Whether an artist, scientist, or film director, trailblazers in particular fields often have a critically-acclaimed'hot streak' where they produce a series of outstanding work in short succession. Now, scientists at Northwestern University in Illinois claim to have pinpointed the secret formula that often triggers a pioneer's best work. Using a form of artificial intelligence (AI) called deep learning, they mined data related to thousands of artists, film directors and scientists to identify a magical formula for success. Hot streaks directly result from years of'exploration' (studying diverse styles or topics), immediately followed by years of'exploitation' (focusing on a narrow area to develop deep expertise), they claim. They define a hot streak as a burst of high-impact works clustered together in close succession – as achieved by artists such as Vincent Van Gogh and Jackson Pollock, or film directors like Peter Jackson or Alfred Hitchcock.

It is a crazy world we live in. Technology has taken the world by storm. In my opinion, it is the best thing that has ever happened since sliced bread. From lab-grown meat to autonomous vehicles, the possibilities are just endless. How have you adapted to the disruptions so far?

For regular readers of the (lately somewhat irregularly published) The Cagle Report, I've finally managed to get my feet underneath me at Data Science Central, and am gearing up with a number of new initiatives, including a video interview program that I'm getting underway as soon as I can get the last of the physical infrastructure (primarily some lighting and a decent green screen) in place. I recently purchased a new laptop one with enough speed and space to let me do any number of projects that my nearly four-year-old workhorse was just not equipped to handle. One of those projects was to start going through the dominant triple stores and explore them in greater depth as part of a general evaluation I hope to complete later in the year. The latest Ontotext GraphDB (9.7.0) had been on my list for a while, and I was generally surprised and pleased by what I found there, especially as I'd worked with older versions of GraphDB and found it useful but not quite there. These four items have become what I consider essential technologies for a W3C stack triple store to fully implement.

AI 2041: Ten Visions for Our Future is an unusual book. Each chapter consists of a short story, penned by science fiction writer Chen Qiufan, and a related analysis piece from Kai-Fu Lee, CEO of Sinovation Ventures and author of the nonfiction bestseller AI Superpowers. Chen, who also is founder of Thema Mundi, a content development studio, spoke with Fast Company on the eve of the release of AI 2041 about his collaboration with Lee, his own experiences with artificial intelligence, and what machine learning will mean for artists and writers. This interview was edited for length and clarity. Fast Company: How did this project come about?

BANGKOK/LONDON – A week after the Myanmar military seized power, a Twitter account that had lain dormant for nearly a decade flickered back into life. The Twitter user mocked anti-coup protesters, hundreds of whom have been killed in a crackdown by security forces since the Feb. 1 coup. After a police truck fired high-pressure water cannons on demonstrators in the capital city of Naypyidaw on Feb. 8, he made a trolling reference to the nation's traditional April new year celebration: "Water festival come earlier for them lol." A few weeks later, the user wrote "#fuckthereds," making a dismissive reference to the political party of Aung San Suu Kyi, the Nobel Prize-winning civilian leader who had been overthrown and arrested in the coup. A review of an archived version of the account, which has since been shut down, revealed the username was a pseudonym belonging to Ivan Htet, the 33-year-old son of a leading figure in the coup: the chief of the air force, Maung Maung Kyaw. But Ivan Htet hasn't just been an enthusiastic supporter on social media of the Tatmadaw, the name for the Myanmar military, which has dominated political life since independence in 1948 for Myanmar, then called Burma. He is also trying to cash in, helping equip the military, along with his wife Lin Lett Thiri, who co-founded a private firm to supply Myanmar's armed forces, Reuters has found.

In the first instalment of this new video series, Stephen José Hanson talks to Michael I Jordan, about AI as an engineering discipline, what people call AI, so-called autonomous cars, and more. To provide some background to this discussion, in 2018, Jordan published an essay on Medium entitled Artificial intelligence -- the revolution hasn't happened yet, in which he argues that we need to tone down the hype surrounding AI and develop the field as a human-centric engineering discipline. He adds further commentary on this topic in an interview published this year in IEEE spectrum, (Stop calling everything AI). Hanson wrote a rebuttal to the Medium article, AI: Nope, the revolution is here and this time it is the real thing, and the pair discuss the theme in more detail in this video discussion below. There is also a full transcript of the discussion below. This interchange was recorded on June 15th 2021. HANSON: Hi Michael, good to see you! So let's get into this. Let me just state what I think you said and you tell me where I'm wrong, if I am. So it appears to me that you're basically talking about that AI should arise from an engineering discipline that with start from well-defined science like chemistry and chemical engineering and this would allow the insights from the science to migrate their way into an engineering domain which had principles of design and control and risk management and many other good statistical quality control ideas that basically made AI the valuable and useful and have some utility and something actually went to calculate about the AI I actually being useful as opposed to the number hidden units it has…. JORDAN: Just to slow you down a little bit there, I mean historically I think the good points of reference or things like the development of chemical engineering or electrical engineering were that there was an existing science and understanding and there was an appetite to build real-world systems that have huge implications for human life. So chemical factories didn't exist initially, but when they started to exist, I don't think it was that the science was all worked out and they kind of applied it and it just happened.

Recently the Manufacturing Media Consortium and its founder, TR Cutler (TRC) set up a new division examining the role of manufacturing and technology in the entertainment industry. What follows is an interview of Jacob Kyle Young (JKY) actor and founder of Post Modern Entertainment. In an interview with Jacob Kyle Young (JKY), actor and founder of Post Modern Entertainment, TR Cutler describes how virtual reality, machine learning, and other industrial automation is being applied in the entertainment industry. Virtual reality (VR) is projected to be the rapidly growing segment in the media and entertainment space, according to Global Entertainment, which reported that 68 million VR headsets would be sold in the USA before the end of 2021, raising VR content revenue to $ 5.0 billion. During COVID, it became evident that using AI can help create VR interactive content. Using AI techniques, the entertainment industry creates remarkable scenes with a pair of goggles.

Eight years after Kennedy's initial so-called moonshot challenge, two American astronauts took the famous "one giant leap for mankind"--walking on the Moon for the first time. However, the bigger impact of that moonshot was the resultant building of a massive military and industrial innovation complex that propelled the US to the top of the industrial economy. The industrial economy, in simple terms, grew by selling excess production from one place to another by connected pathways. By 1975, the industrial economy was at its peak, with more than 1 billion places connected by rail, road and airways dominated by multinational companies born in the US, selling technology developed during the moonshot. The other spinoff of this moonshot was ARPANET, kicked off in 1966, which eventually became the internet. The internet gave rise to the knowledge economy driven by connecting people via the world wide web.

In this paper, we present our Alexa Prize Grand Challenge 4 socialbot: Proto. Leveraging diverse sources of world knowledge, and powered by a suite of neural and rule-based natural language understanding modules, state-of-the-art neural generators, novel state-based deterministic generators, an ensemble of neural re-rankers, a robust post-processing algorithm, and an efficient overall conversation strategy, Proto strives to be able to converse coherently about a diverse range of topics of interest to humans, and provide a memorable experience to the user. In this paper we dissect and analyze the different components and conversation strategies implemented by our socialbot, which enables us to generate colloquial, empathetic, engaging, self-rectifying, factually correct, and on-topic response, which has helped us achieve consistent scores throughout the competition.

Rachel earned her math PhD at Duke University. She is a popular writer and keynote speaker, on topics of data ethics, AI accessibility, and bias in machine learning. Her writing has been read by nearly a million people; has been translated into Chinese, Spanish, Korean, & Portuguese; and has made the front page of Hacker News 9x.