Turing Award Won by 3 Pioneers in Artificial Intelligence

from NYTs

In 2004, Geoffrey Hinton doubled down on his pursuit of a technological idea called a neural network.

It was a way for machines to see the world around them, recognize sounds and even understand natural language. But scientists had spent more than 50 years working on the concept of neural networks, and machines couldn’t really do any of that.

Backed by the Canadian government, Dr. Hinton, a computer science professor at the University of Toronto, organized a new research community with several academics who also tackled the concept. They included Yann LeCun, a professor at New York University, and Yoshua Bengio at the University of Montreal.

On Wednesday, the Association for Computing Machinery, the world’s largest society of computing professionals, announced that Drs. Hinton, LeCun and Bengio had won this year’s Turing Award for their work on neural networks. The Turing Award, which was introduced in 1966, is often called the Nobel Prize of computing, and it includes a $1 million prize, which the three scientists will share.

More here.

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  1. The advances in technology will continue to amaze us and grow at an exponential rate. The smarter we become the faster we will be able to figure out ways to make our lives more and more automated. For some this is exciting as life will become easier and faster, while for others this is scary because we start to lose our freedom. Computers will start to flood each and every industry and we will start to lose our jobs quicker and quicker. As computers become smarter than humans and cheaper to pay than wages, it would make sense for companies to get rid of their employees. Within the next few years I wouldn’t be surprised to see robots gain the ability to feel and communicate emotions, the only thing that makes humans ‘human’.

  2. Dr. Hinton, Dr. LeCun, and Dr. Bengio have all made extraordinary process on their project of the neural network. If you don’t know, the neural network is pretty much a robot that can think the same way like a human being. Face recognition to self driving cars are all forms of neural network that the three computer scientists created. Artificial intelligence has had a major impact on our lives recently whether it’s in the workplace or driving down the road. All three scenitest have worked for major tech companies such as IBM, Facebook, and Google helping these companies introduce new algorithms in their system. Advanced algorithms that these scientists have programmed help companies save money and rule out any human error. Companies can save money in areas such as customer service by going to a company like Google and asking if they can write code for advanced algorithms to outsource their customer service positions. This will save the company money, because they won’t have to pay an employee to sit around. Obviously advanced algorithms like the three scientists created in the neural network won’t steal jobs because today we have more advanced algorithms than ever but the tightest labor market in years. Also, using the neural network advanced algorithms people won’t have to worry about human error. Humans make mistakes all the time, but robots don’t. They are programmed a certain way by backtesting data. I use some algorithms to do certain tasks for me but not the advanced algorithms that the neural network has discovered. I strongly believe that certain advanced algorithms that these three scientist discovered will be implemented more and more in our society as years go on.

  3. Artificial intelligence is such an intriguing topic of discussion, especially with so much new technology being pushed to us consumers on a regular basis. Dr. Hinton, Dr. LeCun, and Dr. Bengio have all made extraordinary progress with artificial intelligence, and I truly admire them for that. Thanks to curious scientists like them, we have facial recognition technology, talking digital assistants, and even self-driving cars.

    Facial recognition increased security to levels that were only seen in movies! It is easier to guess a pin number to unlock a phone or a door, rather than replicate someone’s detailed face to breach a locked phone or a locked door. Digital assistants are becoming sophisticated, and helpful to the average consumer. The fact that they are able to recognize different peoples’ voices, and comprehend commands is mind-blowing. Self-driving cars is another product of artificial intelligence, which is emerging in the auto industry with several manufacturers. The car literally learns the more the software is used similarly to a human being. With all these inventions being made based on artificial intelligence, it displays the importance of the research these scientists are performing. These type of discoveries and advancements in this type of research is the exact reason why they won the Turing Award this year. The Turing award is the equivalent to a Nobel Prize but in the computing world, and includes $1 million dollars, which will be split amongst the scientists.

    I hope more individuals are inspired by these scientists to push the research even further to discover new technologies or uses with artificial intelligence. In today’s world, kids literally grow up with technology as infants, and often times become very dependent on technology, which is a reason why this artificial intelligence research should be pushed forward since the future will consist of the human race being highly dependent on technology.

