YouSaid · the spoken record

Evan W. Ackerman

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27
first
2017-09-16
most recent
2017-09-16
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1
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podcast

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  1. “We're talking about sensors that are mounted on the self driving car, LIDAR and the cameras are always working together. Generally speaking, they're all running very fast multiple times per second. As the car is driving, for instance, at fairly high speed, I don't know, 70 miles per hour on the highway, the car is generating or collecting a lot of data as it's driving at that high speed with both the cameras, the lidars, the radars, and all the other sensors.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “Know either you measure with a ruler or with, I don't know, horses or triangulation. You're trying to get some kind of distance measure, right? through triangulation with camera data, you can do some triangulation and get distance estimate for sure. But when you're talking about extreme high precision measurement, cameras oftentimes it's just not enough. And lasers gives you a precise measurement of depths or distance in the 3D space.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “Well, visual's really important, but I mean, for the same reason Wei is saying today in the past they would use other methods, triangulation. It's about space. It's about space and taking mathematical calculations.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “We try to actually make good use of all the sensors that are going to be mounted on a, let's say, a typical SWAF driving car. The reason is that self-driving car number one requirement needs to be very safe. We want to make sure we can take advantage of all the sensors in case when the car is running and one type of a sensor may fail or make it blocked, we can actually switch between different type of sensors in those backup plan as well.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “On a very high level, obviously, there's the hardware component as well as the software component. The hardware components are more visible because if you look at even a picture of a self-driving car, you will quickly recognize it's a self-driving car mostly because it has a lot of sensors typically around its rooftop. And all these sensors are useful for map creation and map update purpose. We use a combination of different type of sensors that includes cameras. LIDAR GPS IMU, which is a unit that tracks the movement of the car and the radars as well.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “That would call to people to come map it. So I don't think it is gone really if we think about the oceans. I know ways not talking about submarines being autopilot. The whole bathymetry mapping is a complete, fascinating bathymetry mapping.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “It's always been important to capture as much as possible. Now, these were not obviously not anything like HD maps or even digital maps, but they were covering the whole earth. People love on old maps the notion of terra incognita, which is put over the center of Australia or the American West.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “I think a little more multidimensional because it isn't just about scale, it's also about comprehensiveness. So the first Atlas was published in fifteen seventy by Abraham Ortelius, and it was actually the best-selling book in Europe.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “Land versus An element it's exploding, the simple map to as full, as comprehensive as possible. The map needs to describe every little thing on the road and it needs to describe a lot of hidden things that you don't typically see on the map. Like, for instance, the speed limit on the road that you see, you want to tell encode into the map whether or not this lane is allowed to go straight at the intersection or is required to make a left turn or right turn.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  10. “Roll through it. It's so interesting because I think of maps on some basic level as being condensing a huge amount of information and like taking one element of that information and showing it simplifying one down into one picture of like”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  11. “Borges writes a short story about the cartographer that made a map that was one-to-one and the problem he couldn't unroll it. It made me realize that HD mapping is a one to one mapping, and yet we don't unroll it. We roll through it.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  12. “If it's five centimeters in HD mapping, that's approaching something that's been sort of a holy grail for mappers forever, which is what we call the one-to-one map. It's the map of the world as big as the world.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  13. “I mean, people tend to think why do I need, say, 5 centimeter or 10 centimeter accuracy when I'm driving down the road. In most cases, the tolerance for error might be higher than that, but then there are going to be cases where if, you know, you're driving on, you know, I don't know the road to Tahoe, there's literally cliffs on one side and there's really no room for error or any error. So the map needs to be extremely precise and it needs to contain a lot of information that again humans may take for granted. So not only we need to know where the lanes are, where the road boundaries are, we also want to know where the curbs are, how high the curbs are.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  14. “Maps that are purposefully built for self driving purpose are usually called high definition maps or HD map for short. This specifically referred to the maps that have extremely high precision. And we're talking about centimeter level accuracy or precision because the robots need very precise instructions on how to maneuver themselves and how to navigate themselves around the 3D space. Right.