A Quote by Geoff Mulgan

Predation is part of the everyday life of capitalism, in sectors as mainstream as pharmaceuticals, software and oil - where people's money, their data, their time and their attention are routinely taken in fundamentally asymmetrical exchanges.
We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]
Fortunately, in Piramal Enterprises, we are in three broad sectors. One is in the whole financial services sector, the second is in pharmaceuticals, and the third is in healthcare analytics and data.
I don't come from a famous family and don't have this detachment from everyday people and everyday life. I'm just doing my job and the attention that comes with it is part of the territory.
I've been saying for a long time, and I think you'll agree, because I said it to you once, had we taken the oil - and we should have taken the oil - ISIS would not have been able to form either, because the oil was their primary source of income. And now they have the oil all over the place, including the oil - a lot of the oil in Libya, which was another one of her disasters.
I'm a huge proponent of exchanges, student exchanges, cultural exchanges, university exchanges. We talk a lot about public diplomacy, .. It's extremely important that we get our message out, but it's also the case that we should not have a monologue with other people. It has to be a conversation, and you can't do that without exchanges and openness.
We also exchange oil for software technology. Uruguay is one of the biggest producers of software. We are breaking with the neoliberal model. We do not believe in free trade. We believe in fair trade and exchange, not competition but cooperation. I'm not giving away oil for free. Just using oil, first to benefit our people, to relieve poverty.
I'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.
The overflow of big money in politics drowns out the voices of everyday people. That is part of the conundrum in America: The more money you have the more speech you have. That leaves everyday people out of the equation.
The overflow of big money in politics drowns out the voices of everyday people. That is part of the conundrum in this country: The more money you have the more speech you have. That leaves everyday people out of the equation.
I mean, when we did 'Families At War,' on Saturday night prime time, people said we were mainstream then. But it wasn't in the least mainstream. The fact that we got that on BBC1 at that time with those ridiculous things, that's as mainstream as we get. We do what we do and people can think that it's mainstream or avant-garde.
The oil areas have a big problem digesting the oil. There's too much money, and the people don't know what to do with it. I'm finding all the time that we have more industries and more success stories which are not involved with oil.
We need a more holistic approach in which we take account of society's most vulnerable sectors. We shouldn't just do broad averaging of country statistics but rather we need to disaggregate the data to determine where the resources are most needed. In most cases, it's usually the reverse: those who are most marginalized - minorities and rural and remote communities - get the least attention and money.
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
The paradigm shift of the ImageNet thinking is that while a lot of people are paying attention to models, let's pay attention to data. Data will redefine how we think about models.
Anti-capitalism is nothing new in Hollywood. From 'Wall-E' to 'Avatar,' corporations are routinely depicted as evil. The contradiction of corporate-funded films denouncing corporations is an irony capitalism cannot just absorb, but thrive on. Yet this anti-capitalism is only allowed within limits.
We routinely participate in elaborate nonverbal exchanges even when we are not consciously aware of doing so.
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