It took a few moments to realize what was striking about the opening video for Nvidia's GTC conference: the complete absence of humans. That the video ended with Jensen Huang, the founder and CEO of Nvidia, is the exception that accentuates the takeaway. On the one hand, the theme of Huang's keynote was the idea of AI creating AI via machine learning; he called the idea "intelligence manufacting": None of these capabilities were remotely possible a decade ago. Accelerated computing, at data center scale, and combined with machine learning, has sped up computing by a million-x. Accelerated computing has enabled revolutionary AI models like the transformer, and made self-supervised learning possible. AI has fundamentally changed what software can make, and how you make software. Companies are processing and refining their data, making AI software, becoming intelligence manufacturers. Their data centers are becoming AI factories. The first wave of AI learned perception and inference, like recognizing images, understanding speech, recommending a video, or an item to buy. The next wave of AI is robotics: AI planning actions. Digital robots, avatars, and physical robots will perceive, plan, and act, and just as AI frameworks like TensorFlow and PyTorch have become integral to AI software, Omniverse will be essential to making robotics software. Omniverse will enable the next wave of AI. We will talk about the next million-x, and other dynamics shaping our industry, this GTC. Over the past decade, Nvidia-accelerated computing delivered a million-x speed-up in AI, and started the modern AI revolution. Now AI will revolutionize all industries. The CUDA libraries, the Nvidia SDKs, are at the heart of accelerated computing. With each new SDK, new science, new applications, and new industries can tap into the power of Nvidia computing.

Colored figures are available in the online version at https://link.springer.com/journal/11633 Yong Rui received the B. Sc. degree in electrical engineering from Southeast University, China in 1991, the M. Sc. degree in electrical engineering from Tsinghua University, China in 1994, and the Ph. He is currently the Chief Technology Officer and Senior Vice President of Lenovo Group, China. He is a Fellow of ACM, IEEE, IAPR, China SPIE, CCF and CAAI, and a Foreign Member of Academia Europaea. He holds 70 patents, and is the recipient of the prestigious 2018 ACM SIGMM Technical Achievement Award and 2016 IEEE Computer Society Edward J. McCluskey Technical Achievement Award.

The conversation is on hold. The Edge community has hit the road... or they're staying home. Preparing for the academic year to begin, wrapping up projects and starting new ones, celebrating with family and friends or contemplating in solitude. After a hiatus, Edge is pleased to revive Summer Postcards: Edgies reporting in from wherever they are and on whatever they're doing, as the dog days wind out and the season comes to a close. As the world slowly returns to a "new normal" with enduring COVID restrictions in the midst of renewed vaccine freedoms, this year's collection is a testament to change (temporary and lasting), a consideration of loss (will travel ever be like it was?), and a celebration of questions (that still need answering). The hammock may be away until next year, but the memories remain. I spent the summer writing and revising the final section of a longish novel I started in 2019. It seems now as though I've been from 1946 to 2021 on my hands and knees. Various lockdowns have been a liberation from obligations and the luggage carousel, and I've never known such sweet and total focus for months on end. We have the luxury of living in the country--no shortage of big skies and moody walks. All our few breaks were in the UK--Scotland, the Lake District, the West country. Even in our remote part of the Lakes, I had to keep on writing--as in photo. The best novel I read this summer was Sandro Veronesi's The Hummingbird. Best non-fiction was Peter Godfrey Smith's Metazoa: Animal Life and the Birth of the Mind. I gave time also to some wonderful novellas--perfect fictional form for you too-busy scientists. IAN MCEWAN is a novelist whose works have earned him worldwide critical acclaim. He is the recipient of the Man Booker Prize for Amsterdam (1998), the National Book Critics' Circle Fiction Award, and the Los Angeles Times Prize for Fiction for Atonement (2003). His most recent novel is Machines Like Me. In 2019, Časlav Brukner and myself were walking on a beach on Lamma Island, near Hong Kong, marvelling together at the astonishing strangeness of quantum phenomena. This summer, the conversation with Časlav has continued on another island, and quite an island: Lesbos, the northern Greek island near the Turkish coast. Lesbos is the place where lyrical poetry was born. Here lived Sappho and Alcaeus.

