engineers-from-the-united-states

"For the millions of people on the planet who use digital cameras, the work of Dr. Frey and his team has the potential to make it easier to organize and sort through countless pictures stored on a computer's hard drive."

"People with gene mutation A are more likely to get disease B"

"For example, the traditional approach to organizing images is a step-by-step analysis that says, 'if there's colour then do this, and once you've completed that step, then see if there's a border around the image and then do this,' and so on."

"The same tools can also be used to analyze documents by grouping together similar sentences and summarizing their meaning.""

"We put it all together into one big system, Our ability to interpret the genome is growing very rapidly now. I think in 10 years we’re going to understand most of what the genome does, which mutations cause which diseases and why. Even if we could just address 10 per cent of genetic disease more accurately, it would have a huge impact on people’s lives.."

"After the human genome was sequenced, we had the text, but we didn’t know how to make sense of it, Now we have a ‘deep genomics’ engine – a machine-learning system where you feed in the genetics and it will tell you what’s going to happen in the cells."

"But the benefits of this technology go beyond digital photo albums, he says. "Medical researchers can use it to study hundreds of MRI images all at once and identify problems," he says, to give just one practical example."

"I believe that if you work really hard on researching and coming up with new ideas, then everything else will fall into place."

"The kind of research we do is leading edge in information technology."

"Our approach is different: instead of a linear analysis, we look at all the possible variables all at once and put together hypotheses that simultaneously try to figure out what all the images are about.""

"Similar pictures - for instance, all pictures of beach vacations - would be grouped together automatically by a computer program."

"Organisations, small and large, increasingly rely upon cloud environments to supply their ICT needs because clouds provide a better incremental cost structure, resource elasticity and simpler management. This trend is set to continue as increasingly information collected from mobile devices and smart environments including homes, infrastructures and smart-cities is uploaded and processed in cloud environments. Services delivered to users are also deployed in the cloud as this provides better scaleability and in some cases permits migration closer to the point of access for reduced latency. Clouds are therefore an attractive target for organised and skilled cyber-attacks. They are also more vulnerable as they host environments from multiple tenant organisations with different interests and different risk aversion profiles. Yet clouds also offer opportunities for better protection both pro-actively and reactively in response to a persistent attack."

"EU project, part of the FP7 People Programme. It is an international research staff exchange agreement with the aim of facilitating mobility and collaboration between Argentina and Europe on the use of formal methods and logic to model, understand and analyse systems. The Principal investigator is Dr Alessandra Russo and the contact person is Dr Sebastian Uchitel."

"... Let me start with the top mistakes that teachers make. Some of these mistakes are forced on teachers by a badly designed education system, and some are ones that teachers make no matter what they are teaching or which system they are teaching in. Some of these are less than obvious, so let's consider them one-by-one."

"I am a Professor in Applied Computational Logic at the Department of Computing, Imperial College London, and academic member of the Distributed Software Engineering Section."

"I lead the Structured and Probabilistic Knowledge Engineering (SPIKE) research group and my research interests are in foundation AI and applications to real-world problems. Specifically, I have led the pioneering of several state-of-the-art symbolic machine learning systems and widely applied them to the areas of Intelligent Adaptive Systems, Security, Network Management, Distributed Control Systems for Sensor Networks, and Healthcare. My research interests include Computational Logic, Planning, Symbolic Machine Learning, Probabilistic and Distributed Inference, Neuro-symbolic AI and Robustness of Generative Models."

"Certain things need to be done again and again in life, but those things can be learned only in context, not as an abstraction. Different contexts must be provided in order to motivate students and to provide real world skills that will be remembered, not because they were studied and tested but because they were practicied again and again."

"intelligence comes about in part from real focus (goal-directed behavior); (this is why you have the absent minded professor caricature[.] it is a rare woman who is not first and foremost focussed on what others are thinking and feeling about her[.] hard to be brilliant if you are worrying if you look fat or why another woman hates you or why you dont own a kelly bag[.]"

"EPSRC project on privacy management looking at investigating how individuals learn and benefit from their membership of social or functional groups, and how such learning can be automated and incorporated into modern mobile and ubiquitous technologies that increasingly pervade society. The Principal Investigator is Dr Alessandra Russo. The project is in collaboration with the Open University and the University of Exeter. It is a three years project started in November 2013."

"I'm not suggesting that teachers never tell the truth, only that it isn't necessary to do it all the time. Since coming to one's own conclusions is mostly how we learn, the real job of a teacher is to force students to come to sensible conclusions by confronting what they already believe with stuff that is antithetical to those beliefs. A confused person has only 2 choices. Admit he is confused and doesn't care, or resolve the confusion. Resolving the confusion invloves thinking. Teachers can encourage thinking by making sure students have something confusing to think about."

