A Quote by Fei-Fei Li

Making AI more sensitive to the full scope of human thought is no simple task. The solutions are likely to require insights derived from fields beyond computer science, which means programmers will have to learn to collaborate more often with experts in other domains.
Complexity has and will maintain a strong fascination for many people. It is true that we live in a complex world and strive to solve inherently complex problems, which often do require complex mechanisms. However, this should not diminish our desire for elegant solutions, which convince by their clarity and effectiveness. Simple, elegant solutions are more effective, but they are harder to find than complex ones, and they require more time, which we too often believe to be unaffordable
The history of science, like the history of all human ideas, is a history of irresponsible dreams, of obstinacy, and of error. But science is one of the very few human activities-perhaps the only one-in which errors are systematically criticized and fairly often, in time, corrected. This is why we can say that, in science, we often learn from our mistakes, and why we can speak clearly and sensibly about making progress there. In most other fields of human endeavour there is change, but rarely progress ... And in most fields we do not even know how to evaluate change.
That machines will surpass us in intelligence is inevitable. What it means is unknowable. Will they be sentient? What will they care about in the sense that determines our human motivations? All the theorizing by the experts and non-experts makes for interesting conversations and dramatic headlines, but it's more likely we will be surprised by how our technology develops and how it is used, as we so often are.
The very properties of the human mind that provide an enormous scope for human genius in some domains will serve as barriers to progress in other domains, just as the properties that enable each child to acquire a complex and highly articulated human language block the acquisition of other imaginable linguistic systems.
Expertise in one field does not carry over into other fields. But experts often think so. The narrower their field of knowledge the more likely they are to think so.
Another of the qualities of science is that it teaches the value of rational thought, as well as the importance of freedom of thought; the positive results that come from doubting that all the lessons are true... Learn from science that you must doubt the experts. As a matter of fact, I can also define science another way: Science is the belief in the ignorance of experts.
Medicine is the science by which we learn the various states of the human body in health and when not in health, and the means by which health is likely to be lost and, when lost, is likely to be restored back to health. In other words, it is the art whereby health is conserved and the art whereby it is restored after being lost. While some divide medicine into a theoretical and a practical [applied] science, others may assume that it is only theoretical because they see it as a pure science. But, in truth, every science has both a theoretical and a practical side.
The greatest achievements in the science of this [twentieth] century are themselves the sources of more puzzlement than human beings have ever experienced. Indeed, it is likely that the twentieth century will be looked back at as the time when science provided the first close glimpse of the profundity of human ignorance. We have not reached solutions; we have only begun to discover how to ask questions.
Beware of people preaching simple solutions to complex problems. If the answer was easy someone more intelligent would have thought of it a long time ago - complex problems invariably require complex and difficult solutions.
My research career has been devoted to understanding human decision-making and problem-solving processes. The pursuit of this goal has led me into the fields of political science, economics, cognitive psychology, computer science and philosophy of science, among others.
Computer programmers, biotechnologists, environmental scientists, neuroscientists, nanotech engineers - all of these fields, and more, should have at least a course in ethics as part of their degree requirements.
I am often asked what the future holds for Emotion AI, and my answer is simple: it will be ubiquitous, engrained in the technologies we use every day, running in the background, making our tech interactions more personalized, relevant, authentic and interactive.
Religion and science, for example, are often though to be opponents, but as I have shown, the insights of ancient religions and of modern science are both needed to reach a full understanding of human nature and the conditions of human satisfaction. The ancients may have known little about biology, chemistry, physics, but many were good psychologists.
If somebody is working on a new medicine, computer science helps us model those things. We have a whole group here in Seattle called the Institute for Disease Modelling that is a mix of computer science and math-type people, and the progress we're making in polio or plans for malaria or really driven by their deep insights.
Economics is a theoretical science and as such abstains from any judgement of value. It is not its task to tell people what ends they should aim at. It is a science of the means to be applied for attainment of ends chosen, not, to be sure, a science of the choosing of ends. Ultimate decisions, the valuations and the choosing of ends, are beyond the scope of any science. Science never tells a man how he should act; it merely shows how a man must act if he wants to attain definite ends.
...the mind is more powerful than any imaginable particle accelerator, more sensitive than any radio receiver or the largest optical telescope, more complete in its grasp of information than any computer: the human body- its organs, its voice, its powers of locomotion, and its imagination- is a more-than-sufficient means for the exploration of any place, time or energy level in the universe.
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