Making pizza is not rocket science, but for this actual rocket scientist it is now. Benson Tsai is a former SpaceX employee who is now using his skills to launch a new venture: Stellar Pizza, a fully automated, mobile pizza delivery service. When a customer places an order on an app, an algorithm decides when to start making the pizza based on how long it will take to get to the delivery address. Inside Edition Digital’s Mara Montalbano has more.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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AOPEN ACE series raises the bar with scalable commercial computing, maintaining reliability at an affordable price — without sacrificing quality for quantity.
How groups of humans working together collaboratively should redistribute the wealth they create is a problem that has plagued philosophers, economists, and political scientists for years. A new study from DeepMind suggests AI may be able to make better decisions than humans.
AI is proving increasingly adept at solving complex challenges in everything from business to biomedicine, so the idea of using it to help design solutions to social problems is an attractive one. But doing so is tricky, because answering these kinds of questions requires relying on highly subjective ideas like fairness, justice, and responsibility.
For an AI solution to work it needs to align with the values of the society it is dealing with, but the diversity of political ideologies that exists today suggests that these are far from uniform. That makes it hard to work out what should be optimized for and introduces the danger of the developers’ values biasing the outcome of the process.
One consequence of this is there is no guarantee the clocks will tick at the same rate. In fact, many clocks will tick at different rates.
Even worse, the faster you travel relative to someone else, the slower your clock will tick compared to theirs.
This means if you travel very fast in a spaceship—as Buzz does—a few minutes might pass for you, but years might pass for someone on the planet you left behind.
Photosynthesis uses a series of chemical reactions to convert carbon dioxide, water, and sunlight into glucose and oxygen. The light-dependent stage comes first, and relies on sunlight to transfer energy to plants, which convert it to chemical energy. The light-independent stage (also called the Calvin Cycle) follows, when this chemical energy and carbon dioxide are used to form carbohydrate molecules (like glucose).
A research team from UC Riverside and the University of Delaware found a way to leapfrog over the light-dependent stage entirely, providing plants with the chemical energy they need to complete the Calvin Cycle in total darkness. They used an electrolysis to convert carbon dioxide and water into acetate, a salt or ester form of acetic acid and a common building block for biosynthesis (it’s also the main component of vinegar). The team fed the acetate to plants in the dark, finding they were able to use it as they would have used the chemical energy they’d get from sunlight.
They tried their method on several varieties of plants and measured the differences in growth efficiency as compared to regular photosynthesis. Green algae grew four times more efficiently, while yeast saw an 18-fold improvement.
An artificially intelligent first author presents many ethical questions—and could upend the publishing process.
CEO Drew Perkins discusses what the first demo was like. By year’s end, I could be next.
The dream of transforming windows into active power generators has just edged one step closer to realization.
A team of researchers from ARC Centre of Excellence in Exciton Science led by Professor Jacek Jasieniak from Monash University’s Department of Materials Science and Engineering has created perovskite cells with a conversion efficiency of 15.5 percent that allows more than 20 percent of visible light through, a press release states.
This improves the stability of solar windows while allowing more natural light in, which means the amount of visible light passing through the cells is remarkably now reaching glazing levels, increasing their potential for usage in a wide range of real-world applications.
It’s effectively a new data set that will fuel the second wave of discoveries about Mars’ surface composition.
But while it was doing that work, it was also gathering lower-resolution mapping strips, about 83,000 of them. Now that CRISM is no longer active, the team is building their map from those strips.
Processing this much data into one cohesive map is a complicated task requiring powerful computing resources. It takes time to optimize the maps and account for environmental conditions and discrepancies between the different images.
“For an individual tile, the optimization process might take just five hours in some exceptional cases, but sometimes it will take over a day,” said CRISM team member Katie Hancock, a software developer at APL who spearheaded the development of the optimization code. In a press release from JH/UAPL, Hancock said that it could take a computer cluster a month to build the map of the entire planet.
