background preloader

MIT Computer Science and Artificial Intelligence Laboratory

MIT Computer Science and Artificial Intelligence Laboratory
Related:  Evolution of Thinking & ThoughtVeille technologique

The AI Revolution: Road to Superintelligence - Wait But Why PDF: We made a fancy PDF of this post for printing and offline viewing. Buy it here. (Or see a preview.) Note: The reason this post took three weeks to finish is that as I dug into research on Artificial Intelligence, I could not believe what I was reading. It hit me pretty quickly that what’s happening in the world of AI is not just an important topic, but by far THE most important topic for our future. We are on the edge of change comparable to the rise of human life on Earth. — Vernor Vinge What does it feel like to stand here? It seems like a pretty intense place to be standing—but then you have to remember something about what it’s like to stand on a time graph: you can’t see what’s to your right. Which probably feels pretty normal… The Far Future—Coming Soon Imagine taking a time machine back to 1750—a time when the world was in a permanent power outage, long-distance communication meant either yelling loudly or firing a cannon in the air, and all transportation ran on hay. 1. Speed.

Futurist: We'll someday accept computers as human Futurist Ray Kurzweil spoke Monday at the South By Southwest Interactive conference. Ray Kurzweil, the acclaimed inventor and futurist, believes that humans and technology are merging Kurzweil on portentous sci-fi fears about computers: "I don't see it as them vs. us"He spoke to a crowd of more than 3,000 at the South by Southwest Interactive conference Austin, Texas (CNN) -- Any author or filmmaker seeking ideas for a sci-fi yarn about the implications of artificial intelligence -- good or bad -- would be smart to talk to Ray Kurzweil. Kurzweil, the acclaimed inventor and futurist, believes that humans and technology are blurring -- note the smartphone appendages in almost everyone's hand -- and will eventually merge. "We are a human-machine civilization. "If we can convince people that computers have complexity of thought and nuance ... we'll come to accept them as human." "You can start world-changing revolution with the power of your ideas and the tools that everyone has," he said.

Our Evolutionary Journey Neuro Evolving Robotic Operatives Neuro-Evolving Robotic Operatives, or NERO for short, is a unique computer game that lets you play with adapting intelligent agents hands-on. Evolve your own robot army by tuning their artificial brains for challenging tasks, then pit them against your friends' teams in online competitions! New features in NERO 2.0 include an interactive game mode called territory capture, as well as a new user interface and more extensive training tools. NERO is a result of an academic research project in artificial intelligence, based on the rtNEAT algorithm. It is also a platform for future research on intelligent agent technology. The NERO project is run by the Neural Networks Group of the Department of Computer Sciences at the University of Texas at Austin . Currently, we are developing an open source successor to NERO , OpenNERO , a game platform for AI research and education.

AI in 2025 A Non-Mathematical Introduction to Using Neural Networks The goal of this article is to help you understand what a neural network is, and how it is used. Most people, even non-programmers, have heard of neural networks. There are many science fiction overtones associated with them. And like many things, sci-fi writers have created a vast, but somewhat inaccurate, public idea of what a neural network is. Most laypeople think of neural networks as a sort of artificial brain. Neural networks are one small part of AI. The human brain really should be called a biological neural network (BNN). There are some basic similarities between biological neural networks and artificial neural networks. Like I said, neural networks are designed to accomplish one small task. The task that neural networks accomplish very well is pattern recognition. Figure 1: A Typical Neural Network As you can see, the neural network above is accepting a pattern and returning a pattern. Neural Network Structure Neural networks are made of layers of similar neurons. Conclusion

Brain Computing History OVERVIEW OF NEURAL NETWORKS This installment addresses the subject of computer-models of neural networks and the relevance of those models to the functioning brain. The computer field of Artificial Intelligence is a vast bottomless pit which would lead this series too far from biological reality -- and too far into speculation -- to be included. Neural network theory will be the singular exception because the model is so persuasive and so important that it cannot be ignored. Neurobiology provides a great deal of information about the physiology of individual neurons as well as about the function of nuclei and other gross neuroanatomical structures. But understanding the behavior of networks of neurons is exceedingly challenging for neurophysiology, given current methods. Nonetheless, network behavior is important, especially in light of evidence for so-called "emergent properties", ie, properties of networks that are not obvious from an understanding of neuron physiology.

