Lifeboat Foundation

A common concern surrounding automation in recent years is that it will result in widescale job losses as the work previously done by people is taken over by technology. Of course, the reality doesn’t really support this narrative, and indeed, companies that invest in technology often end up employing more people as a result of the improvement in their fortunes heralded by the investment.

The leadership team of the fintech company Kashat highlight the reality of investing in technology. They reveal that microfinance has traditionally been highly labor intensive, with many of the skills the same as those used in the sector for years. With the introduction of AI, new skills have been introduced into the underwriting process in order to serve at scale, while enabling employees to further expand their skillset and become even more valuable in the future.

The impact of this distinction is clearly visible in the growth rates across the sector, with those more tech-enabled firms growing far faster, and therefore employing more people, than their more traditional peers.

Last week saw an announcement that Optimus Ride, an autonomous shuttle company in Boston was purchased in an acqui-hire by Magna, the Ontario based Tier One Automotive company. In an acqui-hire, the company has generally failed, but a buyer pays to pick up the assets and to hire the team, which took time to create. Usually it’s only enough to reward the preferred investors, the team gets options in their new employer.

Optimus Ride built a shuttle on top of the GEM 6-seater electric shuttle platform, adding sensors and their autonomy tools. It evolved out of MIT.

Also announced as shutting its doors was Local Motors, maker of the Olli shuttle. Local Motors began with a focus on 3D printing to make smaller volume vehicles. The started with the Rally Fighter, a vehicle that was crowd designed after contests. Over time, founder Jay Rogers believed that 3D printing could bring a vehicle to production faster and at lower cost than conventional methods than conventional methods, and entered the Shuttle market, partnering with various partners to make them autonomous. Recently, we reported how an Olli shuttle in Whitby, Ontario had a crash resulting in serious injuries. Early reports suggested it was in autonomous mode, but it was later revealed it was being manually driven at the time. That made it mostly a non-story, but the real story of Olli did not go so well, either.

Continue reading “Two Self-Driving Shuttle Companies Fail In One Week. What Does It Bode?” »

Kawasaki has shoehorned the supercharged 1,000cc engine from its wild H2R hyperbike into a heavy-lift autonomous cargo helicopter, and has now demonstrated a robotic system for loading and unloading it without exposing humans to those big blades.

The K-Racer X1 is a beast of a drone, roughly the size of a small car. It rises vertically on a helicopter-style top rotor, but where there’s normally a tail rotor to balance out torque, this machine uses two forward-facing props mounted at the end of stubby wings. These props double as forward propulsion, with the wings providing some lift.

Continue reading “Kawasaki’s supercharged cargo copter tests robotic ground crew” »

Poor Artificial Intelligence (AI). For years, it has had to sit there (like a dormant Skynet) listening to its existence being debated, without getting to have a say. A recent debate held at the University of Oxford tried to put that right by including an AI participant in a debate on the topic of whether AI can ever be ethical.

The debate involved human participants, as well as the Megatron Transformer, an AI created by the Applied Deep Research team at computer-chip maker Nvidia. The Megatron has been trained on a dataset called “the pile”, which includes the whole of Wikipedia, 63 million English news articles, and 38 gigabytes of Reddit conversations — more than enough to break the mind of any human forced to do likewise.

“In other words, the Megatron is trained on more written material than any of us could reasonably expect to digest in a lifetime,” Oxford’s Professor Andrew Stephen wrote in a piece on the debate published in The Conversation. “After such extensive research, it forms its own views.”

Billionaire Mukesh Ambani’s Reliance Industries Ltd. is buying an Indian robotics startup as the conglomerate scales up automation across its businesses, from e-commerce to new energy.

This is lecture 3 of course 6.S094: Deep Learning for Self-Driving Cars taught in Winter 2017. This lecture introduces computer vision, convolutional neural networks, and end-to-end learning of the driving task.

INFO:
Slides: http://bit.ly/2HdXYvf.
Website: https://deeplearning.mit.edu.
GitHub: https://github.com/lexfridman/mit-deep-learning.
Playlist: https://goo.gl/SLCb1y.

Continue reading “MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task” »

Part of the End-to-End Machine Learning School Course 193, How Neural Networks Work at https://e2eml.school/193

Slides: https://docs.google.com/presentation/d/1R-DnrghbU36jO8X4scbr…sp=sharing.
machine learning blog: https://brohrer.github.io/blog.html

SEOUL — Using a high-performance artificial intelligence (AI) chip, South Korean researchers have established a system that can accelerate the process of learning data and yielding results. The system capable of performing five thousand trillion operations per second is ideal for autonomous vehicles and AI servers because its chipset is about the size of a coin.

One possible application of interest to researchers is bone healing. The idea is that the soft material, powered by the electroactive polymer, will be able to maneuver in spaces of complicated bone fractures and expand. When the material hardens, it can form the basis for building new bones. In their study, the researchers demonstrate that the material can wrap itself around chicken bones, and the artificial bone that develops later grows along with the animal’s bone. The developed biohybrid variable-stiffness actuators can be used in soft (micro-)robotics and as potential tools for bone repair or bone tissue engineering.

“By controlling how the material turns, we can make the microrobot move in different ways, and also affect how the material unfurls in broken bones. We can embed these movements into the material’s structure, making complex programs for steering these robots unnecessary”, says Edwin Jager.