All Quotes

"The defining moment that drove my interest in immunology was an inspiring talk delivered by Prof Yechiel Becker from Israel, who was visiting the then National Institute for Virology (now the NICD)."

"You need to love what you do – enormously. Things don’t always work out as you may think, you need to persevere, be proactive and be resilient. See failure as opportunity – more is often learnt from facing challenges."

"All science communication begins with the ability to write clearly and engagingly."

"I tune in on what is happening in the world, looking at current events through a science communication lens which helps me to identify new opportunities for research."

"Hearing from a young age that you are a “words person” can heighten your anxiety about math. As a result, you may avoid it."

"In science stories, math helps the reader understand real-world phenomena."

"Developing novel medicines is hard. Most of the time, compounds don’t make it all the way through to development, so to be part of a project that made it through commercial launch to have a direct impact on so many patients is incredible."

"That early read out was a sign that what we were doing was incredibly efficacious in the field."

"If you take this bag of garri about 10 to 15 kilometers out of this village, you are going to sell it for 6,000 naira."

"In Artificial Intelligence, it is often said that the representation of knowledge is the key to the design of robust intelligent systems. In one form or another the principles of Knowledge Representation are fundamental to work in natural language processing, computer vision, knowledge-based expert systems, and other areas. The papers reprinted in this volume have been collected to allow the reader with a general technical background in AI to explore the subtleties of this key subarea. These seminal articles, spanning a quarter-century of research, cover the most important ideas and developments in the representation field. The editors introduce each paper, discuss its relevance and context, and provide an extensive bibliography of other work. "Readings in Knowledge Representation" is intended to serve as a complete sourcebook for the study of this crucial subject."

"Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs."

"Science became my life’s work, research my passion and mentoring students my mission."

"I always knew I wanted to work with nature. Plant pathology became a calling, combining my love of biology with real-world impact. It connected my scientific interest with a moral purpose: to make food safer for everyone."

"Lots of computer games are compelling. E.g., I find even current computerized poker games quite compelling, and I find The Sims downright fascinating; doubtless you have your own favorites. But our planet isn't graced by even one dramatically compelling computer game (or, more generally, one such interactive digital entertainment). The movie T2, Dante's Inferno, Hamlet, Gibson's prophetic Neuromancer, the plays of Ibsen -- these things are dramatically compelling: they succeed in no small part because they offer captivating narrative, and all that that entails (e.g., engaging characters). There is no analogue in the interactive digital arena, alas. Massively multi-player online games are digital, interactive, and entertaining -- but they have zero literary power (which explains why, though T2 engages young kids through at least middle-aged professors, such games are demographically one-dimensional). The same can be said, by my lights, for all other electronic genres."

"This state of affairs won't change unless a number of key challenges are conquered; and conquering them will require some seminal advances in the intersection of artificial intelligence (AI) and narrative. (E.g., since interactive digital narrative will need to be crafted and massaged as the story is unfolding, computers, not slow-by-comparison humans, will need to be enlisted as at least decent dramatists -- but getting a computer to be a dramatist requires remarkable AI.) In this paper, I discuss one of these challenges for the start of the new millennium: the problem of building dramatically compelling virtual characters. Within this challenge I focus upon one property such characters presumably must have: viz., autonomy."

"We have dramatically compelling non-interactive digital (= electronic) entertainment: sit down and watch The Matrix (see Figure 1) or T2 (see Figure 2). We have compelling interactive digital entertainment; my favorites include console-based sports games.2 We have dramatically compelling interactive entertainment; for example, improvizational theatre. What we don't have is dramatically compelling interactive digital entertainment. People sometimes tell me that there is a counter-example to my negative view to be found in online multi-player games, but though such games are digital, interactive, and entertaining -- they have zero literary power (which explains why, though T2 engages young kids through at least middle-aged professors, such games are demographically one-dimensional). The same can be said, by my lights, for all other electronic genres. Can we build systems that imply and affirmative answer to the title of this paper? My answer is: ``Maybe, maybe not; but at any rate I can tell you, at least in broad strokes, what some of the hurdles are, from the standpoint of AI. And I can tell you, today, about one specific hurdle.""

"Realism About Narrative and AI"

"The first reason is that lots of people are either ignorant of or tendentiously choose to ignore the underlying mathematical facts. These facts include that some problems can be solved by computing machines, and others can't, and that most can't. So whenever you ask whether a problem P can be solved by a computing machine, where P is such that it isn't known that there is an algorithm for solving it, honesty should imply wait-and-see agnosticism.3"

"Let make explicit one presupposition before we begin in earnest. I assume that AI in general, along with the AI part of the gaming industry in particular, have realized that non-logicist AI isn't magic. What do I mean? I mean that people should be smart enough now to concede that no system is going to automatically learn, through subsymbolic, numerical processing, how to, say (and this is the challenge I'm going to focus on below), assemble robust, autonomous characters in a game. Automated learning through artificial neural networks and genetic algorithms are fine for certain applications, but gone, I assume, are the days of wild optimism about the ability of such learning techniques to automatically yield (to stick with this example) full-blooded NPCs.4 We really only have two overall approaches to AI: one based on logic, and one based on subsymbolic processing. This paper is written from the perspective of logic. If you think that you have a way of solving the problems I'm talking about without using logic, I wish you well."

