The development of science from the mid-19th century abounds in specialists, observes veteran cultural historian Peter Burke in his new book, The Polymath . Think of Louis Pasteur in medicine—the field that first embraced specialization—or Gregor Mendel in genetics, Marie Curie in physics, Edwin Hubble in astronomy, or Dorothy Hodgkin in chemistry. Yet despite the trend toward specialization since that time, polymaths, whose expertise spans a range of subjects and who flourished in previous centuries, have remained vital to science, if fewer in number. Charles Darwin and Alan Turing come to mind. As does Linus Pauling, who contributed not only to physical chemistry and mathematical physics but also to biology, medicine, and international peace—for which he received two Nobel Prizes. Indeed, Pauling came close to discovering the structure of DNA in the 1950s but failed to achieve his goal, “perhaps because he was distracted by his other interests.” Burke names “500 western polymaths” in the appendix to his mind-stretching and thought-provoking history, which spans the half-millennium that followed the life of the most wide-ranging polymath of all, Leonardo da Vinci. Like da Vinci, their collective work embraces both the sciences and the humanities. Some notable scientific figures among them include (in order of birth) Nikolaus Copernicus, Christopher Wren, Alexander von Humboldt, Mary Somerville, Ernst Haeckel, Henri Poincaré, Alfred Wegener, Erwin Schrödinger, Richard Feynman, Benoit Mandelbrot, and Oliver Sacks. Oddly omitted is the founder of modern nursing, Florence Nightingale, who was also distinguished for her work as a social reformer and statistician. The first half of the book sketches the lives and work of many of these individuals, with longer sections dedicated to key figures. Here we learn of Thomas Young (1773–1829)—now regarded by many as the greatest polymath since da Vinci—whose tombstone in London's Westminster Abbey describes him as “eminent in almost every department of human learning.” Formally trained as a physician in the 1790s, Young taught himself physics and philology. He discovered the phenomenon of astigmatism and first proposed the three-color theory of how the retina responds to light. He showed, in his famous double-slit experiment, that light could behave as both a particle and a wave, a remarkable observation that Richard Feynman declared “the heart of quantum mechanics” and its “only mystery.” Young also named the Indo-European family of languages and took the first crucial steps in deciphering the Rosetta stone and the Egyptian hieroglyphs. Chapter 6 aims to analyze the personal characteristics of polymaths as a group, singling out their unusual powers of concentration, capacious memory, speed, imagination, restlessness, industriousness, and obsession with not wasting time. “[An] overdose of curiosity, long known as the libido sciendi and described by the polymath Francis Bacon as ‘inquisitive appetite,’ is surely the most general as well as the most obvious characteristic of the species,” notes Burke. Two further chapters consider the careers led by polymaths, fleshing out their familial relationships, their educations and working environments, and their reception by professional institutions and by specialists. For all its considerable insight into polymathy, however, at no point does the book address what distinguishes a polymathic genius from a specialist of comparable standing. Should Albert Einstein, for example, be considered a specialist or a polymath? Einstein receives just one glancing reference in The Polymath , yet it could be argued that the physicist showed some polymathic tendencies, particularly later in life when he began to engage more deeply in political affairs (to say nothing of his well-known musical ability). There has always been a tension between specialization and polymathy. Universities and professions are chiefly organized for the benefit of specialists, not polymaths. Moreover, in addition to greater funding, specialists typically receive more recognition than polymaths do, as evidenced by the Nobel Prizes' emphasis on domain-specific advances. And yet, some of the greatest scientific discoveries and works of art have benefited from interdisciplinarity and even polymathy. As Thomas Young privately concluded, near the end of his underappreciated life, “It is probably best for mankind that the researches of some investigators should be conceived within a narrow compass, while others pass more rapidly through a more extensive sphere of research.”

This editorial introduces the special topic articles on reflections on successful research in artificial intelligence. Consisting of a combination of interviews and full-length articles, the special topic articles examine the meaning of success and metrics of success from a variety of perspectives. Our editorial team is especially excited about this topic, because we are in an era when several of the aspirations of early artificial intelligence researchers and futurists seem to be within reach of the general public. This has spurred us to reflect on, and re-examine, our social and scientific motivations for promoting the use of artificial intelligence in governments, enterprises, and in our lives. Ching-Hua Chen is a research staff member at the T.J. Watson Research Center in Yorktown Heights, New York.

It's Josh Milligan from Dread Central your host for another episode of Dissecting Horror a virtual panel series made to approximate the film festival or convention experience. Yeah, a little technical hiccup there one that I was warned about so yeah. We've got the cast and creators of artificial and interactive sci-fi series. I'm still wrapping my brain around it focuses on an artificial being artificial intelligence and it explores. Lot of the issues that have to do with humanity and technology, and some shows we've seen like Black mirror another films that blur the line between horror and Sci-fi. Artificial, however, is unlike anything I've seen before and even though it was launched a couple of years ago, it's almost perfectly made for the current time that we're living in and you'll see what I'm talking about because we're gonna show you a preview clip. Before we do that, I want to let you know who I've got here um on the panel with me uh Bernie Sue is the co creator and executive producer show runner director and head writer How you doing buddy Hi, thanks for having us. I can't wait to dive in and uh tell our friends what it's all about. Um you know we're also on the.