Top notch AI system about as smart as a four-year-old, lacks commonsense Researchers have found that an AI system has an average IQ of a four-year-old child (Image: Shutterstock) Those who saw IBM’s Watson defeat former winners on Jeopardy! in 2011 might be forgiven for thinking that artificially intelligent computer systems are a lot brighter than they are. While Watson was able to cope with the highly stylized questions posed during the quiz, AI systems are still left wanting when it comes to commonsense. To see just how intelligent AI systems are, a team of artificial and natural knowledge researchers at the University of Illinois as Chicago (UIC) subjected ConceptNet 4 to the verbal portions of the Weschsler Preschool and Primary Scale of Intelligence Test, which is a standard IQ test for young children. While the UIC researchers found that ConceptNet 4 is on average about as smart as a four-year-old child, the system performed much better at some portions of the test than others. “All of us know a huge number of things,” says Sloan. Source: UIC

Intelligent Machines: The truth behind AI fiction Image copyright Thinkstock Artificial intelligence (AI) is the science of making smart machines, and it has come a long way since the term was coined in the 1950s. Nowadays, robots work alongside humans in hotels and factories, while driverless cars are being test driven on the roads. Behind the scenes, AI engines in the form of smart algorithms "work" on stock exchanges, offer up suggestions for books and films on Amazon and Netflix and even write the odd article. But AI does not have the greatest public image - often due to sci-fi films that display dystopian visions of robots taking over the world. Over the next week, the BBC will be looking into all aspects of artificial intelligence - from how to build a thinking machine, to the ethics of doing so, to questions about whether an AI can ever be creative. For many, the only reference point they have for AI comes from films. The all-knowing machine Image copyright ALAMY/IBM Hal is perhaps the most famous AI turned bad. The killer robot

Meet the man who has been at the forefront of AI innovation for three decades Geoffrey Hinton was in high school when a friend convinced him that the brain worked like a hologram. To create one of those 3D holographic images, you record how countless beams of light bounce off an object and then you store these little bits of information across a vast database. While still in high school, back in 1960s Britain, Hinton was fascinated by the idea that the brain stores memories in much the same way. Rather than keeping them in a single location, it spreads them across its enormous network of neurons. This may seem like a small revelation, but it was a key moment for Hinton -- "I got very excited about that idea," he remembers. For a good three decades, the deep learning movement was an outlier in the world of academia. While studying psychology as an undergrad at Cambridge, Hinton was further inspired by the realisation that scientists didn't really understand the brain. He doesn't have all the answers yet. But a few resolute researchers carried on. He was right.

Synthetic intelligence Synthetic intelligence (SI) is an alternative term for artificial intelligence which emphasizes that the intelligence of machines need not be an imitation or any way artificial; it can be a genuine form of intelligence.[1] John Haugeland proposes an analogy with simulated diamonds and synthetic diamonds—only the synthetic diamond is truly a diamond.[1] Synthetic means that which is produced by synthesis; combining parts to form a whole, colloquially, a man-made version of that which has arisen naturally. As defined, a "synthetic intelligence" would therefore be man-made, but not a simulation. The term was used by Haugeland in 1986 to describe artificial intelligence research up to that point,[1] which he called "good old fashioned artificial intelligence" or "GOFAI". Sources disagree about exactly what constitutes "real" intelligence as opposed to "simulated" intelligence and therefore whether there is a meaningful distinction between artificial intelligence and synthetic intelligence.

The Current State of Machine Intelligence (The 2016 Machine Intelligence landscape and post can be found here) I spent the last three months learning about every artificial intelligence, machine learning, or data related startup I could find — my current list has 2,529 of them to be exact. Yes, I should find better things to do with my evenings and weekends but until then… Why do this? A few years ago, investors and startups were chasing “big data” (I helped put together a landscape on that industry). What is “machine intelligence,” anyway? I mean “machine intelligence” as a unifying term for what others call machine learning and artificial intelligence. Computers are learning to think, read, and write. What this landscape doesn’t include, however important, is “big data” technologies. Which companies are on the landscape? I considered thousands of companies, so while the chart is crowded it’s still a small subset of the overall ecosystem. The most exciting part for me was seeing how much is happening in the application space.

A Robot With A Simple Form of Consciousness Synopsis A year ago, researchers endowed the walking robot Hector with a simple form of consciousness. Their new research goes a step further and enables Hector to see himself as others see him. Summary Both biologists are involved in further developing and enhancing walking robot Hector’s software.