NASA's launch of the Mars Science Laboratory -- hampered by technical difficulties and cost overruns -- has been delayed until the fall of 2011, NASA officials said at a news conference Thursday in Washington.
Researchers have developed an automated way to design customized hardware that speeds up a robot's operation. The system, called robomorphic computing, accounts for the robot's physical layout in suggesting an optimized hardware architecture.
Patients with motor dysfunctions are on the rise across Japan as its population continues to age. A researcher has developed a new method of rehabilitation using virtual reality to increase the sense of agency over our body and aid motor skills.
Computer scientists developed a deep learning method to create realistic objects for virtual environments that can be used to train robots. The researchers used TACC's Maverick2 supercomputer to train the generative adversarial network. The network is the first that can produce colored point clouds with fine details at multiple resolutions.
Researchers present an optical flow-based learning process that allows robots to estimate distances through the visual appearance (shape, color, texture) of the objects in view. This artificial intelligence (AI)-based learning strategy increases the navigation skills of small flying drones and entails a new hypothesis on insect intelligence.
Scientists are combining artificial intelligence and advanced computer technology with biological know how to identify insects with supernatural speed. This opens up new possibilities for describing unknown species and for tracking the life of insects across space and time.
Computer-based artificial intelligence can function more like human intelligence when programmed to use a much faster technique for learning new objects, say two neuroscientists who designed such a model that was designed to mirror human visual learning.
An international team of researchers, including Professor Roberto Morandotti of the Institut national de la recherche scientifique (INRS), just introduced a new photonic processor that could revolutionize artificial intelligence, as reported by the prestigious journal Nature.
We are fascinated by machines that can control cars, compose symphonies, or defeat people at chess, Go, or Jeopardy! While more progress is being made all the time in Artificial Intelligence (AI), some scientists and philosophers warn of the dangers of an uncontrollable superintelligent AI. Using theoretical calculations, an international team of researchers shows that […]
Like a longtime couple who can predict each other's every move, a new robot has learned to predict its partner robot's future actions and goals based on just a few initial video frames. The study is part of a broader effort to endow robots with the ability to understand and anticipate the goals of other […]
A Swinburne-led team has demonstrated the world's fastest and most powerful optical neuromorphic processor for artificial intelligence. The neuromorphic processor operates faster than 10 trillion operations per second and is capable of processing ultra-large scale data.
Researchers have proposed a new principle by which active matter systems can spontaneously order, without need for higher level instructions or even programmed interaction among the agents. And they have demonstrated this principle in a variety of systems, including groups of periodically shape-changing robots called 'smarticles.'
A new device developed by engineers can recognize hand gestures based on electrical signals detected in the forearm. The system, which couples wearable biosensors with artificial intelligence (AI), could one day be used to control prosthetics or to interact with almost any type of electronic device.
A model based solely on the past 40 years of weather events uses 7,000 times less computer power than today's weather forecasting tools. An A.I.-powered model could someday provide more accurate forecasts for rain, snow and other weather events.
New research offers clues to what goes on inside the minds of machines as they learn to see. Instead of attempting to account for a neural network's decision-making on a post hoc basis, their method shows how the network learns along the way, by revealing how much the network calls to mind different concepts to […]
Neuroscientists have found reading computer code does not rely on the regions of the brain involved in language processing. Instead, it activates the 'multiple demand network,' which is also recruited for complex cognitive tasks such as solving math problems or crossword puzzles.
Scientists often look to nature for cues when designing robots - some robots mimic human hands while others simulate the actions of octopus arms or inchworms. Now, researchers have designed a new soft robotic gripper that draws inspiration from an unusual source: pole beans.
Researchers are embracing chaos and nonlinear physics to create insectlike gaits for tiny robots -- complete with a locomotion controller to provide a brain-machine interface. Biology and physics are permeated by universal phenomena fundamentally grounded in nonlinear physics, and it inspired the researchers' work. The group now describes using a system of three nonlinear differential […]
A research team has developed a new range of strain sensors that are 10 times more sensitive when measuring minute movements. These sensors are ultra-thin, battery-free and can transmit data wirelessly, making them attractive for a wide range of applications.
