Lifeboat Foundation

This AI can JUDGE how attractive you are and more… and it could be a dangerous sign of things to come.

The World Economic Forum suggests we are on the cusp of a Fourth Industrial Revolution driven by ‘ubiquitous automation, big data and artificial intelligence’. The Institute for Public Policy Research, however, says that “despite the growing capability of robots and artificial intelligence (AI), we are not on the cusp of a ‘post-human’ economy.”

IPPR suggests that an estimated 60 percent of occupations have at least 30 percent of activities which could be automated with already-proven technologies. As tasks are automated, work is likely to be redefined, focusing on areas of human comparative advantage over machines.

The CIPD point out that “new technology has changed many more jobs than it has destroyed, and it does not destroy work. Overall, the biggest advanced industrialized economies have between them created over 50 million jobs, a rise of nearly 20 percent, over the past 20 years despite huge economic and technological disruptions.”

Researchers make significant progress toward proving a critical mathematical test of the theory of general relativity.

• By Kevin Hartnett, Quanta Magazine on August 27, 2018

If you’ve ever experienced jet lag, you are familiar with your circadian rhythm, which manages nearly all aspects of metabolism, from sleep-wake cycles to body temperature to digestion. Every cell in the body has a circadian clock, but researchers were unclear about how networks of cells connect with each other over time and how those time-varying connections impact network functions.

In research published Aug. 27 in PNAS, researchers at Washington University in St. Louis and collaborating institutions developed a unified, data-driven computational approach to infer and reveal these connections in biological and chemical oscillatory networks, known as the topology of these complex networks, based on their time-series data. Once they establish the topology, they can infer how the agents, or cells, in the network work together in synchrony, an important state for the brain. Abnormal synchrony has been linked to a variety of brain disorders, such as epilepsy, Alzheimer’s disease and Parkinson’s disease.

Jr-Shin Li, professor of systems science & mathematics and an applied mathematician in the School of Engineering & Applied Science, developed an algorithm, called the ICON (infer connections of networks) method, that shows for the first time the strength of these connections over time. Previously, researchers could only determine whether a connection existed between networks.

The algorithm is saving about $10 million as part of an effort to replace the city’s water infrastructure.

To catch you up: In 2014, Flint began getting water from Flint River rather than the Detroit water system. Mistreatment of the new water supply, combined with old lead pipes, created contaminated water for residents.

Solving the problem: Records that could be used to figure out which houses might be affected by corroded old pipes were missing or incomplete. So the city turned to AI. Using 71 different pieces of information—like the age or value of the home—Georgia Tech researchers developed an algorithm that predicted whether or not a home was connected to lead pipes.

Continue reading “AI is helping find lead pipes in Flint, Michigan” »

One of the most significant AI milestones in history was quietly ushered into being this summer. We speak of the quest for Artificial General Intelligence (AGI), probably the most sought-after goal in the entire field of computer science. With the introduction of the Impala architecture, DeepMind, the company behind AlphaGo and AlphaZero, would seem to finally have AGI firmly in its sights.

Let’s define AGI, since it’s been used by different people to mean different things. AGI is a single intelligence or algorithm that can learn multiple tasks and exhibits positive transfer when doing so, sometimes called meta-learning. During meta-learning, the acquisition of one skill enables the learner to pick up another new skill faster because it applies some of its previous “know-how” to the new task. In other words, one learns how to learn — and can generalize that to acquiring new skills, the way humans do. This has been the holy grail of AI for a long time.

Continue reading “Artificial General Intelligence Is Here, and Impala Is Its Name” »

Level 4 – Awareness + World model: Systems that have a modeling system complex enough to create a world model: a sense of other, without a sense of self – e.g., dogs. Level 4 capabilities include static behaviors and rudimentary learned behavior.

Level 5 – Awareness + World model + Primarily subconscious self model = Sapient or Lucid: Lucidity means to be meta-aware – that is, to be aware of one’s own awareness, aware of abstractions, aware of one’s self, and therefore able to actively analyze each of these phenomena. If a given animal is meta-aware to any extent, it can therefore make lucid decisions. Level 5 capabilities include the following: The “sense of self”; Complex learned behavior; Ability to predict the future emotional states of the self (to some degree); The ability to make motivational tradeoffs.

Level 6 – Awareness + World model + Dynamic self model + Effective control of subconscious: The dynamic sense of self can expand from “the small self” (directed consciousness) to the big self (“social group dynamics”). The “self” can include features that cross barriers between biological and non-biological – e.g., features resulting from cybernetic additions, like smartphones.

Continue reading “The Transhumanist Bill of Rights version 2.0” »

Quantum computers aren’t yet practical, but Microsoft has already developed a programming language for them. Q# works inside Visual Studio, just like most other languages, and could offer aspiring programmers a chance to learn the basics of quantum physics through trial-and-error.

Engineers at Caltech have developed a new control algorithm that enables a single drone to herd an entire flock of birds away from the airspace of an airport. The algorithm is presented in a study in IEEE Transactions on Robotics.

The project was inspired by the 2009 “Miracle on the Hudson,” when US Airways Flight 1549 struck a flock of geese shortly after takeoff and pilots Chesley Sullenberger and Jeffrey Skiles were forced to land in the Hudson River off Manhattan.

“The passengers on Flight 1549 were only saved because the pilots were so skilled,” says Soon-Jo Chung, an associate professor of aerospace and Bren Scholar in the Division of Engineering and Applied Science as well as a JPL research scientist, and the principal investigator on the drone herding project. “It made me think that next time might not have such a happy ending. So I started looking into ways to protect airspace from birds by leveraging my research areas in autonomy and robotics.”

Continue reading “Engineers teach a drone to herd birds away from airports autonomously” »