Collaborating Authors


What can we learn from a new documentary on Elon Musk?

The Guardian

You could be forgiven for believing that we've already achieved the era of autonomous vehicles. Tesla, the electric car manufacturer run by Elon Musk, refers to a version of its Autopilot software as "Full Self Driving". The company released a (misleadingly edited) video of an autonomous vehicle navigating city streets, its drivers' hands on their lap – a style replicated by enthusiasts. Musk has repeatedly assured in speeches and interviews that autonomous vehicles were one to two years away – or, as he put it in 2015, a "solved problem" because "we know what to do and we'll be there in a few years." But the existing Autopilot technology has not yet realized those promises and, as a new New York Times documentary illustrates, the gap in expectation and reality has led to several deadly crashes.

Python: Master Machine Learning with Python: 3-in-1


You are a data scientist. Every day, you stare at reams of data trying to apply the latest and brightest of models to uncover new insights, but there seems to be an endless supply of obstacles. Your colleagues depend on you to monetize your firm's data - and the clock is ticking. Troubleshooting Python Machine Learning is the answer. Machine learning gives you powerful insights into data.

Machine Learning


In the era of Big Data, machine learning and data analytics are vital to the success of any organisation. From simple sales forecasts to the AI behind self-driving cars, data are helping to drive continuous improvement. The techniques are powerful, but need to be used with a full understanding of the subject. It is vital to understand best practice, and how an analytics project fits with the business objectives. This is a technical course, but it also has a very applied focus.

Resonance as a Design Strategy for AI and Social Robots


Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human–robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of “sympathetic resonance” as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human–robot interactions.

Explorations in Cyber-Physical Systems Education

Communications of the ACM

The field of CPS draws from several areas in computer science, electrical engineering, and other engineering disciplines, including computer architecture, embedded systems, programming languages, software engineering, real-time systems, operating systems and networking, formal methods, algorithms, computation theory, control theory, signal processing, robotics, sensors and actuators, and computer security. Similarly, over the past 14 years, we have had students from computer science, electrical and computer engineering, mechanical engineering, civil engineering, and even bioengineering. Integrating this bewildering diversity of subject areas into a coherent whole for students with such a wide breadth of backgrounds has been a challenge we had to overcome. One approach would have been to not attempt such an integration. Instead, we could have opted for a collection of courses that together cover all the key areas in CPS.

Data Science: Supervised Machine Learning in Python


In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

"HAI 2.0" – NPS Releases Updated Artificial Intelligence Course, Video Series


Early AI began with a variety of tasks such as checkers and chess, speech recognition, language translation, and solving word problems. Over the years it has progressed to give us automated vacuum cleaners, robot dogs, Siri and Alexa, image recognizers, Chess and Go world masters, self-driving cars, and self-guided drones. These technologies have powerful impacts on Naval operations and warfighting as well. AI has the potential to revolutionize military technology, capability and operations. The possibilities have raised many speculations about what AI is capable of and whether it can be trusted.

What are the most in-demand jobs in automation, AI and RPA?


Automation is one of the most rapidly growing job markets right now, incorporating artificial intelligence (AI), machine learning and robotic process automation (RPA). Businesses are realising the untapped potential of intelligent automation. As more adopt automation, those that do not are becoming less productive and will likely be left behind. An awareness of the value of automation is nothing new, but the boom in demand is largely driven by a need for greater efficiency, rapid deployment and scalability. According to Deloitte's 2020 survey, two-thirds of organisations surveyed also note the Covid-19 pandemic's role in accelerating demand for automation.

Learn AI for Free: Top No-Paid Courses to Take Up in 2022


In today's digital world you don't have to take years out of your life studying at university to become familiar with this seemingly complex technology. You will get everything online. And you can learn these courses for free also. AI is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment. Taught by the top researchers and educationists of the best universities globally, these artificial intelligence courses are worth taking up.

Will a robot take my job?


"Computers are able to see,hear and learn.Welcome to the future." According to the World Economic Forum,more than 65% of students will work in jobs that don't even exist today.We want to help prepare them for that future by getting them excited about what computer science (CS) can take them.With a focus on girls and others who are underrepresented in the field today. Robotics and automation are dramatically reshaping the global economy.From delivering faster customer service to better quality products and efficient operations, robotics and automation provide enormous value for organizations that adopt them at scale. "Robots and automation will take 800 million jobs by 2030."-McKinsey.Using AI, the company hopes to teach the robot to copy human movements automatically, so that it can operate without a pilot. From the initially reported outbreak of coronavirus (COVID-19) in China to the spread of it across the globe, Medtech companies are rolling out robots and drones to help fight it and provide services and care to those quarantined or practicing social distancing. This pandemic has fast-tracked the "testing" of robots and drones in public as officials seek out the most expedient and safe way to grapple with the outbreak and limit contamination and spread of the virus.