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At CES 2022, Tech Companies Tried to Pitch Climate Sustainability as Fun and Exciting

TIME - Tech

Between presentations launching new PC processors and candy-colored refrigerators at last week's CES, companies at the annual tech industry jamboree made a lot of big, flashy proclamations about climate change, some more serious than others, and most seeming to include at least one stock video clip of trees, solar panels and children frolicking in grassy meadows or on pristine beaches. General Motors unveiled a new zero-emission pickup truck and dropped hints about new EV models to come, while Panasonic, which calculated that it released 110 million tons of CO2 per year and accounted for 1% of global electricity consumption, reiterated a pledge to decarbonize its operations by 2030 and promised to make its products more efficient. LG--which has pledged carbon neutrality by 2030, and to use fully renewable power by 2050--rolled out glass-fronted refrigerators (to avoid wasting energy while you look inside) and washing machines that use AI to shorten wash cycles. Samsung, whose CO2 emissions actually rose in 2020, and which has faced controversy over its reliance on coal energy, offered promises like devices that would use less standby power, which some environmentalists criticized as greenwashing. A version of this story first appeared in the Climate is Everything newsletter. To sign up, click here.


Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


On the Opportunities and Risks of Foundation Models

arXiv.org Artificial Intelligence

AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically central yet incomplete character. This report provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e.g., model architectures, training procedures, data, systems, security, evaluation, theory) to their applications (e.g., law, healthcare, education) and societal impact (e.g., inequity, misuse, economic and environmental impact, legal and ethical considerations). Though foundation models are based on standard deep learning and transfer learning, their scale results in new emergent capabilities,and their effectiveness across so many tasks incentivizes homogenization. Homogenization provides powerful leverage but demands caution, as the defects of the foundation model are inherited by all the adapted models downstream. Despite the impending widespread deployment of foundation models, we currently lack a clear understanding of how they work, when they fail, and what they are even capable of due to their emergent properties. To tackle these questions, we believe much of the critical research on foundation models will require deep interdisciplinary collaboration commensurate with their fundamentally sociotechnical nature.


Facebook AI boss Yann LeCun goes off in Twitter rant, blames talk radio for hate content

#artificialintelligence

Yann LeCun, Facebook's world-renowned AI guru, had some problems with an article written about his company yesterday. So he did what any of us would do, he went on social media to air his grievances. Only, he didn't take the fight to Facebook as you'd expect. Instead, over a period of hours, he engaged in a back-and-forth with numerous people on Twitter. Apparently, one can write about AI fairness without paying attention to journalistic fairness.


How AI is leading the way on transport tech

#artificialintelligence

For Rolls-Royce, the world's second largest manufacturer of aero engines and a company with a distinguished history of pioneering R&D, technology strategy is all about the play-off between optimising existing products and simultaneously leading the charge on developing the low carbon power systems of the future. "The most pressing issue is how to get the right balance between new technology-led opportunities and existing product evolution," says the firm's chief technology officer, Paul Stein. "People will still be buying gas turbines [conventional aero engines] for the next 40 or 50 years, so we have to make sure we keep those products competitive for the long term. But we also have to free up as many resources as we can for driving productivity and for investing in the new." Stein explains how technologies such as digitisation and AI are already paying big dividends in design and operational efficiency.


73 Mind-Blowing Implications of a Driverless Future

#artificialintelligence

I originally wrote and published a version of this article in September 2016. Since then, quite a bit has happened, further cementing my view that these changes are coming and that the implications will be even more substantial. I decided it was time to update this article with some additional ideas and a few changes.


73 Mind-Blowing Implications of a Driverless Future

#artificialintelligence

I originally wrote and published a version of this article in September 2016. Since then, quite a bit has happened, further cementing my view that these changes are coming and that the implications will be even more substantial. I decided it was time to update this article with some additional ideas and a few changes.


Renault-Nissan developing a fleet of self-driving EVs

Engadget

French people love to drive, but with private radar companies set to give out way more speeding tickets, they may be willing to let machines take the wheel. Luckily, the Renault-Nissan Alliance has teamed with a company called Transdev to develop a fleet of self-driving vehicles "for future public and on-demand transportation," it said in a press release. The project will kick off with autonomous field testing of Europe's most popular EV, the 250-mile-range Renault Zoe. Transdev, which will supply the self-driving and logistics tech, recently launched what it claims is the "world's first" fully autonomous fleet to run on an industrial site. Its systems are used on the "Navya Arma" vehicles, shuttling employees around EDF nuclear power stations every five minutes.