A Quote by Oren Etzioni

I love sophisticated algorithms that help consumers in a tangible way. — © Oren Etzioni
I love sophisticated algorithms that help consumers in a tangible way.
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.
Lead generation excels when a campaign is looking to capture a piece of factual intelligence that could never be modelled or predicted through profiling and sophisticated propensity algorithms.
I think that if there's some innovative entrepreneurs out there who can help teach people how they can cost-effectively help themselves and their planet, I think everybody would be for it. That's going to be the challenge - figuring a way to get the marketplace and commerce to teach us consumers another way.
People are very sophisticated consumers of information, and they're pulling all different things.
If old consumers were assumed to be passive, then new consumers are active. If old consumers were predictable and stayed where you told them, then new consumers are migratory, showing a declining loyalty to networks or media. If old consumers were isolated individuals, then new consumers are more socially connected. If the work of media consumers was once silent and invisible, then new consumers are now noisy and public.
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.
It is a good motive, fame and money, as it is tangible and measurable. Being an artist is neither measurable nor tangible and certainly not a way to become rich.
Consumers fall in love with a brand and it's important for a brand to develop and stretch itself to provide for their consumers. I don't suspect that a customer will walk into a store to buy a pair of jeans and end up buying a sofa, but it's about providing loyal consumers with a choice to create a lifestyle.
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.
Businesses are interacting with consumers to socialize rather than learn about customer expectations to in turn, deliver tangible value, improve product experiences, and invest in long-term relationships.
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.
Setting up a college fund would be a great way to redirect the tangible evidence of Daddy's love.
If consumers are strong, if consumers are protected, if they can trust the marketplace and feel confident that they're not being cheated here and there, then consumers can drive this economy forward.
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.
Getting an unsophisticated client was the golden prize. The quickest way to make money on Wall Street is to take the most sophisticated product and try to sell it to the least sophisticated client.
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