"This project is funded by the International Technology Alliance programme in Network and Information Science between UK (MoD) and US (ARL). It investigates the development of formal foundations for secure hybrid wireless networking, which supports adaptable and interoperable communication and information services for coalition operations. The Principal Investigator is Dr Alessandra Russo and the research is conducted in collaboration with Dr Jorge Lobo, form ICREA – UPF and IBM Thomas J. Watson Research Centre, New York, USA."

"EU Future and Emerging Technology (FET) project under the 7th Framework Programme, as part of the Pervasive Adaptation Initiative (PerAda). The recent advances in pervasive technologies enable construction of large-scale socio-technical systems which tightly interweave humans and their social structures with technology. The overall goal of Allow Ensembles is to develop a new design principle and establish a new foundational framework for collective adaptive systems (CAS) based on the concept of cell ensembles. The principal investigator is Dr Naranker Dulay and Dr Alessandra Russo is a co-investigator."

"This project is funded by the International Technology Alliance programme in Network and Information Science between UK (MoD) and US (ARL). It investigates security in tactical clouds from two different perspectives: i) development of a declarative infrastructure for agile, robust, and scalable de-centralized security policy adaptation mechanisms for tactical clouds, and ii) decomposition of network functions (e.g. firewalls, NAT or load balancing proxies) to cope with specific network and computing limitations of the physical deployment environments and the changing characteristics of the tactical clouds. The Principal Investigator is Dr Alessandra Russo and the research is conducted in collaboration with Dr Jorge Lobo, from ICREA – UPF, Professor Peng Liu from Pennsylvania State University, and IBM Thomas J. Watson Research Centre, New York, USA."

"There are endless books about what every third grader must know that use the idea that factual knowledge is the basis of the ability to read as their justification. Unfortunately, the writers of these tracts have misunderstood the cognitive science behind those statements. It is difficult to read things when you don't understand what they are about, but it does not follow from that thatthe solution is to ram that knowledge down kids' throats and then have them read. It is much more clever to have them read about what they know and to gradually increase their knowledge through stories that cause them to have to learn more in order to make the stories understandable to them"

"So, yes it's important to understand how a neuron works and a lot of neurophysiologists might complain that models of the neurons that the AI people are cooking up aren’t accurate enough. Well, that might be, but no amount of detailed understanding of an individual neuron or even how neurons get interconnected I think will be sufficient to have a good explanation of how it is that we do what we do. We have to have some higher level things and there are people working on that. But, some of it, I think, will get developed by those very people who have one foot in artificial intelligence and one foot in neuroscience to say, "Ah, the analogy to these high level programs is such and such to the way the brain does this." And they will invent concepts that will then help us understand the brain better."

"Well, large corpuses of data are going to be useful in lots of them. I don't know that it'll solve all the problems in AI. I mean, right now we can't do all the things that humans can do. Look around you and you can see. I mean, we have office buildings full of people. And many of them aren't using their hand eye coordination. It isn't mechanical engineering which is a problem. You might ask, why are they there? What are they doing? Well, they're having meetings, they're filling out paperwork, they're doing studies, they're communicating with other humans, they're making plans. And those are things, why can't computers do all that? Why is there anybody in those buildings except the janitors and maybe a few top bosses? Well, and computers would be cheap if we could do it, cheaper than those people. And so, why are they there? Well, because computers can't do it yet. And will lots and lots of data solve that problem? I don't think so. Might help, might be part of the solution, but the reason we don't have what you might call human level intelligence yet is that we just don't have the ideas needed in order to write the programs that would allow us to achieve human level AI. But, we have a lot of smart people and I think we're making some progress."

"Well, if you had asked me that a few years ago I might have said "No," because I think that whatever the power of computing was at the time it was fully able to handle any of the ideas that we had at the time. I mean, we were idea short, we weren't hardware short mainly. Now, I'm not so sure because the new idea that's come up, the use of lots and lots of data, well, lots and lots of data requires lots and lots of computing. And so, the more computing, the faster it can go the better. I don't know that that's the bottleneck at the moment. After all if you talk to the Watson people which I haven't, but if you did talk to them and you asked them, "Gee, how could Watson have been better? If you had a computer, this IBM 7000 series or whatever it was, if it were 10 times as fast, 100 times as fast, 100 times as much memory would you have done better?" I think they'd still answer "Well, not necessarily. We would need more ideas about how to program all that.""

