If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Time series forecasting has gained lots of attention recently; this is because many real-world phenomena can be modeled as time series. The massive volume of data and recent advancements in the processing power of the computers enable researchers to develop more sophisticated machine learning algorithms such as neural networks to forecast the time series data. In this paper, we propose various neural network architectures to forecast the time series data using the dynamic measurements; moreover, we introduce various architectures on how to combine static and dynamic measurements for forecasting. We also investigate the importance of performing techniques such as anomaly detection and clustering on forecasting accuracy. Our results indicate that clustering can improve the overall prediction time as well as improve the forecasting performance of the neural network. Furthermore, we show that feature-based clustering can outperform the distance-based clustering in terms of speed and efficiency. Finally, our results indicate that adding more predictors to forecast the target variable will not necessarily improve the forecasting accuracy.
We may not have flying cars, but we could soon have'talking' ones. Elon Musk teased an upcoming Tesla feature that combines external speakers and artificial intelligence, enabling vehicles to'speak' to pedestrians. And the eccentric billionaire said that as well as conversing with pedestrians, drivers could be able to emit a fart noise from the speakers as well. Musk shared a clip of the technology on his personal Twitter page, which highlights a Model 3 driving through the streets and speakers playing'Well don't just stand there staring. 'Teslas will soon talk to people if you want,' he said in the tweet on Saturday.
During Tesla's Autonomy Day last April, Director of AI Andrej Karpathy joked that the attendees of the event only used a pair of cameras to navigate themselves to the venue. Emphasizing this point and Tesla's aversion to LiDAR, the AI Director even joked that the attendees must not have shot lasers from their eyes when they were making their way to the event. These jokes, while lighthearted, show Tesla's all-in bet on Elon Musk's idea that a suite of cameras and a Neural Network are enough to teach a fleet of vehicles how to drive autonomously. Unlike self-driving companies such as Waymo and Cruise, Tesla is intent on not using LiDAR, a component that is pretty much ubiquitous among firms developing FSD technology. Musk has proven quite unforgiving for LiDAR, calling it a "fool's errand" and "stupid" if used for cars.
Elon Musk has been receiving a lot of mail from Germany lately, with government ministers trying to flatter the tech entrepreneur in an effort to promote their states. Almost as soon as the Tesla CEO announced his intention to build a "Gigafactory" in Europe, German state governments began courting Musk like a horde of real estate agents eying a very solvent potential customer. "Lower Saxony," Bernd Althusmann (CDU), the economics minister of that state, wrote, "is one of the world's top regions in the automotive industry." He argued that "trans-European transport routes" cross through it and that the state is leading the way in terms of "electromobility, traffic telematics and autonomous driving." The minister, whose state is home to Volkswagen, said he would be pleased to explain all the advantages "in a personal conversation."
In this article, we propose a novel probabilistic framework to improve the accuracy of a weighted majority voting algorithm. In order to assign higher weights to the classifiers which can correctly classify hard-to-classify instances, we introduce the Item Response Theory (IRT) framework to evaluate the samples' difficulty and classifiers' ability simultaneously. Three models are created with different assumptions suitable for different cases. When making an inference, we keep a balance between the accuracy and complexity. In our experiment, all the base models are constructed by single trees via bootstrap. To explain the models, we illustrate how the IRT ensemble model constructs the classifying boundary. We also compare their performance with other widely used methods and show that our model performs well on 19 datasets.
According to a survey released by Bloomberg, the majority of Tesla Model 3 owners believe Autopilot makes them safer. The survey includes responses from 5,000 owners. Although the overall sense is that the software improves safety, there were instances when drivers were unhappy with how it operated. Self-driving technologies are trickling down into more cars every model year. Tesla hasn't shied away from rolling them out across its lineup.
In this work, a novel approach is proposed for joint analysis of high dimensional time-resolved cardiac motion features obtained from segmented cardiac MRI and low dimensional clinical risk factors to improve survival prediction in heart failure. Different methods are evaluated to find the optimal way to insert conventional covariates into deep prediction networks. Correlation analysis between autoencoder latent codes and covariate features is used to examine how these predictors interact. We believe that similar approaches could also be used to introduce knowledge of genetic variants to such survival networks to improve outcome prediction by jointly analysing cardiac motion traits with inheritable risk factors.
Elon Musk has been ridiculed for claiming he's on the brink of perfecting a fleet of self-driving taxis after Tesla owners reported that their cars crash on summon mode. The CEO of Tesla says that the fleet will be ready by the end of next year, but that has been called into question after the release of Tesla's Smart Summon technology. Raj Rajkumar, from Carnegie Mellon University, says that the California company's new feature is'far from perfection' and he can'only laugh' at Musk's timeline. Many Tesla owners using the summon function, which calls their car to them without anyone in, have experienced several close calls and nasty fender benders. The release of Tesla's Smart Summon technology has CEO Elon Musk promising a fleet of self-driving taxis by the end of next year.
A link has been posted to your Facebook feed. Tesla has won the highest safety honor from the Insurance Institute for Highway Safety for the first time in the electric vehicle maker's history. The Tesla Model 3 earned the 2019 Top Safety Pick award from the organization after achieving a "good" performance in all six IIHS crash tests. The compact car also had to perform well in a headlight test and in a test for its frontal-crash prevention systems. The accomplishment reflects a significant endorsement of Tesla's safety systems, which CEO Elon Musk has often touted.
Seemingly, one of the most controversial things about Tesla cars is its Autopilot feature, a driver-assist feature that helps drivers navigate and pilot their vehicle. Oddly, while news of exciting Autopilot features comes out regularly, general information about exactly what Autopilot is, what the options are, and what it can and cannot do seem to be few and far between. I have tried to collect and answer the biggest questions about Autopilot below to help prospective buyers know what the system is and is not, as well as to inform journalists about the system in case they find themselves trying to cover a news story regarding the system. When the next questionable news story comes out, please feel free to link this article for anyone wondering about the system. Please note that all of the below information refers to Tesla vehicles containing Autopilot 2.0 hardware or higher in them (vehicles built since October of 2016). Although, the majority of the information will apply to all Tesla vehicles that are Autopilot enabled.