The concept of randomness is easy to grasp on an intuitive level but challenging to characterize in rigorous mathematical terms. In "Algorithmic Randomness" (May 2019), Rod Downey and Denis R. Hirschfeldt present a comprehensive discussion of this issue, incorporating the distinct perspectives of "statisticians, coders, and gamblers." Randomness is also a concern to "modelers" who depend on simulation models driven by random number generators or analytic models built using probabilistic assumptions. In such cases, the underlying mathematical model is often an ergodic stochastic process, and the issue is whether the output of the simulator's random number generator or the observed behavior of the real-world system being modeled is "random enough" to establish confidence in the model's predictions. In a sense, this highly pragmatic perspective represents a less restrictive approach to the issue of randomness: if any of the strong criteria described by the authors are satisfied, the output of the simulator's random number generator or the observed behavior of the system being modeled should be sufficiently random to establish confidence in a model's predictions.
The consequences of fabricated news stories may have lingering effects on your perception. According to a new study, voters may develop false memories after reading a fake news report. And, they're more likely to do so if the narrative lines up with their own beliefs. Researchers presented over 3,000 eligible voters in Ireland with legitimate and made-up stories ahead of the 2018 referendum on legalizing abortion. In subsequent questioning – and after being told that some of the reports were fake – nearly half of participants reported a memory for at least one of the fabricated events, and many tended to be steadfast in these beliefs.
Science-fiction can sometimes be a good guide to the future. In the film Upgrade (2018) Grey Trace, the main character, is shot in the neck. His wife is shot dead. Trace wakes up to discover that not only has he lost his wife, but he now faces a future as a wheelchair-bound quadriplegic. He is implanted with a computer chip called Stem designed by famous tech innovator Eron Keen – any similarity with Elon Musk must be coincidental – which will let him walk again.
Ever wondered how video-streaming services such as YouTube and Netflix fetch videos that you like? Or how Google and Facebook find stories that are interesting to you? This is because these services are powered by Artificial Intelligence (AI) and Machine Learning (ML) algorithms – These algorithms are coded using a programming language in such a way that they can analyze your behavior at a granular level to find out your interests and preferences. This article focuses on Python programming language and explains why it is the most effective AI and ML language. AI and ML are seeping into nearly every aspect of our lives, helping us in ways that augment our abilities and make us better at what we do.
I see two main points of interest personally. The first is adversarial examples. There have been adversarially robust generative models developed, but it seems to me that there is more to be understood here. Obviously the'adversarial examples are features, not bugs' paper lays out a convincing argument around the theoretical meaning of the problem, but... is there some overarching pattern that can help distinguish useful features from brittle features? The main area I'm personally interested in though (nowhere near knowledgable enough to be caught up with current research, but it's what I'm working towards at the moment) is unsupervised model based reinforcement learning.
Artificial intelligence has promised to revolutionize our lives, taking over the mundane tasks of daily existence, from prewriting "smart" email replies to driving our car through rush hour traffic. In the PR realm, AI has been touted as equal parts something to celebrate (no more manual coverage reports!) and fear (er, so long, means of employment). But the truth, as usual, lies somewhere in between. Some form of intelligent technology is already embedded in the PR industry, from the tools we use to find new audiences and monitor evolving conversations to modern media placement. Bloomberg News uses AI to generate coverage on some 3,500 earnings reports every quarter.
Here's the good news about artificial intelligence: the Terminator vision of the future, where smart machines turn on humanity, is unlikely. But here's the bad news: we could be heading for disaster anyway thanks to this revolutionary technology. That, at least, is the conclusion of the filmmakers behind Machine, who spent the past year researching the state of play in AI in the hope their documentary might provoke some serious thinking on the subject before it's too late. The documentary Machine ponders the ethical questions posed by the rise of artificial intelligence, including the nature of interactions between humans and sexbots.Credit:Finch "There's a lot of decisions we're making right now that will have ripple effects for decades to come," says Justin Krook, the director of the film. "In the whole history of humanity we've never had so much power at our disposal, and we only have one chance to get these decisions right. "People are worried about the robot apocalypse but that's not exactly the biggest threat we're facing here.