Photographic installation by Matthew Mohr is a large head-shaped LED display which presents subject’s faces:
“As We Are” is a fourteen-foot, 3-D universal human head made from ribbons of ultra-bright, LED screens. In the back of the neck is a photo booth capable of taking 3D pictures. Once a visitor has their picture taken, they step out of the booth and their head is displayed on the giant head.
The sculpture addresses the relationship between self and representation of self, asking the subject of the portrait to reconsider presence through magnification. It is intended to provide amusement and evoke larger discussions around the phenomena of social media, diversity, and the power dynamic of public art.
Three rules for ensuring that A.I. systems don’t run roughshod over humans.
While it is good that some people are waking up to the potential problems of AI for society, the ideas on regulating AI in this opinion piece are largely worthless because the author still thinks of AI as a tool owned and controlled by humans. But the very definition of a true AI is that it is autonomous--and as autonomous entities, there’s no reason to expect them to follow human morality or laws. It’s idiotic to think that applying a few general “laws” to the “programming” of AI’s would work, since it is not possible (for humans, at least) to foresee the outcomes of such complex programming interactions. It would take another AI (many AI’s) to control the whole process.
Thus, while applying the same laws to AI’s as to humans is, at first glance, sensible, how would those laws be implemented and enforced at a global level, without continually relying on more powerful AI’s (AI gods) to even track potential outcomes, much less enforce rules on them?
Moreover, at a more practical level, such laws would not stop AI’s and robots from outperforming and replacing humans for most jobs. Capitalism in fact demands that the more productive must replace the less productive. This can only lead to a crisis within capitalism, for when human consumption is reduced through lack of wages, it is hard to see how the economic system can be sustained without major redistributions of wealth.
Advertising companies, tech giants, data collectors, and the federal government, it turns out.
“The latest generation of this technology will allow law enforcement to scan the face of every man, woman, and child walking in front of a street surveillance camera… Do you have the right to walk down the street without the government secretly scanning your face? Is it a good idea to give government so much power with so few limits?”
It’s a classic human v machine scenario: as AI gets better at teaching and providing educational assistance, the question inevitably turns to whether and when human teachers will be replaced by computers.
I always love it when someone who describes himself as “a best-selling author & keynote speaker on business, technology and big data” feels free to opine about what does, or might, work well in the classroom. Cause, after all, anyone can teach, right? That must be why there have always been so many great teachers. And thus, writing algorithms to do (or wait, to provide support for!) what good teachers do will be a real snap, yes?
To be fair, most of the points the author of this short piece makes are fairly reasonable in themselves. It’s what he doesn’t say that is galling: i.e., he makes no mention of any financial considerations underlying these issues. You can, of course, still see the EdTech entrepreneur’s brain turning between the lines here (far less rapidly than an AI brain, of course--could we please think seriously about replacing these people with AI’s? I frankly think they would much more of a breeze to algorithmize than good teachers): EdTech thinks: Oh Yea! profits from paying fewer teachers less money (like teacher’s aide sorts of money) and we can still claim students will benefit. (Note, of course, that there’s no actual data to support these assumptions.)
Yeah, and what jobs will you be training these students to do? To be best-selling authors and keynote speakers on business, technology, and big data? Future entrepreneurs? Ah. No doubt that’s the key to solving our educational and technological issues.
Sure, AI will make teaching and learning and everything better—but actually, pretty much only for those who own the AI’s.
Software called DeepCoder has solved simple programming challenges by piecing together bits of borrowed code
Remember the old jokes about replacing light bulbs?
Well, how many computer programs does it take to replace a computer programmer? Maybe not too many, as it turns out; but hell, they can potentially self-replicate anyway, so even if it takes millions of them, that’s a lot of programmers who will end up out of jobs.
Music video for track by The Hubschrauber put together by GUAP features unique visual style formed from visualizing video motion vectors.
If you don’t know what motion vectors are, it is part of the video compression process to make video sizes smaller by compaing neighbour frames for visual differences between each other.
Dutch media production collective GUAP created the experimental music video for ‘Kepler’, using a technique that visualises organically generated motion vectors from regular footage. Motion vectors are normally generated to manipulate footage for slow motion for example, but the raw date can be used to create effects like in the video.
Kepler is the lead single of the debut album 'Kepler-186f’ from rock band The Hubschrauber. The music and the video both heavily incorporate themes of space travel, and leaving our planet and moving to the titular Earth-like planet (Kepler-186f) instead.
The record itself will actually be launched to the moon via satellite in 2018, with the help of a Dutch university that develops measuring instruments for a Chinese lunar mission.
The world's top AI researchers met to consider the threats posed by their research. The global economy could be the first casualty.
Duh.
Sample quote: “ . . . the rise of driverless cars and trucks is just a start. New AI techniques are poised to reinvent everything from manufacturing to healthcare to Wall Street.”
Love the MIT economist who thinks more human entrepreneurship will somehow “solve” this problem. First, I’m betting an AI could be written right now (and perhaps already has been) that could be a better entrepreneur than most human beings. Second, who exactly would these entrepreneurs be selling their goods and services to? Other entrepreneurs? That can only lead to a lot of failed entrepreneurs.
There’s no way that scenario pencils out. As people increasingly are marginalized economically, they buy less; economy heads for recessionary spiral; most “entrepreneurs” (and everybody else too) go bust. Might be some jobs guarding the wealth of the .1%, though.
The first day of the Brains vs. AI poker tournament is in the books, and the Libratus bot from Carnegie Mellon University emerged as the clear winner, collecting $81,716 to the humans $7,228. Both...
Interestingly, this seems to suggest that the Libratus bot (a rather curious name in this context) is not simply “brute-forcing” human players; it is actually more “creative”--or at least unpredicable--than humans in its betting.
How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself.
Interesting historical survey.
Of course, it seems that almost everyone has already cited or reposted this piece. It’s here mainly for reference.
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