Lifeboat Foundation

The year is 2021. You’re driving down the highway on your daily commute. You approach a car that’s stubbornly driving at the max speed limit. You decide to pass this overly law-abiding driver, except when you do, you discover there’s no one in the front seat.

As we learned in the first part of our Future of Transportation series, self-driving cars will become publicly available in only a few short years. But due to their component parts, they will likely be far too expensive for the average consumer. Does this mark self-driving cars as an innovation that’s dead in the water? Who’s going to buy these things?

Most articles about autonomous vehicles (AVs) fail to mention that the initial target market for these vehicles won’t be the average consumer—it will be big business. Specifically, taxi and car sharing services. Why? Let’s look at the opportunity self-driving cars represent to one of the biggest taxi/rideshare services on the planet: Uber.

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Made In Space and NanoRacks have been making news lately with the announcement of partnerships to change the way objects are imagined and built off the planet, and now the companies have joined forces to provide a novel new service for CubeSat developers.

They call it “Stash & Deploy,” and the service will leverage the NanoRacks heritage in CubeSat deployment and the capability of Made In Space to provide 3D printing capabilities and deliver – on-demand – satellite manufacturing, assembly, and deployment in the space environment.

The plan calls for a variety of standard and customer-specific satellite components to be “cached” within a satellite deployment vehicle such as the International Space Station, and the components will be “stashed” for rapid manufacture of CubeSats.

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Do we owe our existence to Jupiter? That used to be the standard paradigm in planetary theory, but now theorists routinely debate the merits of such a gas giant planet parked out at a 12 year orbit in our own solar system. However, one thing is clear; solar systems like ours with Jupiter analogs are pretty scarce.

Solar systems like ours, in which Jupiter-like planets orbit their parent stars at Jupiter-like distances, remain scarce in the local stellar neighborhood, says an Australian-led team of astronomers.

The team who report their findings in The Astrophysical Journal, analyzed the latest results from an ongoing planet detection survey of more than 200 solar-type stars mostly within some 300 light years of Earth.

Continue reading “Solar Systems Like Ours Remain Scarce” »

So, space fans, without further ado, here, for the first time in a format easily accessible to the public, are hundreds and hundreds of science-quality images from the Chang’e 3 lander and Yutu rover. I don’t usually host entire data sets (PDS-formatted and all) but I made an exception in this case because the Chinese website is a bit challenging to use.

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Nice! Robo-advice will be accessed by investors worth $2.2 trillion by 2020, equivalent to 12% of the global retail funds.

If you’re a finance professional, the question you probably get asked most by your friends and acquaintances is “what investments they should make”? That’s the basic question that everyone with money will ask. They may ask the “financial advisor” at their bank, they may turn to Google for advice, they may ask their “friends who work in finance”, or they may listen to recommendations of people they trust. However, individuals with a high net worth will typically seek out a wealth management firm with a brand they trust. But which firm?

Try to Google “top wealth management firms” and the first 5 search results will be a comparison of the top 100 wealth management firms. That’s a very competitive space. How do you differentiate yourself from your 99 competitors who are essentially trying to so the same thing you are? One way is through the use of technology, and as a result we see the rise of “robo advisors”. Here’s the definition of a “robo-advisor” from Investopedia:

Continue reading “The Real Truth Behind the Rise of Robo-Advisors” »

One of the best places to test what it will actually be like to fly in Mars’ thin atmosphere is at 90,000 feet in our own. Ironically, this summer, Airbus and partners are testing the Perlan 2 glider in part to help determine among other things just what we need to do to actually aviate through the red planet’s atmosphere. Maybe Andy Weir has a sequel in him.

By pushing the atmospheric envelope at the edge of Earth’s stratosphere, the Airbus Perlan 2 glider’s next tests should pave the way for both future aviation on Mars and Earth-based commercial hypersonic aircraft, Allan McArtor, the Chairman and CEO of Airbus Group, Inc… told me.

The Perlan 2 sailplane/glider, which had its first test flight last September in Oregon, will attempt to reach its optimal cruising altitude of 90,000 feet as early as this coming June in Argentina, says McArtor. When it does, it will be the highest that any winged vehicle, powered or otherwise has gone.

Continue reading “Aviation on Mars? Airbus Perlan 2 Glider To Help Test Its Limits” »

“The dinosaurs became extinct because they didn’t have a space program. And if we become extinct because we don’t have a space program, it’ll serve us right!”

Larry Niven, quoted by Arthur Clarke in interview at space.com, 2001.

Quotations collected by Sylvia Engdahl about why expansion into space is vital to the future survival of humankind, many of them from well-known people.

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The game of Go has long been viewed as the most challenging of classic games for artificial intelligence due to its enormous search space and the difficulty of evaluating board positions and moves.

Google DeepMind introduced a new approach to computer Go with their program, AlphaGo, that uses value networks to evaluate board positions and policy networks to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte-Carlo tree search programs that simulate thousands of random games of self-play. DeepMind also introduce a new search algorithm that combines Monte-Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

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Lonestar developed by Texas A&M is a possible tool that prospectors can utilize to locate mining opportunities on asteroids.

Astronauts fired this small, rectangular hunk from the International Space Station today. The payload will separate into two autonomous satellites as part of a research program to take us one tiny step closer towards making asteroid mining a reality.

If we ever want to mine asteroids, we’re going to need to step up our game for multiple satellites sharing data and working together. A pair of Texan universities are working together on a four-mission sequence to create a pair of robots that can autonomously rendezvous and dock in space. The project is called Low Earth Orbiting Navigation Experiment for Spacecraft Testing Autonomous Rendezvous and Docking — or Lonestar if you ignore the D.

Continue reading “This Two-in-One Satellite Will Bring Us One Step Closer to Asteroid Mining” »