  4. I am still in awe and at a standstill with how much we have managed to progress forward and integrate technology more. Now we have reached appoint where we now want to create something more, something that will push the boundaries of what we think can be possible. The only way to do that is by making the machines we built be able to operate and learn on their own just like a human would. The idea of a neural network isn’t new the article says that it has been attempted at for over 50 years, until these three men managed to achieve the start of a neural network through mirroring the same neural network that we have in our brain. Adding a human proponent to the machines we built only makes these machines more human, again there is a theme of everything that we build is just a reflection of our own humanity. So the advancement of AI to the point where it mirrors a human is now not out of the question anymore. From the three scientist research we have benefitted better facial recognition which has now been integrated into our phones and it only keeps getting faster and more efficient. This raises all sort of questions now that need to be addressed now, because now this neural network and interpret data and information. Now we can already do this but even the most brilliant minds can’t interpret data as fast as the most mediocre operating system. Now it has the capability to learn from all the data its fed which gives it the potential to be smarter than most of us. Is that not a scary thought? The idea of the machines we built being smarter than us and being able to know more, identifying patterns which means they would have a better viw of the future than we can predict from looking at the same data points. In fact they would be able to look at more data points meaning their predictions would be significantly more accurate. Now as I sit here and type this comment up I can only think about how much time do we have before the machines we built continue to benefit us, until there’s a time where the machine will take advantage of us.

  5. I always thought that the advancement of Artificial intelligence was something that had been acquired over time. Little did I know that it was mostly in part due to Dr. LeCun, Dr. Bengio and Dr. Hinton and their work on neural networks. Neural networks are essential to the very makeup of artificial intelligence as it allows machines to “see the world around them, recognize sounds and even understand natural language.” This neural network is modeled after the connection of neurons in the human brain which is absolutely fascinating. This in turn allows the computer to learn completely by itself by analyzing tons of information that allows it to recognize human behaviors.These three researchers have accomplished more in a decade than any other scientists have in five decades. They have phenomenally shifted the archetype of science forwarding the development of tech such as face recognition systems, warehouse robots and self driving cars. These researchers ultimate goal is to have machines at operate at the level of true human understanding. Some may rejoice, other may look at it in dismay but regardless as the years go by this technology advances.
    In my humblest opinion I think that artificial intelligence will definitely surpass the expectations humans have set for them. This also raises the question of how human like do we actually want our computers to think. Humans are anything but perfect and say for example that artificial intelligence is given the task of analyzing data such as world wars and human violence. Will this computer will then utilize its neural network and start to mic-mick this behavior. What procedure do we have set in place in event of such an emergency? There is a ton of money going into the research of neural networks with advocate with huge companies like Google, IBM, and Microsoft. With that being said there must be some type of deactivation procedure in case of such emergency. I would not be surprised if there is not because this research is still fairly in its infancy. I wonder how will take these place of Dr. LeCun, Dr. Bengio and Dr. Hinton when they finally decide to pass the torch. As it is said in this article these systems are “still a very long way from true intelligence.”

  6. The problem with AI is that people are constantly finding ways to replace humans in the jobs and day to day lifestyles that people live. Each of the new innovations mentioned: face-recognition services, talking digital assistants, warehouse robots and self-driving cars, all have benefits, but many disadvantages. Facial recognition services are good for easy access to whatever you try to get into, phone, laptop, other. It helps to easily access whatever you need. It can help increase security by allowing police and government agencies track potential threats. Facial recognition is also preferred over fingerprint scanning by more people. That said, it is also a bad thing this works well. Using facial recognition gives people far less privacy. If government agencies use it, they will be able to track everyone from all around the world which can be threatening to everyone. If everyone uses it, companies like Facebook will also be able to track everyone also, which will give Zuckerberg even more power than he already has and its not like he needs any more of it. Talking digital assistants are interesting to have because they can talk back to you. You can ask whatever question you need like “whats the weather, or whats in the news” and the assistant will answer in seconds by finding related sources to answer your questions. That said, it is also a privacy matter because you will need to turn on location services in order to get news in your area which also affects privacy. Warehouse robots are fairly good idea. Nobody likes to work in warehouse conditions and it pays very little for the conditions and what that is don there. Trust me, I know. People want to work somewhere that pays more and is not as physically demanding. However, people do need jobs sometimes to pay for living expenses. Even though you will not be making much of a living, robots will take over the jobs and many people will be left with nothing. Self driving cars might be the worst on this list. There are no real advantages to it. In order for the car to drive itself, it needs your location and that violates privacy. It will put many truck drivers out of jobs and self driving cars have proven to show they have many difficulties stopping when they should. They are absolutely the worst thing that society can have because it will put many drivers out of work, is still dangerous, and violates privacy. Overall, all these have problems and benefits, except for the self driving cars which are absolutely the worst idea with no benefits whatsoever.