Recommender systems may be the most common type of predictive model that the average person may encounter. They provide the basis for recommendations on services such as Amazon, Spotify, and Youtube. Recommender systems are a huge daunting topic if you’re just getting started. There is a myriad of data preparation techniques, algorithms, and model evaluation […]
Regression refers to predictive modeling problems that involve predicting a numeric value. It is different from classification that involves predicting a class label. Unlike classification, you cannot use classification accuracy to evaluate the predictions made by a regression model. Instead, you must use error metrics specifically designed for evaluating predictions made on regression problems. In […]
Activation functions are a critical part of the design of a neural network. The choice of activation function in the hidden layer will control how well the network model learns the training dataset. The choice of activation function in the output layer will define the type of predictions the model can make. As such, a […]
Function optimization involves finding the input that results in the optimal value from an objective function. Optimization algorithms navigate the search space of input variables in order to locate the optima, and both the shape of the objective function and behavior of the algorithm in the search space are opaque on real-world problems. As such, […]
Gradient descent is an optimization algorithm that follows the negative gradient of an objective function in order to locate the minimum of the function. A limitation of gradient descent is that a single step size (learning rate) is used for all input variables. Extensions to gradient descent like AdaGrad and RMSProp update the algorithm to […]
Optimization is a field of mathematics concerned with finding a good or best solution among many candidates. It is an important foundational topic required in machine learning as most machine learning algorithms are fit on historical data using an optimization algorithm. Additionally, broader problems, such as model selection and hyperparameter tuning, can also be framed […]
How to Optimize a Function with One Variable? Univariate function optimization involves finding the input to a function that results in the optimal output from an objective function. This is a common procedure in machine learning when fitting a model with one parameter or tuning a model that has a single hyperparameter. An efficient algorithm […]
Applied machine learning is typically focused on finding a single model that performs well or best on a given dataset. Effective use of the model will require appropriate preparation of the input data and hyperparameter tuning of the model. Collectively, the linear sequence of steps required to prepare the data, tune the model, and transform […]
Semi-supervised learning refers to algorithms that attempt to make use of both labeled and unlabeled training data. Semi-supervised learning algorithms are unlike supervised learning algorithms that are only able to learn from labeled training data. A popular approach to semi-supervised learning is to create a graph that connects examples in the training dataset and propagates […]
Multinomial logistic regression is an extension of logistic regression that adds native support for multi-class classification problems. Logistic regression, by default, is limited to two-class classification problems. Some extensions like one-vs-rest can allow logistic regression to be used for multi-class classification problems, although they require that the classification problem first be transformed into multiple binary […]
By John P. Desmond, AI Trends Editor The AI Infrastructure Alliance is taking shape, adding more partners who sign up to the effort to define a “canonical stack for AI and Machine Learning Operations (MLOps).” In programming, “canonical means according to the rules,” from a definition in webopedia. The mission of the organization also includes, according to its […]
By AI Trends Staff On the verge of a new era of healthcare in which AI can combine with data sharing to deliver many new services, healthcare organizations need to earn the trust of patients that their data will be used properly. That was a message delivered by speakers on healthcare and AI topics at […]
By AI Trends Staff With remote learning happening for students of all ages during the pandemic area, new technologies incorporating AI—including voice, augmented reality and virtual reality—are being used more widely to enable teaching. “Some 1.2 billion children have been out of school during the pandemic year, and that has led to technology driving change […]
By Lance Eliot, The AI Trends Insider We all seem to know what a red stop button or kill switch does. Whenever you believe that a contraption is going haywire, you merely reach for the red stop button or kill switch and shut the erratic gadgetry down. This urgent knockout can be implemented via a […]
By John P. Desmond, AI Trends Editor Mary Barra, Chairman and CEO of General Motors outlined GM’s move into all-electric vehicles including autonomous self-driving cars, in a keynote speech at the Consumer Electronic Show held virtually this week. While global market penetration of all-electric vehicles stands at about three percent today, “We believe that is […]
By AI Trends Staff The Best AI Papers of 2020 were called out by a writer at GitHub, who posts a video explanation link to each one, a link to a more in-depth article and some code. “In the field of AI, many important aspects were highlighted this year, like the ethical aspects and important biases,” […]
By AI Trends Staff The role of the Chief Data Scientist is needed to help the Chief Technology Officer bridge to business managers who are defining how AI is to deliver on the company’s business strategy. The required amount of guidance and monitoring of data scientists is not likely to happen from the CTO’s office, […]
By John P. Desmond, AI Trends Editor The most popular articles, blog posts, and downloaded publications of 2020 published on the Amazon Science website can serve as an update on AI work at Amazon. The most popular article of 2020 was an account of advances in text-to-speech technologies. Amazon’s Alexa voice service has been on the market for […]
By Lance Eliot, the AI Trends Insider AI is starting to apologize. That’s the latest trend for AI that directly interacts with people. The notion seems to be that if the AI has to deliver unfavorable news or appears to have made a potential mistake, it ought to be civil about the matter and emit an […]
By John P, Desmond, AI Trends Editor Experts offering IT acquisition advice to the incoming Biden administration suggest building on the Trump Administration’s AI and tech policies when they make sense, while forging a path to a new set of priorities. They also foresee a drift toward acquiring more IT services and throttling back in-house application […]
Scientists combine scanning tunneling microscopy with ultrafast spectroscopy to image the motion of electrons with unprecedented resolution, which may lead to advances in semiconductors and optoelectronics.
Researchers have found a way to grow a single crystalline layer of alpha-aluminum gallium oxide that has the widest energy bandgap to date - a discovery that clears the way for new semiconductors that will handle higher voltages, higher power densities and higher frequencies than previously seen.
Researchers have developed an electrochromic hydrogen-bonded organic frameworks film with long cycle life, facile modification, easy recycling and regeneration prepared via electrophoretic deposition rapidly and facile.
A new X-ray laser oscillator generates types of pulses that were never before possible. The pulses are stable, intense, and of ultrashort duration and have a well-defined wavelength. This ability opens new possibilities in experiments and research.
Transport processes are ubiquitous in nature but still raise many questions. Scientists have now developed a new method that allows them to observe a single charged particle on its path through a dense cloud of ultracold atoms.
New photo-ferroelectric materials allow to store information in a non-volatile way using light stimulus. The idea is to create energy efficient memory devices with high performance and versatility to face the challenges of the current society.
Scientists have discovered a new light-induced switch that twists the crystal lattice of the material, switching on a giant electron current that appears to be nearly dissipationless. The discovery was made in a category of topological materials that holds great promise for spintronics, topological effect transistors, and quantum computing.
A pulsed-laser repetition rate of 57.8 GHz was achieved by inserting a resonator containing graphene. The limitations of the manufacturing process were overcome by directly synthesizing graphene onto standard copper wires.