A Quote by William Hurt
The problem with Google is you have 360 degrees of omnidirectional information on a linear basis, but the algorithms for irony and ambiguity are not there. And those are the algorithms of wisdom.
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In popular books and articles, information technology writer Carr has worried over the ways that algorithms like those employed by Google are reshaping the ways we think.
These algorithms, which I'll call public relevance algorithms, are-by the very same mathematical procedures-producing and certifying knowledge. The algorithmic assessment of information, then, represents a particular knowledge logic, one built on specific presumptions about what knowledge is and how one should identify its most relevant components. That we are now turning to algorithms to identify what we need to know is as momentous as having relied on credentialed experts, the scientific method, common sense, or the word of God.
As algorithms push humans out of the job market, wealth and power might become concentrated in the hands of the tiny elite that owns the all-powerful algorithms, creating unprecedented social and political inequality. Alternatively, the algorithms might themselves become the owners.
Once you see the problems that algorithms can introduce, people can be quick to want to throw them away altogether and think the situation would be resolved by sticking to human decisions until the algorithms are better.
When Spotify launched in the U.S. in 2011, it relied on simple usage-based algorithms to connect users and music, a process known as 'collaborative filtering.' These algorithms were more often annoying than useful.
In deep learning, the algorithms we use now are versions of the algorithms we were developing in the 1980s, the 1990s. People were very optimistic about them, but it turns out they didn't work too well.
Google helps us sort the Internet by providing a sense of hierarchy to information. Facebook uses its algorithms and its intricate understanding of our social circles to filter the news we encounter. Amazon bestrides book publishing with its overwhelming hold on that market.
Facebook and Google are essentially an advertising duopoly, and we have almost no idea how their algorithms work.
Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.
It's difficult to make your clients understand that there are certain days that the market will go up or down 2%, and it's basically driven by algorithms talking to algorithms. There's no real rhyme or reason for that. So it's difficult. We just try to preach long-term investing and staying the course.
Increasingly, our decisions will be made by the algorithms that surround us. Whenever there is a big dilemma, you just ask Google what to do. And what kind of life is that?
Facebook, Twitter and YouTube create algorithms that promote and highlight information. That is an active engineering decision.
Competitors argue that Google rigs its search algorithms to demote listings for competing search engines. Many of the allegations of demotion come generally from sites of pretty questionable quality, such as Nextag and Foundem. Some of Google's primary competitors in 'specialized search' clearly place well in search results - Amazon and Yelp.
I want to talk about privacy, the quality of the information you receive, whether it's neutral or commercial or pointed, bringing consciousness to the lack of neutrality in the algorithms.
AI does not keep me up at night. Almost no one is working on conscious machines. Deep learning algorithms, or Google search, or Facebook personalization, or Siri or self driving cars or Watson, those have the same relationship to conscious machines as a toaster does to a chess-playing computer.
AIs are only as good as the data they are trained on. And while many of the tech giants working on AI, like Google and Facebook, have open-sourced some of their algorithms, they hold back most of their data.
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