Engineers From The United States

"Beyond individual intelligence, nature has also cultivated intelligence through swarms. For example, bees, birds and fish act in a more intelligent way when acting together as a swarm, flock or school"

"You have the sense of touch because you need it."

"Hopkins has an altruistic focus that pervades all through the university, In a time where AI and computer science can impact so many different fields, it was really interesting to realize that a lot of startups didn’t care about ethics or the customer in a human way—it was more about earning money or selling your company. It made me realize that everything at Hopkins is very human-centric, and people were very front and center. It was mission-focused."

"It’s crazy that we’re so immune to those deaths,I thought self-driving cars would be a way to save lives proactively, and I also see self-driving cars as the world’s first mass-scale robot, and that’s going to come with a lot of challenges."

"It will be a problem in the end, I think, for society what happens, what do we do with all the people that computers replace? And eventually, I mean, right now you need more and more skills in order to have jobs. But, there's this guy Robin Hansen, you know about Robin Hansen? Robin Hansen is an economist and he has got this interesting metaphor of sea level rising. Sea level is what computers can do. And land and the land that's inhabited, the jobs that require humans to do. And sea level's been rising. And on the shore a lot of people are displaced. Well, they've had to move to higher levels. But, to move to higher levels they have to have more training. Now, the fact that sea level's rising itself makes some higher levels. It's a funny thing. At sea level build some mountains so people can climb those mountains, but sea level will keep rising. And the question is will it rise above even those mountains? And so, what do we end up having people do?"

"The DADA dataset was very diverse, which can be both a good and bad thing. It’s good because there is a lot of variety to learn from, and it’s bad because it is hard to “converge” on. So, the output that the model generates is quite abstract, however, this aligns with the spirit of DADA."

"One "occupational hazard" of being a professor is exposure to various countries, cultures, and people from all over the world. I was very fortunate to visit a few dozen countries, often hosted by people who have the same professional interests. This made me wonder what my life would be like if I had grown up there. I became attracted to Poland, where I have family heritage, and then Nordic countries. I was especially attached to Finland after teaching a short course at the University of Vaasa in 2007; I was invited by Pekka Isto, a Finnish motion planning expert."

"In 2016, I was approached by Huawei to be their Chief Scientist and Vice President for VR/AR/MR consumer products. I proposed building a big research center, in the UIUC Research Park, which would be a joint effort between the University of Illinois and Huawei. Both parties were excited, and after a year of preparation, I joined Huawei while retaining a part-time UIUC position. Like many US universities, UIUC had taken in many thousands of high-paying Chinese students in recent years (presumably to help with rising costs and the lack of tax funding). These students were absolutely shocked and thrilled that I was leading this effort, bridging the gaps between China and the US. Needless to say this was eventually doomed in 2017 amid rising nationalism, the eventual US-China trade war, and Huawei being put on the entity list. I nevertheless had a wonderful time working in Huawei and learned so much about consumer product development. I met many hard working, kind, and intellectually interesting people, and thoroughly enjoyed the culture in Shenzhen, Shanghai, and Hangzhou."

"The unbelievable Oculus success also opened many doors, and I had the opportunity to get to know people I never would have met before, including CEOs, venture capitalists, serial entrepreneurs, billionaires, politicians, and Hollywood people. At the same time, I returned to UIUC to continue my tenured position. I was so excited about the consumer VR revolution that I started a new course and wrote a VR book based on it. The key insight was that understanding human perception and physiology is critical to engineering of VR systems and experiences. Thus, the course and book provide a unique integration of these subjects. A version of the course was recorded by NPTEL when I visited IIT Madras in 2015 and is available online."

"After the industry experiences, I could see startling differences between the academic and business worlds. I was most comfortable in universities, where I was able to freely learn, grow, and openly share whatever I know with people around me. In industry, information is protected, which leads to complicated games and strategies for gaining power based on who knows what. It is a difficult place to be if you enjoy sharing your knowledge and understanding, and generally helping people with their projects. I also found the Dunning-Kruger effect to cause serious problems in industry, especially when people don't know what they don't know, but have massive power over others and company directions. Both worlds clearly play important roles, but I learned that a university research environment makes me the happiest. I feel very lucky to have been able to try both at fairly high levels."

"The reason I included the bits above is to explain why I always have strong empathy for people who have struggled because they are not part of the usual group in power. In my case, it was mostly about coming from a poorer, working-class family. Doing something smart would often lead to bullying. I could feel people having contempt for me as I succeeded and maybe even outperformed them, when based on my way of speaking, clothing, or whatever else, I should have been easily beaten. I really didn't care for competition; I just wanted to ensure I could be in a place where I could work with very smart, open-minded people. I am certain that others who struggle with additional issues based on race, gender, sexuality, disabilities, foreign nationality, and so on, face these problems and more. I had to learn how to speak and act differently to fit into the higher levels of society, but to this day I continue to have feelings of impostor syndrome. If you know what I am talking about, then please be sympathetic and support each other (and not only the ones in your own group)!"