  7. Neural networks appear to be the wave of the future in the technological industry. This saves scientists tons of time because now they don’t have to worry about inputting all of the code because the AI can teach itself by surveying mass amounts of data. This speed up in the process allows scientists to complete experiments more quickly which will be more efficient. I love advances in technology but, it is concerning when you look toward the future. For one, AI are quickly becoming much more efficient than humans which will job loss. Along with this there is also the imminent fear of self-awareness. If the AI can learn all these things from mass data and we are basing the design of the neural network off of the human brain, then why couldn’t it become self-aware? With becoming self-aware comes a plethora of problems and although it is something that probably won’t happen in our life-times, we should still be concerned about it.
    With the bad also comes the good. The good is that the AI can be produced much quicker and they will work much more efficiently. This also makes the AI more diverse and you can essentially make a bot that can do anything. All that you need to do is give the AI a large sample pool of what you want and allow the robot to learn. This will be great for completing tasks that are seen as annoying to humans or dangerous to humans. Of course, this is all hypothetical and are all thing that will happen down the road but for now we have small victories to look forward to. For example, we can now learn even more about AI in a much shorter amount of time. We also can tweak the neural system now in order to make it even better for the future. We also now have the ability to make technological advances much quicker than ever before. The neural networks are a cornerstone of the future of AI. With all the other technologies being developed right now there is no telling what could come from the implementation of neural networks.

  8. Drs. Hinton, LeCun and Bengio have completely accelerated the technology for the upcoming years. For so long we have been anticipating a new wave of technology, whether in the medical field or consumer field, but nothing has been more sought after than AI technology. For years professors around the world have been working with the biggest brands to see who will be the first to implement this new wave in their products. These three absolutely brilliant humans have finally done so, but there are definitely risks along the way although it is fascinating. Creating a self learning technology that works on neural networks is genius. It is almost like the created life and it will grow and learn as it matures. This will save so much time for anyone in the IT business as they won’t have to input codes, or scan large data for answers. All they will have to do is quite literally talk to a machine that will give them the precise answer. With each doctor signing working contracts with Google, Facebook, IBM and Microsoft, I am positive this will be implemented into phones and computers in the next 5 to 10 years.
    What scares me and many people who don’t know as much as some in the technological fields is whether this will take away from human errors. Without errors in the workplace or really anywhere, how will new companies emerge and how will we develop as a nation? The downfall of a company has allowed new people with brighter ideas to take charge of the market, like Steve Jobs did with Apple when Blackberry and Microsoft weren’t changing their philosophies. Will AI now know what to do next, thus never failing companies or will there have to be a restriction as to how far these machines can plan for humans.

  9. A neural network is a very intriguing technological development. The fact that this was a brainchild from the 1970’s is mind-blowing, because there were no computers or machines that could have even supported complicated algorithms that would be required. The most popular advancements included facial recognition technologies, talking digital assistants, self-driving cars, and warehouse robots. All of these advancements proved to be industry shakers and job takers. These three scientists who have dedicated decades to this are still not satisfied with their work. They were questioned even by their own mentors if their ideas were realistic and could be achieved. Once they started having success with written data and simple training data, they at least knew they had something to work with.
    Banks began to use their technology and 10% of America’s written checks were being read through their tech. By 2010, their work had finally begun to pay off, with a lot of development in speech recognition. These geniuses immediately caught the attention of big tech companies, which is no surprise. Currently, they are employed by Facebook, Google, and Microsoft (1 in each company). Of course, this may raise some eyebrows for people like us who have been educating ourselves with data mining techniques. This technology has all the potential to be used in an invasive manner. Knowing what we know, I sure hope that these scientists remain morally sound in their developments and try not to exploit consumers. However, with the ease that these companies steal our information, I would not be surprised if they are on the forefront of data collection. This AI technology is already taking the world by storm, and they are not done. Dr. Bengio plans on creating machines that operate at levels of human understanding.