How to Do It is Slate's sex advice column. Send it to Stoya and Rich here. My partner and I (man and woman in our mid-30s) want to open profiles on an adult dating site (Feeld, probably?) to connect with couples and singles. We've had ethically non-monogamous encounters at adult resorts, but haven't tried a dating site to meet people closer to home in hopes of landing on more "social swinging" relationships. There are a wealth of swinging/lifestyle podcasts with episodes about dating profiles, and omitting your face from "public" photos on the site (that is, visible to all members) is uniform advice. Of course, most often this is to avoid being identified on the site.

These are welcome and encouraging developments, but what's the next AI frontier for leaders in the business community? As I look to what 2022 will bring, I believe that we need to steer this fast-moving tech ship responsibly, even as we stay bold and brave in exploring the art of the possible. In the private sector, we can expect businesses in all areas to use AI as a vehicle to speed up the discovery of new relationships and connections, as well as to elevate the user experience. It will be put to work in back offices, proactively flagging issues and finding creative solutions to problems invisible to the human eye. We can also expect the traditional call center model of customer interactions to become the exception rather than the norm. Instead of relying on human agents, companies will shore up the might of robot armies to take care of the repetitive work and so free up valuable human resources for other tasks, and that's a positive.

In 2016, Alan Winfield gave an "IdeasLab" talk at the World Economic Forum about building ethical robots. "Could we build a moral machine?" Behind him, pictured on a flatscreen TV, was one of the bots Winfield used in his experiments--a short, cutesy, white and blue human-like machine. Just a few years ago, he said, he believed it to be impossible: You couldn't build a robot capable of acting on the basis of ethical rules. But that was before he realized what you could get robots to do if they had an imagination--or less gradiosely a "consequence engine," a simulated internal model of itself and the world outside. Winfield showed clips of his experiments at the Bristol Robotics Lab in England.

The phrase, "this emotiguy does not exist" gives you petrifying emojis that look like a warped off-brand version of Picasso's cubism era. "I think it's really fun that you can give [the machine] something that you might imagine is very vague or that you might imagine is too flowery for a machine to understand and it will still capture the essence of what you were feeling when you read the statement," King tells NYLON. "I think that's remarkable that you can give it a line of poetry and it will encapsulate the feeling of the poem, despite the poem using all sorts of simile and metaphor and analogy in its writing." Like most things on the internet, people have opinions about AI art – namely, that it isn't art. But it has an alien aesthetic of its own, one that could only be created by a human using a machine, and one that is beautiful precisely because of its randomness, not in spite of it.

The Fort Worth native died in the city where he was raised, and no cause of death was given by his wife. As an employee of Tandy in the 70s, Roach convinced RadioShack executives to sell the TRS-80, a desktop microcomputer that retailed for just under $600, in its stores nationwide. This was at a time when few complete, pre-assembled computers were on the market. The TRS-80 first hit RadioShack stores in 1977, and by 1981 became the largest-selling computer of all time, beating out Apple's early offerings. "It is obvious that the microcomputer is at the center of a communications and information revolution. I believe that within 20 years most Americans will be computer users and will benefit from the attendant mental advantage," Roach told Creative Computing in 1984.

Machine Learning at the edge is gaining steam. BrainChip is accelerating this with their Akida architecture, which is mimicking the human brain by incorporating the 5 human senses on a machine learning-enabled chip. Their chips will let roboticists and IoT developers run ML on device for low latency, low power, and low-cost machine learning-enabled products. This opens up a new product category where everyday devices can affordably become smart devices. Rob is an AI thought-leader and Vice President of Worldwide Sales at BrainChip, a global tech company that has developed artificial intelligence that learns like a brain, whilst prioritizing efficiency, ultra-low power consumption, and continuous learning. Rob has over 20 years of sales expertise in licensing intellectual property and selling EDA technology and attended Harvard Business School. This is your host Abate, founder of fluid dev a platform that helps robotics and machine learning companies scale their teams up as they grow. So welcome Rob and honor to have you on here. Rob: Abate it's great to be here and thank you for having me on your podcast.

Virginie Do, Sam Corbett-Davies, Jamal Atif and Nicolas Usunier won the AAAI 2022 outstanding paper award for their work Online certification of preference-based fairness for personalized recommender systems. The award was presented at this year's virtual AAAI Conference on Artificial Intelligence. Here, Virginie Do tells us more about the implications of this research, the methodology, and their main findings. Our paper is about fairness in recommender systems, and more precisely about certifying that recommender systems treat their users fairly. We conducted this research in a context of increased interest in auditing for the fairness of recommender systems.