Academics From The United States

"The research shows that juniors don’t know anything special about AI: they use it first, but they don’t learn specialized knowledge from using it."

"What was new was the way of putting this together to get information from a magnetic core in a memory plane. I was taking a graduate course called Sample Data Systems from Professor William Linvill. Today the same course might have two names."

"We describe a state-of-the-art system for finding objects in cluttered images. Our system is based on deformable models that represent objects using local part templates and geometric constraints on the locations of parts. We reduce object detection to classification with latent variables. The latent variables introduce invariances"

"This manuscript presents a type-theoretic foundation for mathematics in which each type is associated with an equality relation in correspondence with the standard notions of isomorphism in mathematics. The main result is an abstraction theorem stating that isomorphic objects are inter-substitutable in well-typed contexts."

"This award is especially gratifying to me in view of the success of my initiative on advancing the IEEE transnational frontier in Eastern Europe, particularly in Russia"

"And that’s only accelerating,It's great to be connected to a business that is committed to new ideas and innovation.”"

"I am the Global Head of Investment and Client Solutions and CIO of the Solutions and Multi Asset Group within the Investment Management division. Our business has a number of different businesses within it, but at the core, we are focused on solving problems for clients and not only developing investing strategies."

"In order to do that, you need a very good platform with a lot of resources. And you then need to put those resources together in flexible ways to deliver solutions. We do that in a number of contexts. Not everything is so customized—we do have products. But those products are inspired by client problems."

"We have publicly launched Rexa, a new research paper search engine. It is a sibling to CiteSeer and Google Scholar, except that it provides search and browsing over more "object types", including not just papers, but also people, grants and topics."

"Culturally, we look for people who are able to work in teams. It's not a one-man show. We have a number of different businesses, but all of them are characterized by delivering value by combining new ideas and high quality execution, so that, in the end, one plus one equals three."

"The main goal of my research is to dramatically increase our ability to mine actionable knowledge from unstructured text. I am especially interested in information extraction from the Web, understanding the connections between people and between organizations, expert finding, social network analysis, and mining the scientific literature & community."

"Toward this end my group develops and employs various methods in statistical machine learning, natural language processing, information retrieval and data mining---tending toward probabilistic approaches and graphical models. For more information see our current projects and publications."

"The only difference is that cognitive science is more committed to understanding existing biological cognition, as opposed to all possible cognition, which is what AI studies. So, to cite a well-worn analogy, cognitive science is to AI as ornithology is to aerodynamics."

"One is that it has to extract some more facts from the web by reading (facts like 'Obama is president' or 'blue jeans are often worn with t-shirts'), and the second task it has to do each day is to learn to read better than it could the day before so that tomorrow it can collect some more facts more accurately....We started this program running 24 hours a day January 2010 so it's about 4 years old now and the results so far is that it is indeed learning."

"Our clients’ problems can be complex, so we have to think critically and creatively about how we are going to solve them."

"We want to provide a solution, but we first need new tools to help us better understand the problem. So we have to go and find or develop techniques to do that."

"Our team is made up of investors and analysts who have diverse background, and we use that to our advantage, gathering information from a variety of sources. Ideas can come out of academia like using data or analytics in new ways. Ideas may also come from our clients. For example, a client may come to us to find a way to generate income on a portfolio that integrates a particular liquidity and cashflow profile. We develop a solution for them and then may realize that it can be tailored to help us solve the needs of another client."

"I spend time on both the investment side and the client side, trying to think about ways to bridge them. I'm very involved with some of our largest clients, both institutional and high-net-worth individual clients. While we work on customized investment strategies, we also provide value to our clients beyond just the investments. It's not just managing a client’s assets, it's supporting them outside of investing, such as providing content, ideas and access to others within the firm."

"We are very cognizant of what is going on throughout the investment world. We're constantly looking at markets, looking at innovations in finance, scanning the latest research and connecting them to specific client situation."

"I first worked as a management consultant after graduating from college. I was living in Australia at the time and enjoying it, but I knew I wanted to go back to school. I decided to pursue a doctorate in political science. While I was in graduate school, I also received a master's degree in economics."

"I think AI researchers are always trying to make the problems they study a tad more general than an engineer is happy with. They force the problem into an area which is a little less structured, so the solutions are a little less defined, and we always have to use heuristics to solve them."

"I entered academia on a tenure track at the University of California at Berkeley, while continuing to consult on projects. That led to consulting work for the asset management business of a major bank, which was trying to solve some investment problems for their own portfolios and for clients. I was coming at it from a slightly different angle, as a social scientist rather than just a pure finance guy. And we had some success. I think my different perspective helped me and my team develop ideas that had some traction. So I kept consulting while I was on the faculty at U.C. Berkeley. I had been consulting for Morgan Stanley for several years when the bank offered me the full-time position I have now."

"You could say that the definition of the problem is part of AI. For example, with the visual tracking work that's going on here at Yale, the problem is to track something. But what's a ``thing? What counts as a ``something?"

"Well, we're not sure. We look at things that people seem to be able to track, and those are the things the human visual system picks out as trackable things, but that's not a very well-defined concept. Nonetheless, we feel that there's a real problem there, and we can show that the solutions are of great benefit in certain cases."

"We work with clients to achieve their mission beyond just trying to maximize their wealth. For example, we have one client who had a significant liquidity event and she wants to donate her money eventually. But while she's in the process of doing that, she wants the investments to make money and have a particular social impact. The ability to help a client have a positive impact on the world is very fulfilling."

