Commander Stephen Hawking and his space ship the SS Hawking encounter an alien A.I., then race to the edge of the universe, and plunge into an alternate Earth. It's an epic quest to discover the secret of the universe: The Theory of Everything. RIP. Stephen Hawking.
Category:Science Duration:27:13 Series: Stephen Hawking Favorite Places
Do dolphins think the way we do or are their brains wired in a very different way from ours? Will we communicate with them one day? Dolphins have been a source of curiosity to humans and have appeared in our stories and myths for thousands of years. What is the link between our two species? Why do we seem to be so interested and curious about each other?
Category:Science Duration:49:04 Series: Conversations with Dolphins
You find fungi in Antarctica and in nuclear reactors. They live inside your lungs and your skin is covered with them. Fungi are the most under appreciated and unexplained organisms, yet they could cure you from smallpox and turn cardboard boxes into forests. They could even transform Mars into Eden. There are vastly more fungi species than plants and each and every one of them plays a crucial role in life’s support systems. Join us on a journey into the mysterious world of Fungi to witness their beauty, unravel their mysteries and discover how this secret kingdom is essential to life on Earth, and may in fact hold the key to our future.
Predictions underlie nearly every aspect of our lives, from sports, politics, and medical decisions to the morning commute. With the explosion of digital technology, the internet, and 'big data,' the science of forecasting is flourishing. But why do some predictions succeed spectacularly while others fail abysmally? And how can we find meaningful patterns amidst chaos and uncertainty? From the glitz of casinos and TV game shows to the life-and-death stakes of storm forecasts and the flaws of opinion polls that can swing an election, 'Prediction by the Numbers' explores stories of statistics in action. Yet advances in machine learning and big data models that increasingly rule our lives are also posing big, disturbing questions. How much should we trust predictions made by algorithms when we don't understand how they arrive at them? And how far ahead can we really forecast?
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