  10. We’ve talked about AI dozens of times before in not only this class, but in several of my other classes the past few semesters. Of course, it’s a hot-button topic. Every time we discuss the topic, though, I become more and more apprehensive. What struck out to me the most while reading the article wasn’t the amazing advancements made in the field. No, amazing advancements have been made about every second of my lifetime relative to the past couple centuries. What stuck out the most to me was this line: “By analyzing thousands of old phone calls, for example, it can learn to recognize spoken word.” I think it’s because, up until this point, I never really reflected on just how much data is processed. The fact that thousands of old phone calls specifically are being processed shows that, not only is it new data being processed, but existing data as well. AI will be much more capable, and perhaps more dangerous to the current workforce. If AI is being produced with such innate capabilities, I fear for the structural change that will inevitable take place with their advent, and just how great the magnitude of unemployed and discarded employees will be. Of course, a step toward scientific progression is inevitable as well; humans are incapable of stopping their curiosity and need for growth. However, I personally believe that the rate in which we are progressing technologically is too quick for our general society to catch up with logistically, and in terms of resources. AI, whether by employment or SkyNet, will be the downfall of society.

  11. A neural network is a computer system modeled on the human brain and nervous system. This system has been worked on for more than 50 years. What Dr. Hinton, Dr. LeCun, and Dr. Bengio created shaped the way for face recognition services, talking digital assistants, warehouse robots, and self-driving cars. The way it works is that it analyzes mass amounts of data that has been given to it and is able to recognize it when given a different form of that data. An example would be feeding the system with old phone calls so that it can recognize spoken words. When the system was first made, it would only work with some data sets because you needed large amounts of data for it to recognize some of it.
    To see that this became an idea in the 1970s is a little insane because computers were barely a thing and people were already thinking about ways to make technology that recognizes things like spoken words and put them in a database. This idea and the development of it paved the way for all of the technology that involved artificial intelligence. The way that technology advanced since then is scary because now we have artificial intelligence that recognizes your face to unlock your phone or be able to be recognized by a software and have you get tagged in a picture. There are some dangers to this because we are in an era where artificial intelligence is able to take someone’s face, put them on the face of someone else, and have them speak as if the person is speaking. A lot of harm can come from this, but the idea that started all of this was just to have machines recognize what was around them.

  12. During our classes, it has not been uncommon for the topic of artificial intelligence, or AI as it is commonly called, to surface as the heart of the discussion. Just recently, we had conversed about how AI’s are trained – through us. Have you ever signed into a website, but first have had to prove that you’re not a robot? “Select all the images that have a street sign in them.” Do you ever stop to think about why you would have to do that? It’s not a safeguard to prevent robots from hacking into your account – instead it is the process in which we train AI’s. Historically, AI’s have been very objective creatures, able to do simple reading and mathematics. However, when it comes to the identification of something that has differentiated versions, AI is looking to expand. How does an AI know the difference between one dog and another? We are their teachers. Think about the ten seconds you spend selecting those images with street signs – now imagine millions of others doing the exact same thing. You think an AI would get pretty good at recognizing what a street sign is?

    To dive back into the context of the article a little bit more, three artificial intelligence pioneers have been recognized for their astounding work in the pursuit of a technological idea known as neural networks. Modeled somewhat after neuron processing in the human brain, this idea analyzes myriads of information in order to perform discrete tasks. An example given by the article was that through usage of this mathematical system, an AI could listen to thousands of old phone conversations and at the end of that be able to understand spoken language. The reason why this is so revolutionary is because it allows for more rapid advancement of technology. What I mean is that by the integration of these neuron networks, AI’s need not rely on coders as much to help them develop a certain behavior – instead they can develop their own behavior. While the research only worked well in areas where there was a lot of data to be analyzed, there is no limit as to what extent AI’s capabilities can adapt to. In fact, the scientists that implemented this research program, believe that with an increase in the amount of data an AI can study, it can learn to identify hand writing, the way people speak and people’s faces and objects at a much more accurate rate than in the past.

    However, what is interesting to note is how thinking has evolved over the years as it pertains to artificial intelligence. In the 70s, Geoffrey Hinton, one of the pioneers of neuron processing, explained how even his Ph.D. adviser questioned his embracement of AI. I just think it is quite astonishing to think how far we have come in society. Though there are still doubters when it comes to how AI will start to revolutionize our lives, it is important to recognize the growing roles that artificial intelligence will have in the coming future, and continually adapt to make sure they support our lives, not overrule them.

