Philippe Perrin Quotes

It's very dangerous to put astronauts on a moon base where there's radiation, solar flares and micro meteorites. It'd be much better to put robots on the moon and have them mentally connected to astronauts on the Earth.

Drones ply the liminal space between the physical and the digital - pilots fly them, but aren't in them. They are versatile and fascinating objects - the things they can do range from the mundane (aerial photography) to the spectacular - killing people, for example.

Shortly afterwards, I did a third one to repair the robotic arm of the station. This arm plays a very important role in the ongoing expansion of the station as well as in the deployment of solar panels.

During that space walk there will be some repositioning of the power so that the arm can be fully controlled by the robotic station that is in the Lab.

I'll be the person using the shuttle robotic arm.

Once you have perfect virtual reality, what else are you supposed to perfect?

We're using the space station as a test bed for some of the technologies that are going to enable us to work autonomously in space and hit some of our deep-space exploration goals.

Nvidia's self-driving-car business grew out of a long-standing relationship with auto companies. Car guys used Nvidia chips for computer-aided design, then used Nvidia supercomputer chips to do crash simulations. When the car guys started thinking about autonomous vehicles, Nvidia leaped at the chance to help them solve the problem.

Within our lifetimes, we will be able to push out enough computational power to simulate reality.

You can't 'control' a Mars mission from Earth. The Mars mission is going to have to be controlled by the people on Mars... There is just too much involved that is out of sight of Earth.

AI-assisted driving is a perfect platform for advancing fundamental human-centric artificial intelligence research while also producing practical applications.

The core businesses are transforming in very futuristic ways. You know, our aviation business, very interesting things are going on, and unmanned vehicles, drone technology, and things like that.

To make a vehicle autonomous, you need to gather massive streams of data from loads of sensors and cameras and process that data on the fly so that the car can 'see' what's around it.

We've managed to motion-track the silkworm's movement as it is building its cocoon. Our aim was to translate the motion-capture data into a 3D printer connected to a robotic arm in order to study the biological structure in larger scales.

Yes, we have prototyped cars that can drive by themselves, but without smart vision, they cannot really tell the difference between a crumpled paper bag on the road, which can be run over, and a rock that size, which should be avoided.

Early AI was mainly based on logic. You're trying to make computers that reason like people. The second route is from biology: You're trying to make computers that can perceive and act and adapt like animals.

When a driverless car looks out on the world, it's not able to distinguish the age of a pedestrian or the number of occupants in a car.

The only path to build intelligent machines is to enable it with powerful visual intelligence, just like what animals did in evolution.

My system uses the speed of components in cameras and cell phones to get four inches of depth through the brain.

When you think about exploring deep space, it's very dangerous for humans. To potentially sacrifice human life is a delicate proposition. On the flip side, if you want to send a robot to another planet for an extended period of time and at some point you know it'll cease to function, it's not considered a tragedy.

There is great potential to use computer vision technology in a constructive and benevolent way.

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

One thing ImageNet changed in the field of AI is suddenly people realized the thankless work of making a dataset was at the core of AI research.

My Ph.D. is in computer vision and machine learning. I developed software that can read your emotions from your face as part of my doctorate work.

Even if we wanted to imbue an autonomous vehicle with an ethical engine, we don't have the technical capability today to do so.