What do you think when you think of artificial intelligence (AI)? Until recently, generations of people only viewed AI technology through the lens of popular culture depictions. And one major touchstone in their experiences was the movie 2001: A Space Odyssey, which celebrates its 50th anniversary this year. It was the highest-grossing film in North America in 1968, selected to be preserved in the U.S. Library of Congress National Film Registry, won an Academy Award for visual effects and a Hugo Award--one of science fiction's highest honors--for Best Dramatic Presentation. Despite its accolades, the movie drew a mixed reception of awe and confusion over its depiction of evolution and the meaning of existence.

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Combining state-of-the-art optimization and machine learning techniques with high-speed electromagnetic solvers offers a new approach to "inverse" design and implement classical and quantum photonic circuits with superior properties, including robustness to errors in fabrication and environment, compact footprints, novel functionalities, and high efficiencies. In this plenary talk, Jelena Vuckovic of Stanford University illustrates this with a number of demonstrated devices in silicon, diamond, and silicon carbide, including wavelength and polarization splitters and converters, power splitters, couplers, nonlinear optical isolators, on-chip laser driven particle accelerators, and efficient quantum emitter-photon interfaces. Jelena Vuckovic is a professor of electrical engineering at Stanford, where she leads the Nanoscale and Quantum Photonics Lab. Vuckovic has won numerous awards including the Humboldt Prize and the Presidential Early Career Award for Scientists and Engineers. She is a Fellow of APS, OSA, and IEEE.

The latest research from MeriTalk finds what while artificial technology (AI) development is viewed by many in government and industry as still in the blush of youth, the technology is poised to rapidly outgrow its present suit of clothes. The research project – conducted by MeriTalk and underwritten by Pure Storage – polled government and industry executives and IT decision makers at this summer's AI World Government event, who said among other top-line findings that hybrid cloud infrastructure is a key enabler for AI adoption, and that the military and intelligence agencies are expected to lead Federal government's push into AI tech adoption. We sat down last week with Nick Psaki, Federal CTO at Pure Storage, to get his thoughts on the research results, and his longer-term outlook on how AI adoption is likely to gain momentum in the coming years before becoming an ultimately ubiquitous technology layer that will leave an indelible mark on society. MeriTalk: In examining the AI study results, what are the most important findings for Federal government officials that are currently undertaking AI or robotic process automation (RPA), or are considering doing so? Psaki: Two things jump out – the current feelings about AI maturity, and then the time to breakthrough to mission-critical tasks. On the first one, if you add respondents who said AI development is between "a little" (42 percent) and "moderately" (48 percent) mature, combined that's a big number (90 percent).

The Freeman Spogli Institute for International Studies (FSI) and the Stanford Institute for Human-Centered Artificial Intelligence (HAI) are pleased to announce that Marietje Schaake has been named to international policy roles in each of their organizations. At FSI, Schaake will serve as the first international policy director of the Cyber Policy Center. With a focus on cybersecurity, disinformation, digital democracy and election security, the Cyber Policy Center's research, teaching and policy engagement aims to bring new insights and solutions to national governments, international institutions and industry. Schaake will also be an international policy fellow at Stanford HAI, which seeks to advance artificial intelligence (AI) research, education, policy and practice to improve the human condition. The university-wide institute is committed to working with industry, governments and civil society organizations that share the goal of a better future for humanity through AI.

Yann LeCun is one of the fathers of deep learning, the recent revolution in AI that has captivated the world with the possibility of what machines can learn from data. He is a professor at New York University, a Vice President & Chief AI Scientist at Facebook, co-recipient of the Turing Award for his work on deep learning. He is probably best known as the founder of convolutional neural networks, in particular their early application to optical character recognition. This conversation is part of the Artificial Intelligence podcast.

