Lifeboat Foundation

Scientists created an AI that can detect someone’s race from their x-rays with over 90% accuracy. Problem is, they don’t know how it works.

The long term goal for Elon Musk and brain to computer interfaces (brain chips) is to merge our minds with artificial intelligence. While the short term goal for Neuralink and other companies is to help people with medical issues.

This short documentary video takes a look at connecting our brains to computers, and how this works is explained. We also take a look at the downsides of people connecting their brains, the technology being used today, and Elon Musk’s thoughts.

Continue reading “Uploading Memories: Elon Musk’s Brain Chip (Neuralink Future Technology)” »

Showcasing my finalist entry in the Future of Life Institute’s AI worldbuilding competition.

Researchers at the Stevens Institute of Technology used a customized BlueROV2 robot to explore a busy harbor at the U.S. Merchant Marine Academy in New York. | Source: Stevens Institute of Technology.

Underwater environments can be particularly challenging for autonomous robots. Things are constantly moving and changing, and robots need to figure out where they are without relying on GPS data.

Researchers at the Stevens Institute of Technology have created a robot that is able to successfully navigate a crowded marina underwater. The robot is able to map its environment, track its own location and plan a safe route through a complex environment in real-time, simultaneously.

The Boston Dynamics founder behind the popular Spot and Stretch robots makes robotics look easy. He’s #26 on the list.

Tech Power Players 50

Now it’s time to tackle something almost as challenging, and perhaps more profitable — unloading trucks.

Continue reading “Marc Raibert, master of robotics, is making machines smarter — and more useful” »

Researchers at the Department of Energy’s Oak Ridge National Laboratory are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.

“There are so many potential materials, some of which we cannot study at all with conventional tools, that need more efficient and systematic approaches to design and synthesize,” said Maxim Ziatdinov of ORNL’s Computational Sciences and Engineering Division and the CNMS. “We can use smart automation to access unexplored materials as well as create a shareable, reproducible path to discoveries that have not previously been possible.”

The approach, published in Nature Machine Intelligence, combines physics and machine learning to automate microscopy experiments designed to study materials’ functional properties at the nanoscale.

Adam FordAdmin.

I’m sure that’s not Deepmind’s official position atm — Nando de Freitas’s tweet was probably reactionary.

Nikolai Torp DragnesDoesn’t really read like the AGI is in a happy comfortable place does it? “Big red button,” “agents,” etc.? Sounds more like being locked in a cage with a gun to your head told to behave, told what to think, what to feel, what to do and what to look a… See more.

Continue reading “Nanopatterning electronic properties of twisted 2-D semiconductors using twist” »

Massive earthquakes don’t just move the ground — they make speed-of-light adjustments to Earth’s gravitational field. Now, researchers have trained computers to identify these tiny gravitational signals, demonstrating how the signals can be used to mark the location and size of a strong quake almost instantaneously.

It’s a first step to creating a very early warning system for the planet’s most powerful quakes, scientists report May 11 in Nature.

Such a system could help solve a thorny problem in seismology: how to quickly pin down the true magnitude of a massive quake immediately after it happens, says Andrea Licciardi, a geophysicist at the Université Côte d’Azur in Nice, France. Without that ability, it’s much harder to swiftly and effectively issue hazard warnings that could save lives.

Google recently announced a new model for automatically generating summaries using machine learning, released in Google Docs that you can already use.

The model will try to understand the whole document and generate a short summary of the piece—something some movie professionals clearly still can’t do.

Continue reading “Google’s New AI Creates Summaries of Your Documents in Google Docs” »