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  15. “That's right. These decisions are very hard for robots to make. And as part of the decision making process, the mapping becomes a very critical component of helping the robots to make the right decisions.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  16. “We need maps that are easy to interpret by robots. DeepMap is focusing on self-driving cars, but you can generalize it to any robot that needs to roam around the physical world. Even though robots can't outperform humans in certain aspects, in other aspects they are intelligence-wise, humans are actually much smarter. Humans tend to take for granted, such as stopping at the right place at an intersection, watching for the right traffic signal”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  17. “So now we have a totally different set of demands that we need out of our maps. When we start looking at autonomous vehicles, we don't have enough right now to make sure that autonomous car can predict exactly where something is and be safely in real time, right? So what has to change about mapping to serve that?”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  18. “Making those interpretations. That's absolutely correct. And what we are, the new period we're going to enter into is or what's needed to be built for self-driving space is actually maps built purposefully build for robotics systems.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  19. “That's right, you get real time traffic on your Google Maps app and so on and so forth. But if you actually dive deeper maps today, including the digital maps, are actually built for human consumption only. So whether or not you are looking at, say, Google Maps or Apple Maps, Ways and then so on, these are maps purposely built to be first of all very easy to interpret by human beings and easy to use for navigation purpose. The navigation system is telling the humans how to navigate that car according to some very simple instruments.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  20. “It's the access has been the most profound change. The actual depiction of space, I think, or the goal to depict space has been remarkably consistent. Not only the printing or the access of the map has changed over time, but if you look at the general trend, maps tend to get more and more accurate over time, just in general. Right. We're already.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  21. “Methods of printing particularly shape mapping so the first maps were done with woodblock. You could only get, you know, a hundred good impressions. So maps were held by people who were rulers, who were wealthy and so on. Then it changed to copper engraving. You could make 500 impressions. Copper engraving to lithography in the 19th century. Thousands of maps and now chromolithography. And then eventually digital distribution over the web. So maps have become ubiquitous.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  22. “One thing that has changed drastically from paper maps is that maps are dynamic now. Maps are changing. You know, with paper maps, we have a sense of scale. The scale is printed onto the map and it's fixed. But with digital maps, the scale is totally fluid and variable. And the accuracy just depends on the size of the resolution. Mapping as a field has evolved or reinvented itself many times throughout history and now we're reinventing it.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  23. “Would be, you know, typically officers in the Army 1870 with a, we have a big wooden board that they would keep on their arm as they drew the map from their horse, sort of like not a self-driving car, but like a...”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  24. “That's actually a very interesting question because as of today, that process is actually not happening. We are collecting a lot of data, but the information that is actually being shared for map creation purpose is very small. So if you think about the maps that you actually use today, right, there are maps that you have on your phone, there are maps that are probably in your car navigation system as well. Those maps were not created from the GPS unit that you have on your car or the camera system that you have in your car and whatnot they were created by special what we call mapping survey fleets. So companies like for instance Google will build these special fleet that has a lot of special sensors mounted on these special cars. They will hire human drivers to drive this road, collect a lot of data, and then they do a lot of offline processing.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  25. “It's about getting the right information and then do it in a very incredibly, the most precise way at the given time 300 years ago, even 500 years ago. Understanding of the environment is very limited by somehow they need to predict into areas that they cannot visually see. And today, you know, back to your question, you know, what are the backbones of today's digital maps? Well, first of all, we have a lot of sensors that can enable us to see far, right? You know, there are satellites up in there, there are, you know, airplanes up in the air, even the cars on the road, a lot of them have a lot of sensors as well. We'll have radars, we'll have cameras and so on. So a lot of these digital information is already getting collected and we can use that information to help us create digital maps.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  26. “Well, it was really around the time of Columbus because the whole discovery of North and South America produced a phenomenal amount of desire to map it, to possess it. One of our favorite globes is called the Earth Apple, which was by Martin Behem, the year Columbus discovered America in 1492. And there's no North and South America on the globe.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source

  27. “Well, I see, I never referred to Sexton as primitive. You know, the LIDAR of the day. Sextants opened up the whole world and created the ability to make scale maps and to map essentially beyond where you were.”

    2017-09-16 · a16z Podcast · a16z Podcast: Exploding the Map · IDENTIFIED FROM THE TRANSCRIPT · source