"In 2012-2013, I came with my family to Oulu for a sabbatical to write books and get to know Finland better. After living there for nine months, we came to deeply appreciate Finnish culture and lifestyle. It seemed that Finland naturally fit my personality. People are respectful of each other and generally cooperate in maintaining a safe, responsible, and fair society. Modesty and respect for cultural differences around the world are strongly emphasized. Education and educators are highly respected. I thought it would be perfect for raising my children, with safe, playful, and nurturing infrastructure, and where good health care and education are free rights of residents (private universities are even illegal). Relating to my profession, there is strong interest in developing advanced technology while also being respectful of nature, the environment, and wellbeing. These are the values that suit me well, and that I want my family to learn. In 2018, I was invited to become a professor at the University of Oulu, and I could not be happier. I am currently co-leading the Perception Engineering Group, which pursues problems in virtual reality, robotics, and telepresence. The university made a nice video about me, and a Finnish newspaper explains more about why I moved to Oulu. I am also involved in helping the industrial ecosystem in Finland, especially in virtual reality and its various flavors (VR, AR, MR, XR, ...)."

"Near the end of high school, I still believed that engineers mostly drive locomotives, but my guidance counselor pointed out that with my interests in math, science, and computers, I should probably be an electrical or computer engineer. He then showed me a college guide to convince me that some school in Missouri was one of the "top" (it wasn't listed there), and I looked over his shoulder and saw the top 3 schools listed as "MIT", "Stanford", and "Illinois". He didn't seem to know anything about "Illinois", but I made it my mission to learn about it. I figured that MIT and Stanford were only for rich people from another planet, but Illinois happened to be the name of that state on the other side of the Mississippi River from St. Louis. I soon realized that "Illinois" was UIUC, which was actually the home of the fictional HAL 9000 Computer from 2001! It was to be completed in 1992 (movie) or 1997 (book), which meant I had a chance to help realize at least part of the glorious future of that movie. It took me a couple of years of complicated scheming to borrow money in every way possible to cover the triple out-of-state tuition rate. When I finally figured it out, I had to personally petition to UIUC Engineering Dean to even be allowed to apply as an out-of-state transfer student, and they said I was the only one they let in over the past decade. Persistence! I then fought for two more years to get all prior credits transferred, and finally graduated as one of the top students from Electrical and Computer Engineering in 1989."

"Around 2012, I started to get the sense that robotics as a field was gradually becoming less interested in fundamental research, and many researchers were insisting that all work should be experimental and practical. Based on my background described above, I have tended to be respectful and supportive to all communities, which made this trend disheartening. On the other hand, I thought that if one was to do something very practical, then why not just build a product in industry? Otherwise, I could not see the point of being in academia. So, I gave it at try..."

"I was born in 1968 and grew up in and around St. Louis, USA. My loving parents were often overwhelmed because I asked them questions continuously to the point of exhaustion. As a child I was inspired by the space age, with Kubrick and Clarke's 2001 exciting me with dreams of a future full of space exploration and intelligent machines (HAL 9000). No one in my family had gone to college, and nearly everyone around me was skeptical about higher education (why would you let them "educate the brains out of you?" or "After that, he ain't got no more common sense."). This made it seem nearly impossible to get on track for helping build that envisioned future. Also, while I was growing up, the space age was slowly disintegrating."

"In the early 1980s, I spent much of my spare time in video arcades and on the Atari 2600 home console. It blew my mind when I heard that a kid up the street had a computer and it could be used to "program his own" video games. I quickly read a book and started programming regularly on a display TI 99/4A at Kmart. I couldn't believe that I could make this machine do whatever I wanted! Eventually, I scrounged up enough money to get the cheapest home computer (TS 1000 with 2k memory), and when I turned 16, I worked lousy food service jobs all summer to buy a Commodore 64. This allowed me write all kinds of programs, both in BASIC and machine language, with my favorite still being to make video games. At the same time, this activity, along with some inspiring teachers, gave me enough confidence to go from being a terrible student in high school to being the top student in every subject. This required a huge amount of work and determination. I think this made me not very popular among some people who came from more educated and wealthy families."

"In September 2012, I got an email out of the blue from Jack McCauley, from a VR company that was founded two months earlier by a 19-year-old named Palmer Luckey. Oculus VR had just closed a successful Kickstarter campaign and needed to make head tracking work for the Oculus Rift in a hurry. Jack was googling for things like "quaternions" and "Euler angles" and found my Planning Algorithms book. I was just about to refer them to some industry-oriented colleagues, but contemplated my family financial worries, including paying for my eventual children's university tuition, retirement funds, and rising medical costs. I naively thought a successful startup could fix that. Before too long, I was their chief scientist, where I developed patented tracking technology for consumer virtual reality, and led a team of perceptual psychologists to provide principled approaches to virtual reality system calibration, health and safety, and the design of comfortable user experiences. By March 2014, Facebook agreed to buy the company for $3 billion. I guess I was lucky in my first industry experience! The overall story is nicely told in this book by Blake Harris."

