Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. We also dive into a general framework for machine ethics, contractarianism, Rawls' original position thought experiment (which is one of my favourite ethical thought experiments), maximin function approach to machine ethics, and whether robots should respect the consent of a person in life threatening circumstances… Derek Leben is Associate Professor of Philosophy at the University of Pittsburgh, Johnstown. He works at the intersection of ethics, cognitive science, and emerging technologies. In his book, Ethics for Robots, Leben argues for the use of a particular moral framework for designing autonomous systems based on the Contractarianism of John Rawls. He also demonstrates how this framework can be productively applied to autonomous vehicles, medical technologies, and weapons systems.
'The show must go on,' an often heard sentence that makes absolute sense in the pandemic hit the world. Yes, it all became at the end of 2019 when Covid-19 was first reported in Wuhan. Later, the virus spread across the globe and pushed governments to impose strict lockdowns. An international sports event that was supposed to take place in 2020 got delayed and finally, when people started living with the virus in 2021, the IOC and Japan, the host country, came forward to go on with it. One of the most welcomed guests in the summer Tokyo Olympics is artificial intelligence.
And far from being a futuristic idea, the first steps towards autonomous vehicles are already here. Self-driving vehicles are to be allowed on UK roads by the end of this year, according to the Department for Transport. Automated lane-keeping systems would be the first type of hands-free driving legalised, using technology which controls the position and speed of a car in a single lane and limited to 37mph. Such an innovation doesn't sound like it is going to impact much, beyond making short parts of a journey less stressful for drivers with the technology, but it is a big step towards the fully autonomous driving which could change our lives in almost every way – with driverless vehicles roaming the country, picking up passengers on demand and negating the need for individuals to drive, park or even own their own car. Such a system, which could certainly start to be introduced in the next decade, will change an awful lot in the world of residential real estate too.
We're excited to announce that Plainsight is now on Google Cloud MarketPlace! Derek Muller (a.k.a Veritasium) explores why how close we are to having fully autonomous vehicles become mainstream on the roads, and if they're safer than human driven vehicles. This video shows Waymo's (Google's) self-driving car progress and brings up some great questions about the future of the self-driving industry. NVIDIA's new Alias free GAN is capable of generating much more realistic looking faces not only in images but also in videos by better handling complex textures! Check out the video below or read the paper and see more examples here.
Marshall Worth, senior project manager AI at PowerSecure, discusses artificial intelligence and a practical approach that microgrid customers can take today to achieve their energy goals of the future. "Alexa, reduce my energy costs!" With as fast as technology has progressed over the last decade, and with the promise of self-driving cars on the horizon and the electrification of everything, it's only natural to question when this is all going to filter into our everyday, energy consuming lives. In this device-driven age, shouldn't we already have the artificial intelligence (AI) capabilities to reduce our carbon footprint today and our energy bill tomorrow? Those of us who work in the energy industry are fortunate; we are naturally driven to innovate and build the future of energy.
AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career. CS50's Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs.
Honda Motor Co. has boosted its operating income forecast for the full year but gave guidance that missed analyst estimates, leaving investors disappointed as the automaker embarks on an ambitious plan to go all electric by 2040 and make highly autonomous cars a reality. Operating income for the 12 months ending March should touch ¥780 billion ($7.1 billion), up from previous expectations for ¥660 billion, Honda said in a filing Wednesday. Analysts had been looking for around ¥803 billion. For the first quarter ended June, Honda reported operating income of ¥243.2 billion -- more than double the average analyst estimate of ¥100.8 billion. Despite spending heavily on research and development, Honda's high-tech plans haven't borne much fruit.
Inceptio Technology, a China-based developer of autonomous trucking technology, raised a $270 million Series B round of funding. Inceptio said the funding will allow it to accelerate the development of its full-stack autonomous driving system called "Xuanyuan" and speed up its deployment in electrification. Inceptio, which was founded in 2018, has raised approximately $490 million to date. It raised a $100 million Series A round in April 2020, followed by an additional $100 million in November 2020. The Series B round was led by JD Logistics, Meituan, and PAG.
We enjoyed messing around with the games, but pretty quickly our mind wandered to what these things can do. VR is still a young space, and you quite frequently find yourself wanting an app that doesn't exist. At the top of our list: Could you view the world through a drone's camera while you flew it? We'd taken a few AI courses in the past, and we thought that single camera 3D VR might just be possible. In the world of autonomous vehicles, there is similar work underway in the form of research into "Pseudo-LIDAR".
AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner What is the Mother Idea of All Ideas, Concepts, Rules, Laws or Algorithms? All in all, the idea of all ideas, the rule of all rules, or the law of all laws, the algorithms of all algorithms, or the Mother Discovery is certainly the concept of causality and causation as the real, circular, or reversible causality with the interactive causation, governing the causal order of the world and all its regions, domains and fields. The Six Layer Causal Hierarchy defines the Ladder of Reality, Causality and Mentality, Science and Technology, Human Intelligence and Non-Human Intelligence (MI or AI). The Causal World [levels of causation] is a basis for all real world constructs, as power, force and interactions, agents and substances, states and conditions and situations, events, actions and changes, processes and relations; causality and causation, causal models, causal systems, causal processes, causal mechanisms, causal patterns, causal data or information, causal codes, programs, algorithms, causal analysis, causal reasoning, causal inference, or causal graphs (path diagrams, causal Bayesian networks or DAGs). CAUSALITY AND GLOBAL ARTIFICIAL INTELLIGENCE We need a unifying model of reality/world in terms of causality/actuality, mentality/intelligence and computing/data /virtuality/cyberspace, where neural networks are brain-encoded causal networks.