Lifeboat Foundation

An alert pops up in your email: The latest spacecraft observations are ready. You now have 24 hours to scour 84 hours-worth of data, selecting the most promising split-second moments you can find. The data points you choose, depending on how you rank them, will download from the spacecraft in the highest possible resolution; researchers may spend months analyzing them. Everything else will be overwritten like it was never collected at all.

These are the stakes facing the Scientist in the Loop, one of the most important roles on the Magnetospheric Multiscale, or MMS, mission team. Seventy-three volunteers share the responsibility, working weeklong shifts at a time to ensure the very best data makes it to the ground. It takes a keen and meticulous eye, which is why it’s always been left to a carefully-trained human – at least until now.

A paper published recently in Frontiers in Astronomy and Space Sciences describes the first artificial intelligence algorithm to lend the Scientist in the Loop a (virtual) hand.

Fifty years of Moore’s law scaling in microelectronics have brought remarkable opportunities for the rapidly evolving field of microscopic robotics^1,2,3,4,5. Electronic, magnetic and optical systems now offer an unprecedented combination of complexity, small size and low cost^6,7, and could be readily appropriated for robots that are smaller than the resolution limit of human vision (less than a hundred micrometres)^8,9,10,11. However, a major roadblock exists: there is no micrometre-scale actuator system that seamlessly integrates with semiconductor processing and responds to standard electronic control signals. Here we overcome this barrier by developing a new class of voltage-controllable electrochemical actuators that operate at low voltages (200 microvolts), low power (10 nanowatts) and are completely compatible with silicon processing. To demonstrate their potential, we develop lithographic fabrication-and-release protocols to prototype sub-hundred-micrometre walking robots. Every step in this process is performed in parallel, allowing us to produce over one million robots per four-inch wafer. These results are an important advance towards mass-manufactured, silicon-based, functional robots that are too small to be resolved by the naked eye.

Artificial Intelligence research is making big strides. But in practice?

There are several buckets you can use to categorize AI, one of which is the BS bucket. Within, you’ll find simple statistical algorithms people have been using forever. But there’s another bucket of things that actually weren’t possible a decade ago.

“The vast majority of businesses are still in the early phases of collecting and using data. Most companies looking for data scientists are looking for people to collect, manage, and calculate basic statistics over normal business processes.”

Continue reading “AI in the enterprise: Prepare to be disappointed – oversold but under appreciated, it can help… just not too much” »

The quadrupedal robots secured the perimeter of a base during a recent test of the USAF’s Advanced Battle Management System.

Extremely energy-efficient artificial intelligence is now closer to reality after a study by UCL researchers found a way to improve the accuracy of a brain-inspired computing system.

The system, which uses memristors to create artificial neural networks, is at least 1,000 times more energy efficient than conventional transistor-based AI hardware, but has until now been more prone to error.

Existing AI is extremely energy-intensive — training one AI model can generate 284 tonnes of carbon dioxide, equivalent to the lifetime emissions of five cars. Replacing the transistors that make up all digital devices with memristors, a novel electronic device first built in 2008, could reduce this to a fraction of a tonne of carbon dioxide — equivalent to emissions generated in an afternoon’s drive.

A Camcopter S-100 drone made the first commercial drone delivery to an offshore oil platform in late August and it might be the beginning of a major industry. The helicopter drone flew a 3D printed part from Norway to a rig located about 60 miles off the coast. The flight was conducted without any special airspace adjustments and the drone was just part of the traffic servicing the oil fields. The drone also did an exterior inspection of the drilling platform and performed a simulated search and rescue drill with the rig’s standby vessel.

Of course, the oil companies are keeping a close eye on the drone developments because hauling freight and supplies to the rigs by drone could not only be a lot cheaper, but also safer. There are also several major helicopter companies that have oilfield supply as their core business watching the new initiatives. Servicing oil platforms is a multibillion-dollar business and also one of the most dangerous forms of commercial flying. Nordic Unmanned, which flew the first drone flight, says drones are a viable alternative to many missions now flown by big, expensive helicopters. “This marks the beginning of a new chapter within unmanned logistics,” spokesman Pål Kristensen said.” The technology is proven and robust enough to implement in large scale and reduces the risk cost and environmental footprint drastically.”

Autonomous vessels may offer solution to pandemic struggles.

As cybercrime is becoming more lucrative and more automated, we’re going to have to depend on automated defenses on the other side.

Once you graduate beyond development boards like the Arduino or Wemos D1, you’ll find yourself in the market for a dedicated programmer. In most cases, your needs can be met with a cheap USB to serial adapter that’s not much bigger than a flash drive. The only downside is that you’ve got to manually wire it up to your microcontroller of choice.

Unless you’re [Roey Benamotz], that is. He’s recently created the LEan Mean Programming mAchine (LEMPA), an add-on board for the Raspberry Pi that includes all the sockets, jumpers, and indicator LEDs you need to successfully flash a whole suite of popular MCUs. What’s more, he’s written a Python tool that handles all the nuances of getting the firmware written out.

Continue reading “Turning The Raspberry Pi Into A MCU Programmer” »