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) …
A camera films Dr. Emma Fisher, an astronaut aboard what seems to be an otherwise empty International Space Station, as she floats through the facility's tangled modules just after some horrible accident. The situation looks bleak: the rest of the crew is missing, and the ISS is no longer in Earth orbit. Fisher must piece together what happened and why. Wires creep like blue veins into a centralized hub, connecting the live feed to a station-wide artificial intelligence system called "S.A.M." As the game begins, Fisher's trapped in a station module, and needs S.A.M.'s help to escape -- but moreover, S.A.M. needs her help, too.
Assigning female genders to digital assistants such as Apple's Siri and Amazon's Alexa is helping entrench harmful gender biases, according to a UN agency. Research released by Unesco claims that the often submissive and flirty responses offered by the systems to many queries – including outright abusive ones – reinforce ideas of women as subservient. "Because the speech of most voice assistants is female, it sends a signal that women are obliging, docile and eager-to-please helpers, available at the touch of a button or with a blunt voice command like'hey' or'OK'," the report said. "The assistant holds no power of agency beyond what the commander asks of it. It honours commands and responds to queries regardless of their tone or hostility. In many communities, this reinforces commonly held gender biases that women are subservient and tolerant of poor treatment."
Researchers have identified how the human brain is able to determine the properties of a particular object from touch alone, a so-called inner pickpocket trait. This so-called inner pickpocket trait is inherent in all of us, they say, and is the reason a thief can pilfer a handbag and instantly pull out the most valuable item. It relies on the brain's ability to break up a continuous stream of information and turn it into smaller chunks. This manifests itself for professional pickpockets as being bale to interpret the sequence of small depressions on their fingers separate well-defined objects. 'Notably, the participants in our study were not selected for being professional pickpockets - so these results also suggest there is a secret, statistically savvy pickpocket in all of us,' said Professor Máté Lengyel from the University of Cambridge, who co-led the research.
Drones and self-driving cars may soon come with'spidey' senses. That's according to engineers in America, who believe the unmanned machines would benefit from sensory detectors similar to those often seen in arachinds. Specifically, they're referring the hairs on a spider's legs, which are linked to special neurons called mechanoreceptors, which flag-up danger through vibrations. If machines had similar characteristics, they'd be able to navigate more effectively in dangerous environments. Until now, sensor technology hasn't always been able to process data fast enough, or as smoothly, as nature.
NASA's next trip to the moon will entail 37 separate launches over a decade and culminate in the construction of a moon base by 2028, according to leaked documents that detail the agency's'Artemis' plan. Information on the nascent mission come from documents obtained by Ars Technica, and, for the first time, show a detailed glimpse of America's first human-led mission to the moon since 1972. In a graphic, NASA breaks down a year-by-year guide of the construction of the'Gateway' a space station and waypoint on the way to the moon, human test flights, and a lunar landing slated for 2024. Russia and the United States are cooperating on a NASA-led project to build the first lunar space station, codenamed the Lunar Gateway. The agreement, signed in September 2017, is part of a long-term project to send humans to Mars.
Surveillance isn't the only application of China's advanced facial recognition software. Conservationists are now using the technology too, as a tool to help protect wild panda populations. According to a report from Xinhua News, researchers at the China Conservation and Research Center for Giant Pandas in Chengu have begun using facial recognition software to identify the often similar-looking faces and markings of wild pandas. Giant pandas are the latest subject of China's facial recognition software. Conservationists are now using the technology to monitor and track the animals.
Abstract: In this work, we propose a non-autoregressive seq2seq model that converts text to spectrogram. It is fully convolutional and obtains about 17.5 times speed-up over Deep Voice 3 at synthesis while maintaining comparable speech quality using a WaveNet vocoder. Interestingly, it has even fewer attention errors than the autoregressive model on the challenging test sentences. Furthermore, we build the first fully parallel neural text-to- speech system by applying the inverse autoregressive flow (IAF) as the parallel neural vocoder. Our system can synthesize speech from text through a single feed-forward pass.
Abstract: Gaussian processes (GPs) are flexible models with state-of-the-art performance on many impactful applications. However, computational constraints with standard inference procedures have limited exact GPs to problems with fewer than about ten thousand training points, necessitating approximations for larger datasets. In this paper, we develop a scalable approach for exact GPs that leverages multi-GPU parallelization and methods like linear conjugate gradients, accessing the kernel matrix only through matrix multiplication. By partitioning and distributing kernel matrix multiplies, we demonstrate that an exact GP can be trained on over a million points in 3 days using 8 GPUs and can compute predictive means and variances in under a second using 1 GPU at test time. Moreover, we perform the first-ever comparison of exact GPs against state-of-the-art scalable approximations on large-scale regression datasets with $104-106$ data points, showing dramatic performance improvements.
I saw a cool take yesterday, that we listen to music because it's a meaningful (it has patterns) adversarial example to our neural network. If we humans fit a good model of the world through exploration (I think the free energy principle says something like that? I don't totally get it), then we need to have incentives to find examples that counter our model, since that's the way we improve. Maybe art in general exploit something like that. Except some art is more simply explained because it just exploits things that help us/our genes survive (beautiful bodies, green sceneries).
The battle for future markets and bigger market shares is in full swing. The world's most influential companies are in a steady race to develop better automated systems and, in turn, boost artificial intelligence technology – taking them ahead of their competitors. By 2020, AI is expected to turn over more than 21 billion euros worldwide. However, further development of machine learning and artificial intelligence technologies seems to be blocked by a major obstacle: data privacy. The more data is consumed, the better these computer algorithms can recognize and capture patterns in the data.