A Quote by Frans van Houten

Genomics, Artificial Intelligence, and Deep Machine learning technologies are helping practitioners deliver better diagnosis and actually freeing up time for patient interaction.
Deep learning is a subfield of machine learning, which is a vibrant research area in artificial intelligence, or AI.
Now, given the increasing importance of artificial intelligence, automation, machine learning, and other innovative technologies, we are evolving Accenture Digital to be even more relevant to our clients and drive even greater differentiation in the marketplace.
Artificial intelligence, machine learning... cell therapy, immunotherapy. There's just a constant stream of investment ideas we could pursue better in that fashion.
Previously, we might use machine learning in a few sub-components of a system. Now we actually use machine learning to replace entire sets of systems, rather than trying to make a better machine learning model for each of the pieces.
Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data - big surfaces, deep depths - and not enough data - it is too expensive and not necessarily useful to collect samples of any kind from all over.
I think whatever nation or whoever develops one artificial intelligence will probably make it so that artificial intelligence always stays ahead of any other developing artificial intelligence at any other point in time. It might even do things like send viruses to a second artificial intelligence, just so it can wipe it out, to protect its grounds. It's gonna be very similar to national politics.
You can imagine all the things that people want in machine learning and artificial intelligence area that we're working on, that we'll continue to work on in the future.
By developing deep learning solutions that are faster, easier, and less expensive to use, Nervana is democratizing deep learning and fueling advances in medical diagnostics, image and speech recognition, genomics, agriculture, finance, and eventually across all industries.
We need to be vigilant about how we design and train these machine-learning systems, or we will see ingrained forms of bias built into the artificial intelligence of the future.
Artificial intelligence is one of 50 things that Watson does. There is also machine learning, text-to-speech, speech-to-text, and different analytical engines - they're like little Lego bricks. You can put intelligence in any product or any process you have.
What I advocate for is that, as soon as we get to the point when artificial intelligence can take off and be as smart, or even 10 times more intelligent than us, we stop that research and we have the research of cranial implant technology or the brainwave. And we make that so good so that, when artificial intelligence actually decides - when we actually decide to switch the on-button - human beings will also be a part of that intelligence. We will be merged, basically directly.
There is no reason and no way that a human mind can keep up with an artificial intelligence machine by 2035.
There is huge demand for artificial intelligence technologies.
As a Millennial and Gen Z expert at Accenture I had the opportunity to host and lead several workshops and panels with key clients at industry events. The topics ranged from virtual reality to blockchain; artificial intelligence to machine learning.
Things like chatbots, machine learning tools, natural language processing, or sentiment analysis are applications of artificial intelligence that may one day profoundly change how we think about and transact in travel and local experiences.
The techniques of artificial intelligence are to the mind what bureaucracy is to human social interaction.
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