Academics From The United States

"The biodiversity of microbes far exceeds that of all other organisms combined."

"I think of this as maybe similar to the fact that the complex numbers are an algebraic closure of the real numbers. And quite similarly again, the problems in the quantum model often have richer connections between them; they somehow ring ‘right,’ mathematically."

"There are so many different universal models of quantum computers, each one based on a completely different algorithmic approach — like adiabatic computation, quantum walks, measurement-based quantum computation, topological quantum computation, and more — and they are all essentially equivalent,” she said. “You don’t really know which direction the next quantum algorithm will come from."

"One very, very interesting thing about quantum computation is that it touches so many different fields in mathematics"

"It’s not like that in classical computation. It’s really something that is special for quantum computation because it’s somehow ‘complete’ — quantum computation is some kind of completion, mathematically, of classical computation."

"I think there are advantages and disadvantages to that. I would like to see more stamina from the community when it comes to looking into the more difficult questions that have less immediate reward — like, for example, deeply understanding quantum algorithms."

"Previous papers, and in particular Hastings’ first papers on topological obstructions, manage to show that stoquastic adiabatic computation is capable of understanding something about the global structure of a problem."

"There are two Nobel Prize discoveries whose computation system was powered by HTCondor––the Higgs Boson in 2012 and then recently detection of gravitational waves by the LIGO collaboration. So I am always joking, I’m looking for the triple crown. But I can’t say that they’re more important or challenging than other works of science powered by HTCondor."

"But the personal angle is that we always saw what we are doing as expanding from the desktop to the world. And that’s how we went from the campus to nation-wide and beyond."

"We now share HTC capabilities across more than 125 institutions. And that brought with it many complications, not only in terms of volume of users, but also in diversity of science domains, types of institutions and politics. I always listed sociology as the top obstacle to high throughput computing and we have our fair share in the Open Science Grid."

"Today’s quantum ecosystem is extremely vibrant, and there is a lot of energy and focus on particular questions"

"The thing is that people have tried a lot with few successes, but I don’t think that too many people have tried enough"

"Microbes have been shaping the course of evolution since the beginning of life."

"From the most remote landscapes to the depths of the ocean, microbes are everywhere."

"I was always fascinated by the simple problem that you have a quest for work sitting and waiting in one place and a resource capable and willing to serve it is idling in another place. How do you bring them together? It turns out it’s an unsolvable problem so I can work for 40 more years."

"I think there are more algorithms down that road — very interesting ones — but it will probably be difficult to come up with them."

"That's exactly the key thing. We need to understand the math to get it right. And so I spent a lot of time reading John von Neumann, and von Neumann had a lot of really good thoughts about how to do it. And I was amazed people didn't follow up on some of these thoughts. So I decided, well, okay, I'll take the mathematical approach. I'll solve these mathematical problems. Here's how to do it."

"And believe it or not, reinforcement learning was the first thing, how to come up with a system that could learn to act and achieve goals."

"One thing I think we should realize is, we'll be calling the AI today what they used to call AI 10 years ago. AI 10 years ago was a bunch of rules. You would write thousands of rules and that was AI. And that's embedded in pretty much every system we consume today. Every service we're getting-- simple things like health insurance. A typical high-rate insurance company has about half a million rules inside the system to process your claim. And so AI has always been in there; it's just as soon as it becomes deployed, it's not called AI because it's now real, it's not magic."

"my experience with computing started with work on memory. I always had a perspective on computers which is sort of a memory's eye view. I look for the memory and see what you have to connect around it. In my work for a master's degree I wanted to improve the signal-to-noise ratio of the sensing signal coming out of core memory. In those days, the materials for making magnetic cores were very poor compared to what they finally evolved into."

"What was needed was a very square hysteresis loop, and they couldn't get that exactly. The signals coming from the selected core in the memory plane containing the bit that the computer was trying to read became corrupted with noise, and sometimes the signal could be noisy enough to cause an error. I had the idea of driving the Cartesian x and y axis grid lines of the core with currents of two different frequencies, and I chose 10 mhz and 10.5 mhz."

"Nobody knows. We don't know what o1's good or bad at yet, no one knows anything about models on release. The question I always ask is: “How is your business figuring out what o1’s useful for?”"

"The problem people have out there to try to understand what's going on in the world today, there are just a whole lot of pieces, and you don't really know what's happening until you can put them together and know what they are"

"And it's really scary to be one of the few people in the world, even now who really knows what these algorithms are. I see people talking about artificial intelligence and neural nets and their future, and it's amazing what kind of theories you can hear on TV, a lot of it from people who have political motivations."

"So I think the way to think about it isn't whether it's going to help or not, or does it do something well or not, but does it do it better than what we're doing today? And I think that gets to deepest point of values. If we take a problem and we solve it and now it's 90% correct, well what does that mean? Do we only care about overall correctness, or do we care about how does it have disparate impact on different types of people? If it's 10% wrong, is it 10% wrong on everybody"

"The phrase "signal processing" was not used. But in fact, I was dealing with signals and determining what was happening with nonlinearity and mixing in the frequency domain. All these concepts were well understood."