With companies continuing to shrink or outsource their human resources departments, it is tempting to augment that traditional business function with artificial intelligence. Data science holds so much promise for other fields that it makes sense for algorithms to replace imperfect human decision-making for hiring, firing, scheduling and promoting. But new research from Wharton professors Peter Cappelli and Prasanna "Sonny" Tambe flashes a cautionary yellow light on using AI in human resources. In their paper, "Artificial Intelligence in Human Resources Management: Challenges and a Path Forward," the professors show how limited data, the complexity of HR tasks, fairness and accountability pose problems for digital HR. The study, which was co-authored by Valery Yakubovich, professor at ESSEC Business School and senior fellow at the Wharton Center for Human Resources, also looks at how to remedy those problems. Cappelli and Tambe spoke about their research with Knowledge@Wharton. An edited transcript of the conversation follows. Knowledge@Wharton: You make the point that while AI is invading many different industries and sectors, there are some special concerns when it comes to using AI in human resources. Can you talk about what some of those challenges are?

Compared to constituency parsing and semantic role labeling, dependency parsing provides more clear relationships between predicates and arguments (Johansson and Nugues, 2008). Constituency parsers provide information about noun phrases in a sentence, but provide only limited information about relationships within a noun phrase. For example, in the sentence "What do you think about Google's privacy policy being reviewed by journalists from CNN?," a constituency parser would place "Google's privacy policy being reviewed by journalists from CNN" under a single phrasal node. Similarly, a semantic role labeling system would tend to label the same phrase as an argument of the verb, but it would not disambiguate the relationships within the phrase. Finally, NER only provides information about named entities which may or may not be the key semantic content of the sentence. Dependency parsers, by contrast, can provide information about relationships when a sentence contains multiple entities, even when those entities are within the same phrase. Identifying relationships between entities in a user utterance can help a dialog system formulate a more appropriate response. For instance, in the sentence about "Google's privacy policy" mentioned above, there are multiple entities for the system to consider. The system must determine the most important entity in the utterance in order to model the topic and generate an appropriate response.

This week I'm joined by Jason "JJ" James who is the CIO for Optima Healthcare Solutions. JJ is also the author of the upcoming book "Make IT work: Practical IT guide to mergers and acquisitions." In our conversation, JJ outlines how the CIO is similar to an anthropologist and must be a study of human tools, culture and development. We also discuss JJ's perspective on how innovative technology is impacting the healthcare industry. Closing out our conversation, JJ talks about why hype is valuable and the role the CIO plays in the changing landscape. Tim Crawford: Hello, and welcome to the CIO In The Know podcast, where I take a provocative, but pragmatic look at the intersection between business and technology. Tim Crawford: This week I'm joined by Jason JJ James, who is the CIO for Optima Healthcare Solutions. JJ is also the author of the upcoming book, Make it Work: Practical IT Guide to Mergers and Acquisitions. In our conversation, JJ outlines how the CIO is similar to an anthropologist, and must be a study of human tools, culture, and development. We also discuss JJ's perspective, on how innovative technology is impacting the healthcare industry. Closing out the conversation, JJ talks about why hype is valuable, and the role the CIO plays in the changing landscape. So, when you think of healthcare in the space we operate in, which is post-acute care, which is everything outside of the hospital, there's so much happening in that space. I think about my own mother who is in assisted living.

John Chambers, founder and chief executive officer of JC2 Ventures LLC, stands for a photograph following a Bloomberg Technology Television interview in San Francisco, California, U.S. John Chambers, who just turned 70, prefers to take any stage at a run. In his tech trendy uniform--blue blazer, designer jeans, checked shirt, and blue boat shoes--he still exudes the physical energy of his successful tenure as CEO at Cisco Systems, which he grew from an annual revenue of $2.2 billion in 1995 to $49 billion in 2015 when he stepped down. Today Chambers runs his own boutique investment firm, JC2 Partners, in Palo Alto, California. He prefers to call himself a mentor to startup CEOs rather than a venture capitalist. When he's not in Silicon Valley he can often be found in India, where he advises Prime Minister Narendra Modi's government on digital transformation and the economy.