"We have this research project going which we call our Never-Ending Language Learner (or NELL for short), and the goal here is to build a program that runs 24 hours a day 7 days a week and everyday it has two things it has to do."

"We also work for large public pension funds. I relate to this as a former employee of the state of California. You realize in this role that you work for firemen and teachers and you have something beyond a fiduciary duty. These people are depending on your performance. Delivering that is rewarding."

"We need our team members to be flexible in their thinking and flexible about ideas and functions. The people who work on our teams are experts in certain fields but are able to engage very rigorously on the investment side, analyzing investments, understanding them, identifying new ideas. They also understand how to engage with our clients."

"An engineer might throw his hands up at a problem like that and say ``Bring me something a little bit more defined than that. I'm willing to print bar codes on a thing, so it's clear what it means to track them. In the long run, it's conceivable that there will be no difference between engineering and AI. It's hard to say."

"You just glanced at your phone, didn’t you? That’s exactly how algorithms draw us in. We’re living suspended between two worlds: one where AI quietly decides who gets hired, what news we see, and which voices we hear—and another where millennia of human wisdom sit waiting to guide us."

"How do we use computation models to reverse-engineer intuitive theories and teach an AI to evolve based on these principals?"

"After forty years building AI systems and twenty years studying dharma in Indian ashrams, author Alok R. Chaturvedi learned something crucial: our digital future desperately needs our philosophical past. This isn’t another robot apocalypse book—it is an invitation to see technology through ancient wisdom made urgently relevant as artificial general intelligence approaches."

"Through deeply human stories—a coder discovering her biases embedded in “neutral” algorithms, a parent watching their child disappear into endless scrolling—we explore how technology impacts us across three dimensions: Daihik (personal), Daivik (universal), and Bhautik (material). We also examine how technology carries the Three Gunas: Sattvik (clarity), Rajasik (restlessness), and Tamsik (numbness). Additionally, The Dharma of AI introduces the Five Guardians, which are timeless ethical principles: Ahimsa (do no harm), Satya (seek truth), Asteya (take only what’s given), Brahmacharya (consume mindfully), and Dharma (act righteously). Whether building technology, raising children, or seeking authentic digital living, this book offers profound insight and practical wisdom for our most urgent conversation."

"Human common sense involves the understanding of physical objects, intentional agents and their interactionsHuman common sense involves the understanding of physical objects, intentional agents and their interactions"

"a weird quirk I’ve observed is that people are often hesitant towards applying AI towards security work. One of my students was using campus police data to determine where crimes may occur in and around campus. When we presented this at a conference, people were generally taken aback by our findings."

"As we get closer to limits in these approaches, it’ll become evident that other facets of AI need to be explored."

"In my opinion, there needs to be a rehabilitation of sorts for the classes of society that will face the brunt of job loss, like truck drivers when it comes to self-driving tech. While many people will face some crises in this transition, I believe it’ll be a good change in the end. In that sense, I’m more optimistic about AI’s effect on jobs."

"Throughout cognition, there are instances where we seem to know more than we have any reasonable right to know about the world, where we arrive at generalizations that go far beyond our sparse, noisy, limited experience. How are inductive leaps possible? There must be some other knowledge in our heads, some more abstract knowledge that guides and constrains our inferences"

"Personally, my theoretical focus has been on computational game theory, for example. I’ve witnessed cycles in AI where one particular technology suddenly takes over, and DL has certainly carried its weight with its wide-ranging applications."

"there is physics for AI, where there are concepts from physics that can help you build better AI tools, even if you aren’t directly studying physical systems. You can build machine learning architectures that have physics-style reasoning embedded and those concepts turn out to be quite powerful."

"I started writing about it right away in my Substack and I said immediately that it’s going to excite people but it has limits."

"We have a lot of tools now that are very useful. But I think the bigger questions of, like, how do you represent and acquire knowledge? You still don’t have really good answers to those. So I’ve never reached a point of being really satisfied. I always want it to go better."

"I came to Carnegie Mellon in 1978 as a graduate student. The robotics institute started in 1979. I was here from the beginning, but I did not do robotics then."

"I am slowly trying to learn quantum mechanics. Right now I’m reading Noson Yanofsky and Mirco Mannucci’s Quantum Computing for Computer Scientists, and Manjit Kumar’s Quantum: Einstein, Bohr, and the Great Debate about the Nature of Reality. Both are excellent books."

"I’ve never been fully optimistic about it. I don’t think we’ve made as much progress as I’d hoped that we would. I would have guessed that 40 years after I was looking at this, that a lot of A.I. would have been solved problems."

"I take a constructivist approach to understanding. When I study something, I ask “How could I build this, or how can I build things with this?” This is opposed to, for example, “Where might I observe this in nature?” I also tend to ask right away,"

"I designed a hexapod robot called the Chiara (see photo), which some students of mine have used to do really cool things. One programmed two Chiaras to play chess on a real chessboard. Another got a Chiara to walk up to an electronic keyboard and play Ode to Joy."

"I basically told them, in no uncertain terms, that this was not the way that I thought physics research should be going. And they agreed with me, actually, about the off-the-shelf use of machine learning."

"Where would someone live within the academic ecosystem if they wanted to dive into physics topics, but also computation and statistics? That was the motivation for submitting a grant to the NSF to start this institute.If you think about AI solely as it applies to fundamental physics research, we have massive challenges in our field and we’re trying to understand some of the deepest questions in nature."

"I’ve been very fortunate to pursue theoretical research and apply AI, finding a way to use it to advance the cause of social justice."