"Invoking the simple principle of translational symmetry — which in nature gives rise to conservation of momentum — led to dramatic improvements in image recognition"

"So backpropagation really came from me trying to understand how brains work and how you could build a brain like a brain. And when I was growing up, I read a lot of books I was excited by. There's a book called Computers and Thought, which was the start of the whole artificial intelligence world."

"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."

"The hardware is a collection of about a hundred computers that Garth Gibson (another faculty in our department here), runs as a research project and he lets us use that collection to run NELL....Maybe more interesting than the hardware is how the learning itself works and I could take a few minutes to explain that"

"They have (in a funny way) a more complete factual set knowledge than a normal three year old, but they still don't have that kind of common sense that a 3 year old has"

"Let's say I give you the word 'mom' or 'computer'....it's really the same brain and the only difference is that when I say the word 'mom' it was one pattern of neurons firing and when I say 'computer' it is a different set of neurons firing in your brain. We've become very interested in how the brain processes natural language and for the past 12 years with my colleague Marcel Just in our psychology department"

"Actual end user adoption has been insanely high, certain surveys that show 65% of marketers, 60% of coders are using Gen AI. But businesses don’t necessarily capture all of that value – that requires rethinking processes and approaches. If I increase everyone’s productivity by 20%... that’s awesome, but how do I as a firm actually collect on that? One way is to fire people, but if you fire people they won’t show you how they’re using AI."

"You have to incentivize it. If employees are worried colleagues will lose respect for them for using AI, or the bank won’t reward them for using AI, or they will get let go because they’ve got AI to do 90% of their tasks, then they’ll never show you how they use it. AI access helps, sharing helps, some education/training helps, as well as showing support at the highest levels of the organization."

"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."

"I was operating as a person intrigued by mechanism rather than concerned with the task, concerned with the problem and the need to bring a solution to the problem"

"The model performs in the 75th percentile for American adults, making it better than average The problems that are hard for people are also hard for the model, providing additional evidence that its operation is capturing some important properties of human cognition.""

"Seniors are actually the best able to use AI because they have the expertise, and they can get a sense very clearly of when the AI knows something or if it’s making it up."

"Like many students in the intervening years, I was obsessed by this new representational idea and looking for a place to apply it, rather than the other way around - facing the problem and bringing the right tools to bear on it."

"In any event I was speculating on the use of semantic nets in a blocks world context and a very obscure footnote in my thesis proposal said, "Well, gee, if I can describe block structures as semantic nets, then perhaps I could gain something from the differences between two descriptions of different scenes and their semantic net form and that might be a basis for learning something." And maybe I gave an example or something."

"I should refine my notion of how difficult to approach... Minsky has never been difficult to approach. He just seemed that way because anybody sufficiently famous will seem difficult to approach to a shy graduate student. I'm still awed by Minsky. In a sense, nothing's changed."

"It is also worth pointing out that I have developed a strong interest in (re)defining Computing as a separate and vivid discipline. This has most obviously manifested itself in my efforts at curricular development and reform. Possibly related to these efforts, I was the Associate Dean of Academic Affairs in the College for a number of years before becoming the Senior Associate Dean and eventually the Executive Associate Dean (where I retained my role in Academic Affairs while overseeing a lot of the operations of the College). I was lucky enough to serve as the fourth John P. Imlay, Jr. Dean of the College. After four years doing that, I became the Provost at University of Wisconsin-Madison."

"Definitely related to these efforts, I have put a great deal of energy into thinking about access at all levels, with an eye toward broadening participation in the professoriate. I don't have dozens of papers in this space, but I care about it as deeply as I do my AI research and all the rest that I do. Generally speaking, I split my time among my professor and admin selves because I think efforts around operationalizing and supporting broad access deserve as much intellectual energy and thought as any of our other academic efforts"

"I’m energized by this chance to serve the citizens of Illinois and advance the mission of learning, discovery, engagement and economic development”"

"We want to solve the problems that have been engendered by the success of search"

"I think of my field as interactive artificial intelligence. My fundamental research goal is to understand how to build autonomous agents that must live and interact with large numbers of other intelligent agents, some of whom may be human. Progress towards this goal means that we can build artificial systems that work with humans to accomplish tasks more effectively; can be more robust to changes in environment, relationships, and goals; and can better co-exist with humans as long-lived partners."

"After thinking about this problem for a number of years, I've decided that the central technical issues here are: adaptive modeling, especially activity discovery (as distinct from activity recognition); and scalable interaction, including coordination and influence. Further, I have come to believe that as a practical matter, it is necessary to build development environments that support rapid development, and so I try to think seriously about authorial tools, including adaptive programming languages, domain-specific example-driven development, socially-guided machine learning, and corresponding issues in software engineering."

"All in all, I believe that there are many opportunities in this space, and it should interest anyone who cares about any of the areas I mention above. To that end, I have spent time building The Laboratory for Interactive Artificial Intelligence and the pfunk research group. Our research goal is to develop methodologies for building persistent, adaptive, collaborative, and believable agents that must live with other similar agents, including humans."

"If you have 20 researchers interested in search, then getting them together where they are cross-fertilizing ideas, you make something bigger than its parts. You can create a nuclear reaction"

"I realized two things It’s doable at the massive scale of the campaign, and that means it’s doable in the context of other problems.”"