"I enjoy sports, although I’m not good at any. I’m not one of those people who just says they’re bad, I really am uncoordinated, but for some reason I enjoy things anyway. At MIT I played soccer with The Cold Booters (I founded their C-league team) and D-league ice hockey with the Halting Problem in 1995 & 2000 (I got to play D league 2 years because I never learned to skate). In Edinburgh I managed to find 3 different weekly bad soccer games. When I first came to Bath, sometimes the Math & CS grad students let me play football with them, and Marina De Vos played squash with me, but then I ran out of time for that. More often I hill walk (mostly to work in Bath), cycle (mostly to work in Mannheim) and very occasionally play"

"There are contexts in which it is immoral to use generative AI. For example, if you are a judge responsible for grounding a decision in law, you cannot rest that on an approximation of previous cases unknown to you. You want an AI system that helps you retrieve specific, well-documented cases, not one that confabulates fictional cases. You need to ensure you procure the right kind of AI for a task, and the right kind is determined in part by the essentialness of human responsibility."

"I'm interested in how intelligence works, in people and in animals. (I don't think you can understand the former without the latter!) My research starts from a distributed model of intelligence called reactive, behavior-based reasoning. This approach has produced the first robots that can reliably interact with the real world at realistic, animal-like speeds. However, by the time I started working on this problem in 1993, it was already obvious that the approach wasn't scaling very well. In other words, no new purely behavior-based robots have come out that could behave in a significantly more complex way than the early projects such as Herbert and Polly ."

"The best supported theory in science is the theory of evolution. We don't understand evolution perfectly, but we understand it better than we understand gravity. If you don't know basic evolution theory, you will have trouble understanding not only biology, but also modern theories of society (including religion) and intelligence (including artificial intelligence). If you aren't getting a good background on evolution at school, try reading some of the links off John Wilkins's Evolution Links page."

"I mean, first of all, like I said, it’s for all of the media interest in the idea of sexualized robots, it’s really not a burgeoning industry yet. There really just have not been functioning robotics in that area. I guess I’m hesitating because it’s sort of hard to say right now; they’re talking dolls essentially, if you can afford one. So that’s a very different experience than something that can move and interact with you."

"So as the technology changes, as the supply chain for them changes and the prices come down, that changes the market. That’s capitalism. That’s how it works with everything. As they become more accepted, as they become more common, all of these things impact how culturally we look at them. So will it go from we’re looking at them… I mean, think of a Terminator narrative or a Frankenstein narrative that we very much have about robots 25 years ago in the West that I think has changed a lot."

"As I watched it, there is fear of some emerging robot scenarios like sexualized robots or people who could fall in love with robots because it’s new. But as these things become more common and as we can observe how people are interacting, we can really… Instead of trying to predict damages, we’re learning how people are navigating it as it’s happening. I mean, that’s my view as a cultural scholar, really."

"I’m very much an observer. Again, that’s ethnographer in me. I’m sure there are plenty of people in this area and ethics that would have a much more active response. But I view my work as one that’s heavily one of observation and reporting, again, patterns in how I see people interacting with these technologies. So I’m sort of this conduit of information, if you will. I’m a medium in itself if that makes sense."

"I am a cosmologist, which means that I spend my time thinking of the universe and how it formed and evolves with time. I work with a combination of data and theory – it is important to me to make sure that our theories actually match the data we observe!"

"Because I analyse data as well as testing theories, a lot of my time is spent writing (and debugging) computer code, and doing statistical analysis. It is very rewarding to go from a theory that you think might explain our universe, to the nitty gritty of data analysis. I’m lucky to be able to work in both areas."

"I’m just curious about how things work. I think I became a scientist because my mom had been a physics teacher and she brought home cool demos—I saw a laser and I thought that was awesome. She’d bring home dry ice and I thought that it was amazing that gas could be a solid. I’ve always liked quantitative puzzles and so it’s a way to combine, sort of, curiosity about things around me with my tendency to be quantitative about things. What I study now is materials. I’m interested in why materials behave the way they do. Much of the technology in the world around us is built upon materials that have very specific properties."

"I always thought maybe I could transfer to medicine at some point but I never actually did in the end. When I started to work on some of these problems, I found it so interesting that I couldn’t break away. I was lucky I found a group of supervisors who had done some very, very interesting physics."

"A big problem in science is the inadequate recognition given to the female physicists who made groundbreaking contributions last century."

"Gow to grow plantain, the market availability of plantain, where to obtain seedlings to grow cocoyam, and so forth."

"I wanted to develop an innovative and interactive platform."

"The farmers' contributions are transmitted to us via a Wi-Fi connection. We receive tons of messages. But we first have to listen to the messages to ensure that they are relevant."

"Where there is no electricity, people can get batteries for radio."

"We're working with a group of people that earned about less than U.S. $.50 a day. *Today most of them are earning $.80 to $1 a day because we're working with them. It's a long process. But it gradually comes together."

"Our broadcasts have resulted in increased crop yields, higher standard of living, lower death rate, and above all."

"Though the reach of the radio station is 30 kilometers, around 65 percent of the population is benefited as it is a densely populated area."

"The duration of the broadcast is 10 hours five in the morning and five in the evening."

"The idea is to empower farmers with critical skills."

"Our information includes techniques in crop production, livestock rearing, sustainable environmental management, local and international markets, exportation process, business skills and access to a question and answer service."

"The idea for my start-up came from a radio show, where I work as a radio host."

"The show I run targets farmers and serves as a knowledge platform for new developments in agriculture."

"That’s the reason I spend a lot of time on the ground talking to farmers, which helps me to identify their problems and challenges to get a better understanding of their current situation."

"I have made many contacts for my company. At the moment, I can not yet assess whether these contacts will result in cooperation."

"Business relations are slowly developing."

"This is the only way to build the trust you need for cooperation in business."

"“Alcuni uomini con cui ho lavorato avevano paura di una ragazza giovane e carina … era difficile avere lo stesso spazio dei colleghi uomini, non parliamo dello stipendio.”"

"“Tengo a bada lo stress con passeggiate in Cilento, la mia terra, yoga e calciotto.”"