We build a platform, that totally automizes the wealth management process. Lars started out as a management consultant inside of Deutsche Bank, in their unit called in-house-consulting, focusing on their retail business. Our clients are wealthy, but not wealthy enough to qualify for traditional wealth management. You can now support us on Patreon https://www.patreon.com/bePatron?u 35246148 if you like what you see and hear consider to support us, so we can keep bringing you great content. There was no one at my company interested in what is today robo advisors, so I started my own and do not regret it until this day. They are wealthy enough to have money to invest, but in Germany, the normal threshold to enter the wealth management services of large banks is 2 million Euros, and they do not qualify yet. Ginmon wants to be the online financial advisor for this clientele. Therefore, they became fully licensed as a wealth manager in 2017, by German financial services oversight body BaFin. They now have an investment volume of more than 100 mn Euros for approx. According to Lars, they have approx.

Jaynarayan H. Lala (jay.lala@rtx.com) is a Senior Principal Engineering Fellow at Raytheon Technologies, San Diego, CA, USA. Carl E. Landwehr (carl.landwehr@gmail.com) is a Research Scientist at George Washington University and a Visiting Professor at University of Michigan, Ann Arbor, MI, USA. John F. Meyer (jfm@umich.edu) is a Professor Emeritus of Computer Science and Engineering at University of Michigan, Ann Arbor, MI, USA. This Viewpoint is derived from material produced as part of the Intelligent Vehicle Dependability and Security (IVDS) project of IFIP Working Group 10.4.

This paper develops a novel passive stochastic gradient algorithm. In passive stochastic approximation, the stochastic gradient algorithm does not have control over the location where noisy gradients of the cost function are evaluated. Classical passive stochastic gradient algorithms use a kernel that approximates a Dirac delta to weigh the gradients based on how far they are evaluated from the desired point. In this paper we construct a multi-kernel passive stochastic gradient algorithm. The algorithm performs substantially better in high dimensional problems and incorporates variance reduction. We analyze the weak convergence of the multi-kernel algorithm and its rate of convergence. In numerical examples, we study the multi-kernel version of the LMS algorithm to compare the performance with the classical passive version.

The above are excerpts from a long reply to a few questioning letters written by nine eminent philosophers from Massachusetts Institute of Technology, Harvard, Cambridge University and others. These letters asked questions like: Can artificial intelligence (AI) be truly conscious--and will machines ever be able to "understand"? How does technology interact with the social world, in all its messy, unjust complexity? How might AI and machine learning transform the distribution of power in society, our political discourse, our personal relationships, and our aesthetic experiences? The questions were addressed to the most recent arrival in the world of AI, called GPT-3.

Family, Career and Community Leaders of America (FCCLA) held its first-ever virtual National Leadership Conference since the organization was founded in 1945. This year's virtual National Leadership Conference was a memorable chapter in FCCLA's story as the organization kicked off its 75th anniversary celebration and honored FCCLA's Class of 2020. Instead of gathering in-person, 65 of Edison's John P. Stevens High School FCCLA students logged on to an online platform from Tuesday, July 7, through Thursday, July 9, which blended virtual reality and gamification technology to transform FCCLA's National Leadership Conference (NLC) into an "on-demand" virtual experience. This year's historic virtual NLC included keynote speakers, breakout sessions, leadership training, a College Fair and EXPO, STAR Events recognition, networking opportunities, adviser professional development, and many more activities. With just a click of a button, members had the opportunity to participate in the Ultimate Leadership Experience in the comfort and safety of their home.

"Machine learning is to businesses today what petrol engines were to horses back then." For this week's ML practitioner's series, Analytics India Magazine got in touch with Eugene Khvedchenya from Ukraine. Eugene is a Kaggle master and is currently ranked 104 on the global leaderboard. He has more than 10 years of experience in developing computer vision applications, and in this interview, he shared few valuable insights from his decade long journey. Eugene started programming from a young age ever since he saw his father assembling Orion 128 PC, a popular DIY PC in the early 90s.

Emilia Díaz-Struck is research editor and Latin American coordinator for the International Consortium of Investigative Journalists (ICIJ). She oversees data projects and has been involved in some major cross-border investigations including the Panama Papers, the Paradise Papers and the Offshore Leaks. The ICIJ receives vast amounts of files from whistleblowers and uses AI-powered technologies to sift through that data more efficiently. For our interview series with women working on the intersection of AI and journalism, Emilia spoke to us about how exactly AI is deployed and what impact it will have on investigative journalism. JournalismAI: You have a very diverse background in journalism, having worked with major organisations such as The Washington Post, the Press and Society Institute of Venezuela and co-founding your own news site Armando.info. How did you initially move into a data-driven role?