A Quote by Maelle Gavet
When a handful of tech giants are gatekeepers to the world's data, it's no surprise that the debate about balancing progress against privacy is framed as 'pro-data and, therefore, innovation' versus 'stuck in the Dark Ages'.
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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.
I promoted Hyderabad to the world by saying that there was privacy in India and their data will be sage. Data is wealth.
When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.
As individuals, we have very little say about how our data is being used. I'm not worried about the privacy implications of it so much. But it seems to me that, as an individual, if I'm the one generating the data, I should have some kind of say in how it's going to be used.
Big data is great when you want to verify and quantify small data - as big data is all about seeking a correlation - small data about seeking the causation.
We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.
We use nearly 5 thousand different data points about you to craft and target a message. The data points are not just a representative model of you. The data points are about you, specifically.
The computer is here to stay, therefore it must be kept in its proper place as a tool and a slave, or we will become sorcerer's apprentices, with data data everywhere and not a thought to think.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
The desktop computer industry is dead. Innovation has virtually ceased. Microsoft dominates with very little innovation. That's over. Apple lost. The desktop market has entered the dark ages, and it's going to be in the dark ages for the next 10 years, or certainly for the rest of this decade.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
The NSA is not listening to anyone's phone calls. They're not reading any Americans' e-mails. They're collecting simply the data that your phone company already has, and which you don't have a reasonable expectation of privacy, so they can search that data quickly in the event of a terrorist plot.
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