Jean-Philippe Courtois Quotes

Google is all about information. So the notion of using and presenting information in the right point at the right time to users is what, in essence, describes Google.

Along with Facebook, Microsoft, and Apple, these companies are in a race to become our 'personal assistant.' They want to wake us in the morning, have their artificial intelligence software guide us through our days, and never quite leave our sides.

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

Asking Siri where the nearest sushi bar is - that's not interesting. What's interesting is asking your phone where one of your friends have last had dinner in the neighborhood, or having it recommend a cool paella place in Barcelona because it knows you eat paella all the time at home.

Computers ought to help people find their own best path through lots of textual information.

In the early stages of negotiation software, on your smartphone, there may be programs that listen to the pitch of a voice, or that test for stress. You'll just ask the program, 'Was he lying? Was he eager to do business with me?' Maybe the computer will be right sixty per cent of the time.

Google Now is one of those products that to many users doesn't seem like a product at all. It is instead the experience one has when you use the Google Search application on your Android or iPhone device (it's consistently a top free app on the iTunes charts). You probably know it as Google search, but it's far, far more than that.

I'm a geek through and through. My last job at Microsoft was leading much of the search engine relevance work on Bing. There we got to play with huge amounts of data, with neural networks and other AI techniques, with massive server farms.

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.

One of the things Baidu did well early on was to create an internal platform that made it possible for any engineer to apply deep learning to whatever application they wanted to, including applications that AI researchers like me would never have thought of.

Human language is the new UI layer, bots are like new applications, and digital assistants are meta apps. Intelligence is infused into all of your interactions.

AI - not so some kind of far-off thing. It's part of our lives now, from your phone to everything you do. It makes our lives easier in a lot of ways.

The whole concept of data science is that the software becomes the expert, and you, as the average user, are able to understand what's going on.

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.

Without your data, Google couldn't pursue the dream of trying to figure out what you're really thinking when you're asking a question, of trying to discern, from the imprecision of your language, the exact answer you're looking for.

The model of Yood is 'taking search out of search.'

I am often asked what the future holds for Emotion AI, and my answer is simple: it will be ubiquitous, engrained in the technologies we use every day, running in the background, making our tech interactions more personalized, relevant, authentic and interactive.

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

Emotion AI uses massive amounts of data. In fact, Affectiva has built the world's largest emotion data repository.

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

Scientists need the infrastructure for scientific search to aid their research, and they need it to offer relevancy and ways to separate the wheat from the chaff - the useful from the noise - via AI-enabled algorithms. With AI, such an infrastructure would be able to identify the exact study a scientist needs from the tens of thousands on a topic.

We have a good sense of the pulse of the industry. We know what's going on out there. We know that deep learning adoption is broad. It's going into production at scale.

A lot of what people are calling 'artificial intelligence' is really data analytics - in other words, business as usual. If the hype leaves you asking 'What is A.I., really?,' don't worry, you're not alone.

Artificial intelligence is here and being rapidly commercialized, with new applications being created not just for manufacturing but also for energy, healthcare, and oil and gas. This will change how we all do business.

The battle between Google and Apple has shifted from devices, operating systems, and apps to a new, amorphous idea called 'contextual computing.' We have become data-spewing factories, and the only way to make sense of it all is through context.