  13. When it comes to artificial intelligence, our nation is attempting to implicate it in all forms of life. Whether it be on our cellphones, computers, our automobiles or devices that our used around the house like amazons “Alexa” or googles “Home”, the technology used in AI is growing rapidly and becoming more complex day by day. While reading this article, you can’t help but see how much work used to go into the coding and construction of an artificial intelligence system. Each algorithm had to be put in manually in order to complete simple menial tasks. This process would have caused for a lack of range as to what these intelligences could do. Now, this team that is introduced in the article has begun to make the artificial intelligence more self-sufficient than ever. They have created a way to make these programs run through data to teach themselves how to pronounce, recall, read writing and who knows what else is in store with such programs. As we have talked about in class, AI is becoming very prominent in our daily lives and one day it will soon have more impact in the work places then ever before and after reading this article it seems this day is closer than we would have imagined. The problems that could come along with these advancements involve way more repercussions than we initially may see. It would come with a loss of jobs, political outbreak because of this, lower wages because a robot could do the same work faster and cheaper, and many others. This is not to say I am against advancements because productions in our nation will skyrocket once artificial intelligence takes over and all of those problems, I mentioned would get taken care of as they were thrown at us. Overall, this article shows how artificial intelligence is becoming more prominent in our world and it is up to us what side we wish to take and to prepare for our future careers working side by side with incredibly smart machines.

  14. It is no question that technology has taken over our lives and is now controlling and identifying our every move. This science of Neural Networking is a dangerous one, putting everyday individuals at risks of identity theft and misrepresentation. These three researches have been given praise for their accomplishments in their field, and it is no debate that their work has altered technology and AI. Their work has improved our understanding and technology in facial recognition, talking digital assistants, robots and even self driving cars, but where do we draw the line. It is also no contest that large companies, such as Apple and Facebook, are using these services to their own advantage. I don’t find any coincidence that Dr. Hinton is now working at Google and Dr. LeCun is working for Facebook. These two powerhouses have been under the spotlight of the digital privacy debate for years and there is no question that they are not using this research to increase the digital privacy of consumers. The idea of the neural network is a system in which data can now analyze our every move. One of the most alarming parts of this is the improvement of facial recognition. Now, you can be identified in any part of the world just based on the outline of your face and other data. Now, companies like Google and Facebook, can track your everyday routine, using this to their advantage. It used to be that when we were looking at something online and an add popped up, but now, our face is being used in order to determine things like where is the next family vacation, or recognizing health patterns.

    In my opinion, a line has been crossed. I have said multiple times that there is nothing that I need to hide, and this is true; however, it is not within Facebook or Googles’ power that they can identify me and use that to show me the best new ads for something. This is just one of the greatest concerns of the digital privacy debate. At first, it was just simple information being used, but now, neural networking can track our individual behaviors. So what does this mean? This means that there is no longer a boundary between the consumer and the producer. There is no boundary from a private citizen and a public institution. There needs to be laws passed in order to protect the private individual. In order to better the relationship between large companies and the consumer again, this development needs to be stopped.

  15. Over the past decade, artificial intelligence has played a huge in the world’s economy now and will continue to get even bigger as more time passes on. The idea of a neural network, which according to the article is technology that can complete certain discrete tasks based on the amount of data it has. The less amount of the data a neural network has, the less number of tasks that it can do. On the other hand, the more data it has, the neural networks will be able to complete more tasks. This was the start of the rise of artificial intelligence and what it has become in today’s world is nothing short of incredible. What Doctors Hinton, LeCun, and Bengio have done is spectacular. In terms of the tasks, at first Artificial Intelligence could go through and read handwriting and letters. It could not do the things that AI does today like identifying images and facial recognition. However, that changed and AI has the ability to do a lot of good things. In my opinion, you can argue from both sides whether or not artificial intelligence is good for the economy. From a business perspective, using artificial intelligence is definitely something that is very useful. Artificial intelligence can produce products, analyze data, and do many other tasks at a more effective rate that what human labor does. Unfortunately, people who work on the assembly lines in factories or drive trucks to deliver products are no longer needed to do their jobs. Why? Artificial intelligence is taking over. If I were to get laid off from my job and be replaced by a robot who could do the same job as me, I would not be very happy with that. Businesses are employing artificial intelligence to replace humans to increase productivity to therefore increase profits. Labor costs would also be reduced as a result of less human labor in businesses. However, artificial intelligence could be used to benefit the healthcare industry. AI would be able to detect unknown diseases that doctors or nurses would normally miss. Is there a limit to the amount of artificial intelligence? I think that there should be, but one thing is certain. Artificial intelligence will be around for a very long time.

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