To celebrate New Scientist magazine's 50th birthday, we are tackling eight of the truly big questions, from free will and reality to life and death If we encountered alien life, chances are we wouldn't recognise it – not even if it were here on Earth, says Robert Hazen However you look at it, the answer seems to be "maybe", says Vlatko Vedral When Winston Churchill took a ride on a new monorail at the Japan-British exhibition of 1910, he was convinced it would revolutionise railways – so what went wrong?
At Lyft, our mission is to improve people's lives with the world's best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization. Data Science is at the heart of Lyft's products and decision-making. As a member of the Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products.
Deep learning is increasingly dominating technology and has major implications for society. From self-driving cars to medical diagnoses, from face recognition to deep fakes, and from language translation to music generation, deep learning is spreading like wildfire throughout all areas of modern technology. But deep learning is not only about super-fancy, cutting-edge, highly sophisticated applications. Deep learning is increasingly becoming a standard tool in machine-learning, data science, and statistics. Deep learning is used by small startups for data mining and dimension reduction, by governments for detecting tax evasion, and by scientists for detecting patterns in their research data.
The researchers used all this data to simulate what would happen if a passenger in seat 14C (an aisle seat) were sick. To be conservative, they used an transmission rate that was four times higher than a real-life example from 1977, when 54 passengers and crew were forced to sit on the tarmac for 4.5 hours and 38 of them became sick with an influenza-like illness as a result.
Robot, voice assistance, instant translation, visual recognition, automated planning and learning, stock market, autonomous car… applying to these and many other fields, innovations related to Artificial Intelligence (AI) are already exist behind the scenes of our daily lives. But its advances also generate possibilities of excesses against which communities of scientists are mobilized.