Month: April 2019

Tesla selfdrving

In shadow testing, a car is being driven by a human or a human with autopilot. A new revision of the autopilot software is also present on the vehicle, receiving data from the sensors but not taking control of the car in any way. Rather, it makes decisions about how to drive based on the sensors, and those decisions can be compared to the decisions of a human driver or the older version of the autopilot. If there is a decision — the new software decides to zig where the old one zags, or the new software cruises on when the human hits the brakes, an attempt can be made to figure out how different the decisions were, and how important that difference is. Some portion of those incidents can be given to human beings to examine and learn if the new software is making a mistake. If there is a mistake, it can be marked to be fixed, and the testing continues.

User Input is an error:

Elon Musk views any human user intervention is an error situation for the Tesla Autopilot. Elon means that whenever a human has to take control from the Tesla Autopilot system this is indicating an error that must be fixed for a future fully autonomous car.

Teslas improve with use:

Most of the systems we currently use aren’t built to improve through use. They have locked in performance and capabilities. These systems can only improve through revisions and patches made by technical experts. That approach is on the way out. Systems can now be improved operationally …. Further, for the most complex activities, this will be the only type of system you will be able to buy.

Let me guess, the media won’t be falling over themselves to report on these instances where the tesla autopilot saved lives.

Doctors told Neally later that he’d suffered a pulmonary embolism. They told him he was lucky to have survived. If you ask Neally, however, he’ll tell you he was lucky to be driving a Tesla. As he writhed in the driver’s seat, the vehicle’s software negotiated 30 highway km to a hospital just off an exit ramp. He manually steered it into the parking lot and checked himself into the emergency room, where he was promptly treated. By night’s end he had recovered enough to go home.

Another analysis on the Tesla software disruption:

Tesla’s first bet is that it will solve the vision-only problem before the other sensors get small and cheap, and that it will solve all the rest of the autonomy problems by then as well. This is strongly counter-consensus. It hopes to do it the harder way before anyone else does it the easier way. That is, it’s entirely possible that Waymo, or someone else, gets autonomy to work in 202x with a $1000 or $2000 LIDAR and vision sensor suite and Tesla still doesn’t have it working with vision alone.

The second bet is that Tesla will be able to get autonomy working with enough of a lead to benefit from a strong winner takes all effect – ‘more cars means more data means better autonomy means more cars’. After all, even if Tesla did get the vision-only approach working, it doesn’t necessarily follow that no-one else would. Hence, the bet is that autonomous capability will not be a commodity.

This video from 2014 is what happens when you improve cars at the speed of the software industry. very very impressive.

Being able to update the fleet isn’t just useful for selfdriving

Researchers Hacked a Model S, But Tesla’s Already Released a Patch If you were CEO of a car manufacturer, which of these headlines would you rather were written about you? The first speaks of a tired, old manufacturing model where fixes take months and involve expense and inconvenience. The second speaks of a nimble model more reminiscent of a smartphone than a car

Dark Matter Evidence?

While dark matter doesn’t shine or fraternize with known particles, in the right sort of collision these particles could annihilate in a shower of familiar matter and antimatter that would then go out with a puff of gamma rays. A measurement of these offshoots would represent the first evidence of dark matter that wasn’t exclusively gravitational in nature. Yet dark matter wasn’t the only thing that could be generating the excess gamma rays. They could shine from cosmic lighthouses known as millisecond pulsars — magnetically charged neutron stars that make 1000 turns each second. A group of undiscovered pulsars too dim to be picked out individually could be bathing the center of the galaxy in extra gamma rays. Experts express optimism that with these inputs, the current modeling wars could settle down in a matter of years. And now that the gamma ray glow is back on the table, hopes for dark matter look somewhat brighter. “If the galactic center excess is back in the game, potentially we are seeing the first signal of dark matter.”

The AI Does Not Hate You

This is a book about AI and AI risk. But it’s also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can’t give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right, and why they might be wrong. It is a book about the cutting edge of our thinking on intelligence and rationality right now by the people who stay up all night worrying about it.

Teranga

Everything on the menu—from black-eyed-pea salad to fonio, an ancient grain that Thiam imports from West Africa, to chicken marinated in lime, garlic, and thyme—is designed to pair with everything else. Drinks include ginger juice, bissap (a sweetened mint-hibiscus tea), and bouye, a traditional Senegalese shake made with a fruit called baobab.

Info Ops Kill Chain

it’s time to conceptualize the “information operations kill chain.” Information attacks against democracies, whether they’re attempts to polarize political processes or to increase mistrust in social institutions, also involve a series of steps. And enumerating those steps will clarify possibilities for defense.

Visual Object Detection

2 Cheap Cameras Can Provide LiDAR-like Object Detection

For most self-driving cars, the data captured by cameras or sensors is analyzed using convolutional neural networks – a kind of machine learning that identifies images by applying filters that recognize patterns associated with them. These convolutional neural networks have been shown to be very good at identifying objects in standard color photographs, but they can distort the 3D information if it’s represented from the front. So when Wang and colleagues switched the representation from a frontal perspective to a point cloud observed from a bird’s-eye view, the accuracy more than tripled.

Data Manifesto

a recasting of “information wants to be free”

  1. Data cannot be owned. By anybody.
  2. The natural habitat of data is in the commons. It is born in the commons, and will return to the commons, even if it is granted temporary monopolies. The longer it spends in the commons, the better.
  3. Data is a shared resource, that only exists in relationship to its sources and substrates.
  4. Any party that touches or generates a bit of data has rights and responsibilities about that data.
  5. Rights always have corresponding responsibilities.
  6. Control of data is both a right and responsibility that is always shared.
  7. Privacy is a misunderstanding that does not apply to data.
  8. Data is made more valuable by being connected to other data. Solitary data is worthless.
  9. Data is made more valuable by moving. Storage is weak because it halts, “Movage” is better.
  10. Both directions of movage are important — where it came from, where it goes.
  11. The meta data about where data goes is as important as where it came from.
  12. Ensuring bi-directionality, the symmetry of movage, is important to the robustness of the data net.
  13. Data can generate infinite derivative data (meta data) but they all follow the same rules.
  14. When new data is generated from data (meta data) the rights and responsibilities of the first generation proceed to the second.
  15. At the same time, meta data has claims of rights and responsibilities upon the root data.
  16. Data can be expensive or free, determined by the market. It has no inherent value.
  17. Data is easy to replicate in time (free copies) and difficult to replicate over time (digital decay). The only way to carry data into the future is if it is exercised (moved) by those who care about it.
  18. Like all other shared resources, data can suffer from the tragedy of the commons, and this commons must be protected by governments.
  19. As the number of entities, including meta data, touching a bit of data expands over time, with claims of rights and responsibilities, some values will dilute and some will amplify.
  20. To manage the web of relationships, rights and responsibilities of data will require technological and social tools that don’t exist yet.