"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?"

"Well, there's certain jobs that only people can do. You can't have a machine make sweaters made by hand. And there's kinds of things which involve social interaction which only people can do. Some of the social interaction maybe machines can do. But, if you really want a human you got to have a human. And so, I'm not saying that all jobs will be replaced, but we're already seeing a trend of many and I think that trend will continue and you read people who talk about the current slow recovery, the economic situation, and many people say "Well, we've laid off a lot of people because of the recession, but in the meantime we've found out we could do some of those jobs that those people did with machines and by the way, we're not going to hire those people back." And so, I think that's going to be a continuing difficulty."

"Right now, I don't know, I think I'd try to get involved in the bridge between AI and neurophysiology. Let's take neuroscience in particular because I think there's still a lot of secrets about how the brain works that we don't understand that'll be helpful in engineering. The reason we don't understand them, I think, is we haven't invented the concepts needed to understand them. I have this analogy with computers. If you had a Martian coming down looking at computers, measuring all the currents flowing back and forth from the transistors, no amount of all that measuring, no amount of understanding how a transistor works is going to tell you how say an online banking system works or how an airline reservation system works. You have to have concepts that got invented in computer science to even understand them. You have to have concepts like lists, programs, data structures, compilers and there are probably a whole set of analogous concepts in helping us understand the brain."

"A GAN stands for Generative Adversarial Network and is a machine learning technique for generation of content. It works by using two systems, one which tries to make convincing output by learning from a dataset and another which judges if the output is real or not. The generator keeps adapting to try to fool the tester and eventually it makes output that is fairly convincing."

"GANs are interesting because the output, while in the same style as the input, is almost always surprising and interesting."

"I recorded all of that and I looked at it. I've forgotten some of the questions that were asked. Well, for example, on this Toronto thing. Remember the example in which it was asked, well the clue was World War II aviators or naval battles for which airports were named. And the answer would be Midway and Chicago and O'Hare. And it mentioned something in Toronto, I think, even though it was supposed to be a US city. And I think the people who designed it explained that well, oftentimes the category US city doesn't really mean exactly US city, it's sort of general. And so, Watson didn't count that as heavily as it should have. But, maybe it had some inaccurate common sense that allowed it to answer Toronto. But, anyway it was a failure of some sort of common sense reasoning."

"We focus on a unique form of artificial intelligence called artificial swarm intelligence"

"Forcing polarized groups into a swarm allows them to find the answer that most people are satisfied with"

"A machine is not a genie, it does not work by magic, it does not possess a will, and … nothing comes out which has not been put in, barring of course, an infrequent case of malfunctioning. … The “intentions” which the machine seems to manifest are the intentions of the human programmer, as specified in advance, or they are subsidiary intentions derived from these, following rules specified by the programmer. … The machine will not and cannot do any of these things until it has been instructed as to how to proceed. ... To believe otherwise is either to believe in magic or to believe that the existence of man’s will is an illusion and that man’s actions are as mechanical as the machine’s."

"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."

"Out of all my projects, this is the research area that’s resonated the most with people, I think everyone is interested in the arts and creativity, and how AI and technology will impact it for the future. Like how the computer enhances the way people work, I’m hoping AI technology can enhance how artists work, freeing them up to be more creative."

"It’s such an important subject for any age,Everyone in life experiences failure, and this book is about how to strategize getting unstuck. Some people may even view Drive.ai being acquired by Apple last year as a failure instead of it becoming the next stand-alone billion- dollar company. I see it as an opportunity for my next company to get there.”"

"A poll will give you the most popular answer but not the answer that optimizes the preference of a group."

"The reason that fish form schools, birds form flocks, and bees form swarms is that they are smarter together than they would be apart. They don't take a vote; they don't take a poll: they form a system. They are all interactive and make a decision together in real time."

"How does nature amplify the intelligence of groups? It forms swarms."

"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"

"Taking a vote or poll is a great simple way to take a decision, but it doesn't help a group find consensus. It actually polarizes people and highlights the differences between them. People end up getting entrenched in their views."

"We take the sense of touch for granted. Think about it: Without it, you're missing one of the basic senses that enables you to interact with the world."

"There is more that can be done by cleaning up and sorting through the data set. For instance, it can be trained on drawn faces, or many images of a particular style."

"Still, some of the output veers into the figurative. In a relatively short time, it could draw human faces and some creatures that look like animals. How do you imagine DADAGAN evolving?"

"It’s hard not to antropomorphize DADAGAN, because it’s easy to play around with the idea that it is making art. Where do you draw the line?"