Lifeboat Foundation

An amazing aspect of living in The Fourth Industrial Era is that we are at a new inflection point in bringing emerging technologies to life. We are in an era of scientific breakthroughs that will change the way of life as we currently know it. While there are many technological areas of fascination for me, the meshing of biology with machine is one of the most intriguing. It fuses many elements of technologies especially artificial intelligence and pervasive computing. I have highlighted two frontiers of “mind-bending” developments that are on the horizon, Neuromorphic technologies, and human-machine biology.

Neuromorphic Technologies

Human computer interaction (HCI) was an area of research that started in the 1980s and has come a long way in a short period of time. HCI was the foundation for what we call neuromorphic computing, the integration of systems containing electronic analog circuits to mimic neuro-biological architectures present in the biological nervous system.

Reliable Robotics, a startup developing autonomous flight technologies, this week emerged from stealth with $33.5 million in venture capital funding. Cofounder and CEO Robert Rose says the funds will be used to scale production of the company’s products and bring on new engineering talent.

Aviation companies pursuing autonomous transportation include Uber, Boeing, and Honeywell. According to management consulting firm Oliver Wyman, replacing single-pilot operations with autonomous planes could save airlines as much as $60 billion annually. Pandemic headwinds have only reinvigorated the search for cost-cutting opportunities, as Statista estimates airlines will lose at least $314 billion in revenue in 2020.

Looking to expedite their path to market, companies like Xwing, Airbus, and Elroy Air have explored retrofitting existing aircraft rather than developing hardware from scratch. Reliable Robotics, which was founded in 2017 by Rose and VP of engineering Juerg Frefel, aims to develop a platform that imbues any fixed-wing plane with autonomous capabilities.

Robot vending machines designed specifically for pizza is the future we need right now.

Accurate computational prediction of chemical processes from the quantum mechanical laws that govern them is a tool that can unlock new frontiers in chemistry, improving a wide variety of industries. Unfortunately, the exact solution of quantum chemical equations for all but the smallest systems remains out of reach for modern classical computers, due to the exponential scaling in the number and statistics of quantum variables. However, by using a quantum computer, which by its very nature takes advantage of unique quantum mechanical properties to handle calculations intractable to its classical counterpart, simulations of complex chemical processes can be achieved. While today’s quantum computers are powerful enough for a clear computational advantage at some tasks, it is an open question whether such devices can be used to accelerate our current quantum chemistry simulation techniques.

In “Hartree-Fock on a Superconducting Qubit Quantum Computer”, appearing today in Science, the Google AI Quantum team explores this complex question by performing the largest chemical simulation performed on a quantum computer to date. In our experiment, we used a noise-robust variational quantum eigensolver (VQE) to directly simulate a chemical mechanism via a quantum algorithm. Though the calculation focused on the Hartree-Fock approximation of a real chemical system, it was twice as large as previous chemistry calculations on a quantum computer, and contained ten times as many quantum gate operations. Importantly, we validate that algorithms being developed for currently available quantum computers can achieve the precision required for experimental predictions, revealing pathways towards realistic simulations of quantum chemical systems.

AI tools are shaping next-generation theorem provers, and with them the relationship between math and machine.

Reliable Robotics, created by two Space X veterans, plans unmanned air cargo deliveries within two years.

An Artificial Intelligence (AI) produced DeepFake video could show Donald Trump saying or doing something extremely outrageous and inflammatory – just imagine that! Crazy I know, and some people might find it believable and in a worst case scenario it might sway an election, trigger violence in the streets, or spark an international armed conflict.

WHY THIS MATTERS IN BRIEF We are now locked in a war as nefarious actors find new ways to weaponsise deepfakes and fake news, and defenders try to figure out how to discover and flag it. Interested in the Exponential Future? Connect, download a free E-Book, watch a keynote, or browse my.

Continue reading “World leaders can rest easy for now after researchers find new ways to reveal DeepFakes” »

YouTube says it took down a record number of videos in the second quarter of this year due to an increased use of AI in its content review efforts.

In total, 10.85 million of the 11.4 million videos removed from the platform between April and June were flagged by automated systems, according to YouTube‘s latest Community Guidelines Enforcement Report.

AI played an even bigger role in the removal of user comments. Of the 2.1 million comments taken down, 99.2% were detected by automated systems.

For Dr. Cecily Morrison, research into how AI can help people who are blind or visually disabled is deeply personal. It’s not only that the Microsoft Principal Researcher has a 7-year-old son who is blind, she also believes that the powerful AI-related technologies that will help people must themselves be personal, tailored to the circumstances and abilities of the people they support.

We will see new AI techniques that will enable users to personalize experiences for themselves,” says Dr. Morrison, who is based at Microsoft Research Cambridge and whose work is centered on human-computer interaction and artificial intelligence. “Everyone is different. Having a disability label does not mean a person has the same needs as another with the same label. New techniques will allow people to teach AI technologies about their information needs with just a few examples in order to get a personalized experience suited to their particular needs. Tech will become about personal needs rather than disability labels.”