Henri Poincare Quotes

You don't want to influence the same system you are trying to forecast.

Big data is mostly about taking numbers and using those numbers to make predictions about the future. The bigger the data set you have, the more accurate the predictions about the future will be.

In order to predict effectively, we need to use science. And the reason that we need to use science is because then we can reproduce what we're doing; it's not just wisdom or guesswork. And if we can predict, then we can engineer the future.

A smart model is a good model.

Networks love data. They love to be able to look at numbers and try to predict what they think will work.

Every part of your business will change based on what I consider predictive analytics of the future.

Google's founders have had a good eye for imagining what technologies will be significant in the near future. No one asked Google to develop self-driving cars, but it helped them with street views for Google Maps.

I have been doing technology foresight for a number of years now on the level of scenario design, primarily. I want to become more rigorous with research methodology and statistical methods. I want to shift from creating clever SF scenarios to being a professional forecaster able to make rigorous predictions.

When human judgment and big data intersect there are some funny things that happen.

The ability to collect, analyze, triangulate and visualize vast amounts of data in real time is something the human race has never had before. This new set of tools, often referred by the lofty term 'Big Data,' has begun to emerge as a new approach to addressing some of the biggest challenges facing our planet.

Machine learning signicantly enhances the ability to predict where and when crimes are more likely to happen and who may commit them.

The ability to foretell what is going to happen tomorrow, next week, next month, and next year – and to have the ability afterwards to explain why it didn’t happen.

Data is going to be dynamic... and, combined with the performance of computing that allows for artificial intelligence to be applied, is going to bring all kinds of insights and additives to enhance everyday life.

Managers used to say, 'I have a gut feeling.' Do you know what a gut feeling is for a professional manager? It's a pattern that they recognize. But if your system can recognize that pattern, if it's not just a couple of managers who know that pattern, then the system's gut feeling can tell you which way to go. That's really liberating.

The real use of AI in industry is generally for very narrow pattern-matchers - a better search algorithm, an object-detection algorithm, etc. These things are tools which we can use - for good or evil. But they're nothing like self-aware beings.

By definition, big data cannot yield complicated descriptions of causality. Especially in healthcare. Almost all of our diseases occur in the intersections of systems in the body.

When I look at the next set of technologies that we have to build in Salesforce, it's all data-science-based technology. We don't need more cloud. We don't need more mobile. We don't need more social. We need more data science.

The answers to today's most important scientific, business, and social problems lie in data.

Technologies like Ayasdi's exist now to automatically discover information from data without having someone making guesses up front.

The premise and promise of Big Data is that there are no stories, only patterns; that the human preference for story is aligned with the human tendency for error; and that only through dislocations in scale - the scale of sample size and of time - will truth emerge.

The power of Ayasdi is its unique ability to automatically discover insights - regardless of complexity - without asking questions.

Even smaller companies are putting resources behind their analytics teams in the same way they put resources behind engineering and product teams. There are some great tools out there that allow even tiny businesses to use data effectively.

Ayasdi's customers can finally learn the answers to questions that they didn't know to ask in the first place.

You need to use data science and machine learning to get the ground truth of what's happening inside of a company.

Data drives success. That is how we began our success with eSpeed. It was always based on the data.