Margrethe Vestager Quotes

The deep learning techniques, while relatively easy to learn, are quite foreign to traditional engineering modalities. It takes a different mindset and a relaxation of the presumption of control. The practitioners are like magi, sequestered from the rest of a typical engineering process.

Artificial intelligence is just a new tool, one that can be used for good and for bad purposes and one that comes with new dangers and downsides as well. We know already that although machine learning has huge potential, data sets with ingrained biases will produce biased results - garbage in, garbage out.

Increasingly, the central question is becoming who will have access to the information these machines must have in storage to guarantee that the right decisions are made.

Forget artificial intelligence - in the brave new world of big data, it's artificial idiocy we should be looking out for.

There is no such thing as transparent intelligence.

As machines take over the decision-making that saves lives, we are left with fewer chances to save lives later.

Machine learning is the science of getting computers to learn without being explicitly programmed.

I am worried that algorithms are getting too prominent in the world. It started out that computer scientists were worried nobody was listening to us. Now I'm worried that too many people are listening.

The revolution in deep nets has been very profound. It definitely surprised me, even though I was sitting right there.

Beyond helping other people build AI systems with Deeplearning.ai, I also hope to build some AI systems myself!

While infusing technology with humanity, we are trying to make sure it's used for good and also trying to foresee some of the ways it can be used in a bad way and eliminate those.

With the Google Brain project, we made the decision to build deep learning processes on top of Google's existing infrastructure.

We now think of internal representation as great big vectors, and we do not think of logic as the paradigm for how to get things to work. We just think you can have these great big neural nets that learn, and so, instead of programming, you are just going to get them to learn everything.

And I think the greatest danger that AI poses isn't so much these anthropomorphic beings who look like us and are beguiling are going to fool us. It's the fact that a intelligence without a body or corporeal form will fool us into trusting it with data, which we seem to think is... it has no repercussions.

Take any old classification problem where you have a lot of data, and it's going to be solved by deep learning. There's going to be thousands of applications of deep learning.

We believe behavioral science, cognitive computing, and machine intelligence are essential to a successful, holistic surveillance offering and critical to efficient and effective organizational compliance with an increasingly intricate global regulatory environment.

Deep learning is a subfield of machine learning, which is a vibrant research area in artificial intelligence, or AI.

Smart CEOs should be thinking about AI and its impact on their respective business.

Only by developing a deeper understanding of AI systems as they act in the world can we ensure that this new infrastructure never turns toxic.

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.

The real problem is not the existential threat of AI. Instead, it is in the development of ethical AI systems.

AIs are only as good as the data they are trained on.

Mood-aware technologies would make personalized recommendations and encourage people to do things differently, better, or faster.

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.

There was a time when events that define the human condition were subject to very limited and time-delayed analysis. In the 21st Century and beyond, however, the human condition is subject to real-time, overwhelming analysis and dissection.