"“The central idea in connectionism is that a large number of simple computational units can achieve intelligent behavior when networked together.”"

"“Working successfully with datasets smaller than this is an important research area, focusing in particular on how we can take advantage of large quantities of unlabeled examples, with unsupervised or semi-supervised learning.”"

"“Hochreiter and Schmidhuber (1997) introduced the long short-term memory (LSTM) network to resolve some of these difficulties. Today, the LSTM is widely used for many sequence modeling tasks, including many natural language processing tasks at Google.”"

"“A probability distribution over discrete variables may be described using a probability mass function (PMF).”"

"“At this point, deep networks were generally believed to be very difficult to train. We now know that algorithms that have existed since the 1980s work quite well, but this was not apparent circa 2006. The issue is perhaps simply that these algorithms were too computationally costly to allow much experimentation with the hardware available at the time.”"

"“Cognitive science is an interdisciplinary approach to understanding the mind, combining multiple different levels of analysis.”"

"“Logic provides a set of formal rules for determining what propositions are implied to be true or false given the assumption that some other set of propositions is true or false. Probability theory provides a set of formal rules for determining the likelihood of a proposition being true given the likelihood of other propositions.”"

"“Another crowning achievement of deep learning is its extension to the domain of reinforcement learning. In the context of reinforcement learning, an autonomous agent must learn to perform a task by trial and error, without any guidance from the human operator. DeepMind demonstrated that a reinforcement learning system based on deep learning is capable of learning to play Atari video games, reaching human-level performance on many tasks”"

"“we do not yet know enough about biological learning for neuroscience to offer much guidance for the learning algorithms we use to train these architectures.”"

"“We assume familiarity with programming, a basic understanding of computational performance issues, complexity theory, introductory level calculus and some of the terminology of graph theory.”"

"“Several key concepts arose during the connectionism movement of the 1980s that remain central to today’s deep learning. One of these concepts is that of distributed representation (Hinton et al., 1986). This is the idea that each input to a system should be represented by many features, and each feature should be involved in the representation of many possible inputs.”"

"“∑x∈xP(x) = 1. We refer to this property as being normalized. Without this property, we could obtain probabilities greater than one by computing the probability of one of many events occurring.”"

"“The former kind of probability, related directly to the rates at which events occur, is known as frequentist probability, while the latter, related to qualitative levels of certainty, is known as Bayesian probability.”"

"“The training algorithm used to adapt the weights of the ADALINE was a special case of an algorithm called stochastic gradient descent. Slightly modified versions of the stochastic gradient descent algorithm remain the dominant training algorithms for deep learning models today.”"

"“Probability mass functions can act on many variables at the same time. Such a probability distribution over many variables is known as a joint probability distribution. P(x = x, y = y) denotes the probability that x = x and y = y simultaneously. We may also write P(x, y) for brevity.”"

"“Another major accomplishment of the connectionist movement was the successful use of back-propagation to train deep neural networks with internal representations and the popularization of the back-propagation algorithm (Rumelhart et al., 1986a; LeCun, 1987). This algorithm has waxed and waned in popularity but, as of this writing, is the dominant approach to training deep models.”"

"“Even today’s networks, which we consider quite large from a computational systems point of view, are smaller than the nervous system of even relatively primitive vertebrate animals like frogs.”"

"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."

"“As of 2016, a rough rule of thumb is that a supervised deep learning algorithm will generally achieve acceptable performance with around 5,000 labeled examples per category, and will match or exceed human performance when trained with a dataset containing at least 10 million labeled examples.”"

"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."

"“A representation learning algorithm can discover a good set of features for a simple task in minutes, or for a complex task in hours to months.”"

"“one of the names that deep learning has gone by is artificial neural networks (ANNs).”"

"“Software libraries such as Theano (Bergstra et al., 2010; Bastien et al., 2012), PyLearn2 (Goodfellow et al., 2013c), Torch (Collobert et al., 2011b), DistBelief (Dean et al., 2012), Caffe (Jia, 2013), MXNet (Chen et al., 2015), and TensorFlow (Abadi et al., 2015) have all supported important research projects or commercial products.”"

"“The field of deep learning is primarily concerned with how to build computer systems that are able to successfully solve tasks requiring intelligence, while the field of computational neuroscience is primarily concerned with building more accurate models of how the brain actually works.”"

"“While neuroscience is an important source of inspiration, it need not be taken as a rigid guide.”"

"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."

"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."

"“It is worth noting that the effort to understand how the brain works on an algorithmic level is alive and well. This endeavor is primarily known as “computational neuroscience” and is a separate field of study from deep learning. It is common for researchers to move back and forth between both fields.”"

"“The third wave of neural networks research began with a breakthrough in 2006. Geoffrey Hinton showed that a kind of neural network called a deep belief network could be efficiently trained using a strategy called greedy layer-wise pretraining (Hinton et al., 2006),”"

"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."

"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."

"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."

"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."