Obviously, I encourage all of my readers to go to read the original.  —  KMAB]
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On This Day In:
2018 New And Old
2017 Ever
2016 At The Center
2015 True Value In Life
2014 A Potential To Be Concerned
2013 Fine No More
2012 Have You Checked Your Height Lately?
2011 Are You Convinced?

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As powerful as advanced AI might be someday, we need to understand it first and think carefully about how it should be applied.  The best thing we can do is make sure we have the best minds working on AI and support research that helps us develop it faster.  Again, it’s just math.  Not magic.
At a very basic level, I think AI is good and not something we should be afraid of.  We’re already seeing examples of how AI can unlock value and improve the world.  If we can choose hope over fear — and if we advance the fundamental science behind AI — then this is only the beginning.
    —  Mark Zuckerberg
Quoted by: Jason Tanz
In his article: “A To-Do List For The Tech Industry
Appearing in: Wired Magazine, dtd: November 2016
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On This Day In:
2016 Today’s Rule
2015 Remembering Oklahoma City
2014 Who Was That Masked Man?
2013 Enemy Mine
2012 Strengthen Me
2011 Service, Please
2010 The Church In Crisis…

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