The use of Hemingway as an example is unfortunate. Something less literary would be a better example maybe?:
Close to the western summit there is the dried and frozen carcass of a leopard. No one has explained what the leopard was seeking at that altitude.
Near the top of the west there is a dry and frozen dead body of leopard. No one has ever explained what leopard wanted at that altitude.
One of those is pretty stilted and not much better than lot of machine translations. The uncanny valley of being good enough but not optimal is probably something that's going to plague AI for a long time.
Google’s decision to reorganize itself around A.I. was the first major manifestation of what has become an industrywide machine-learning delirium. Over the past four years, six companies in particular — Google, Facebook, Apple, Amazon, Microsoft and the Chinese firm Baidu — have touched off an arms race for A.I. talent, particularly within universities. Corporate promises of resources and freedom have thinned out top academic departments. It has become widely known in Silicon Valley that Mark Zuckerberg, chief executive of Facebook, personally oversees, with phone calls and video-chat blandishments, his company’s overtures to the most desirable graduate students. Starting salaries of seven figures are not unheard-of. Attendance at the field’s most important academic conference has nearly quadrupled. What is at stake is not just one more piecemeal innovation but control over what very well could represent an entirely new computational platform: pervasive, ambient artificial intelligence.
That's...worrying. Given all of these companies lack of respect for privacy and consumers, it should trouble us that one of them may end up with such a world-changing innovation. Throw enough money into one place, stick a bunch of PhDs in a building, and eventually you'll get something. It's just numbers. Bodies + money. What's inspiring about that?
Does the prospect of Mark Zuckerberg having control over AI for the next five decades trouble you? Even more remarkable is he'd do it on the back of having made a marginally better social networking site in PHP in 2004 and spreading it via the best social network in the world - Ivy League universities. And now those same universities are being raided for talent by these companies...
Is this how we should be picking winners? The distinct lack of diversity and their past stances and actions are troubling. This seems to be mostly a hype piece without any regard for practical effects.
If these same companies can't anticipate or mitigate the impact of issues like fake news until after an election, what makes you think they understand the consequences and impact of something much more complex? And even if they do anticipate it, how do they hold back the pressures of shareholders?
I just hope that we do see multiple such platforms of AI prevailing in the long term. Fragmentation in AI platform would ensure flexibility and bit of privacy protection on consumer side and eventually these competitors can keep each other in check. for example, Amazon echo vs Google home. If Google starts being very creepy in terms of accessing my data to serve me ads, I would just switch to Echo or some other platform. At least I can live in that kind of world.
I found it weird that the article claims that the lack of the definite article is the only sign that makes the machine-translated version of the Hemingway worse. OK, that's the only clinching evidence, but it's easy to spot how it's a lot more stilted in other respects, too.
It's still impressive, mind, and a big improvement over the previous translation, but not perfect like the article wants to imply.
Close to the western summit there is the dried and frozen carcass of a leopard. No one has explained what the leopard was seeking at that altitude.
Near the top of the west there is a dry and frozen dead body of leopard. No one has ever explained what leopard wanted at that altitude.
One of those is pretty stilted and not much better than lot of machine translations. The uncanny valley of being good enough but not optimal is probably something that's going to plague AI for a long time.
Google’s decision to reorganize itself around A.I. was the first major manifestation of what has become an industrywide machine-learning delirium. Over the past four years, six companies in particular — Google, Facebook, Apple, Amazon, Microsoft and the Chinese firm Baidu — have touched off an arms race for A.I. talent, particularly within universities. Corporate promises of resources and freedom have thinned out top academic departments. It has become widely known in Silicon Valley that Mark Zuckerberg, chief executive of Facebook, personally oversees, with phone calls and video-chat blandishments, his company’s overtures to the most desirable graduate students. Starting salaries of seven figures are not unheard-of. Attendance at the field’s most important academic conference has nearly quadrupled. What is at stake is not just one more piecemeal innovation but control over what very well could represent an entirely new computational platform: pervasive, ambient artificial intelligence.
That's...worrying. Given all of these companies lack of respect for privacy and consumers, it should trouble us that one of them may end up with such a world-changing innovation. Throw enough money into one place, stick a bunch of PhDs in a building, and eventually you'll get something. It's just numbers. Bodies + money. What's inspiring about that?
Does the prospect of Mark Zuckerberg having control over AI for the next five decades trouble you? Even more remarkable is he'd do it on the back of having made a marginally better social networking site in PHP in 2004 and spreading it via the best social network in the world - Ivy League universities. And now those same universities are being raided for talent by these companies...
Is this how we should be picking winners? The distinct lack of diversity and their past stances and actions are troubling. This seems to be mostly a hype piece without any regard for practical effects.
If these same companies can't anticipate or mitigate the impact of issues like fake news until after an election, what makes you think they understand the consequences and impact of something much more complex? And even if they do anticipate it, how do they hold back the pressures of shareholders?