Astronomers took centuries to figure it out. But now, a machine-learning algorithm inspired by the brain has worked out that it should place the Sun at the centre of the Solar System, based on how movements of the Sun and Mars appear from Earth. The feat is one the first tests of a technique that researchers hope they can use to discover new laws of physics, and perhaps to reformulate quantum mechanics, by finding patterns in large data sets. The results are due to appear in Physical Review Letters 1. Physicist Renato Renner at the Swiss Federal Institute of Technology (ETH) in Zurich and his collaborators wanted to design an algorithm that could distill large data sets down into a few basic formulae, mimicking the way that physicists come up with concise equations like E mc 2. To do this, the researchers had to design a new type of neural network, a machine-learning system inspired by the structure of the brain. Conventional neural networks learn to recognize objects -- such as images or sounds -- by training on huge data sets.
Between 6,000 and as many as 24,000 people are killed by lightning every year. Switzerland's leading university has found a way to predict when and where lightning will strike to the nearest 10 to 30 minutes and within a radius of 30 kilometres. The method developed by researchers at the federal technology institute ETH Zurich combines standard data drawn from weather stations and artificial intelligence. Lightning is one of the most unpredictable and lethal phenomena in nature. It regulary kills people and animals, sets fire to homes and forests, keeps aircraft grounded and damages power installations.
We recently had the opportunity to catch up with Attila Toth, CEO, zesty.ai, the Silver Winner of the 2019 Zurich Innovation World Championship, to discuss how Artificial Intelligence is impacting the Property & Casualty Insurance market across personal and commercial lines. Click the link to have a listen. You can also read the full transcript of the conversation below. With me today is Attila Toth, CEO of zesty.ai Today we have an interesting show planned for you where we're going to talk about the global insurance industry as it undergoes a digital transformation. As insurance companies find themselves trying to make sense of all these new technologies – artificial intelligence, natural language processing, machine learning, computer vision, – understanding the business case for each can be extremely confusing and daunting. With insurance companies being held to higher customer expectations, the time is now to embrace new technologies to leapfrog the competition. Being status quo is no longer an option. Technology is driving diversity across many industries – insurance included – as it reshapes the value chain. Age-old processes are being disrupted, while new market entrants and changing business models are bringing new threats, as well as opportunities for those who act on them. Some of the questions we'll cover today include: What is the value that AI is delivering to the insurance industry, and how are insurance providers reacting to these seismic changes?
ETH researchers use artificial intelligence to improve quality of images recorded by a relatively new biomedical imaging method. This paves the way towards more accurate diagnosis and cost-effective devices. Scientists at ETH Zurich and the University of Zurich have used machine learning methods to improve optoacoustic imaging. This relatively young medical imaging technique can be used for applications such as visualizing blood vessels, studying brain activity, characterizing skin lesions and diagnosing breast cancer. However, quality of the rendered images is very dependent on the number and distribution of sensors used by the device: the more of them, the better the image quality.
Physicists have designed artificial intelligence that thinks like the astronomer Nicolaus Copernicus by realizing the Sun must be at the centre of the Solar System.Credit: NASA/JPL/SPL Astronomers took centuries to figure it out. But now, a machine-learning algorithm inspired by the brain has worked out that it should place the Sun at the centre of the Solar System, based on how movements of the Sun and Mars appear from Earth. The feat is one the first tests of a technique that researchers hope they can use to discover new laws of physics, and perhaps to reformulate quantum mechanics, by finding patterns in large data sets. The results are due to appear in Physical Review Letters1. Physicist Renato Renner at the Swiss Federal Institute of Technology (ETH) in Zurich and his collaborators wanted to design an algorithm that could distill large data sets down into a few basic formulae, mimicking the way that physicists come up with concise equations like E mc2.
Creoptix AG is a growing company located in Wädenswil near Zurich. Our biosensor instruments are used in life science research labs within academia and industry, providing biochemists with the best tools to explore new applications in the field of molecular interaction analysis. Our products incorporate industry-leading software automation based on machine learning frameworks, and we are very committed to stay ahead. In this role, you will work in our software team in close collaboration with an interdisciplinary team of biochemists and engineers to continuously improve our software used for designing, conducting and analyzing biochemical experiments. You will be developing in .NET (Core, C#/F#) with Visual Studio on Windows, as well as building and maintaining TensorFlow models in Python.
The Max Planck ETH Center for Learning Systems (CLS) offers a unique fellowship program, where PhD students are co-supervised by one advisor from ETH Zurich and one from the MPI for Intelligent Systems in Tübingen and Stuttgart. PhD students are expected to take advantage of the opportunities offered by both organizations and to actively seek cross-group collaborations. The Center also offers a wide range of activities like retreats, workshops, and summer schools, as well as the possibility to engage in organizing such events. This is an exciting new program and admission is highly competitive. Each PhD fellow will have a primary location (chosen based on interests and match) and spends one year at the other location as well.
This kind of future may seem like science-fiction. But at Health's Digital Future, a special event titled "ETH Meets Digital Festival Zurich," researchers and partners from ETH Zurich gathered to discuss the realities of this kind of future. Moderated by Diplomatic Courier's own Contributing Editor Shalini Trefzer, the event featured leading voices in technology, entrepreneurship, research and healthcare, all discussing the future of digital health. A key takeaway from the event focused on the complexity of digital health, especially within large organizations. As brought up in the discussion between Novartis CDO Bertrand Bodson and ICRC s Director of Digital Transformation and Data Charlotte Lindsey-Curtet, one of the necessary components with digitizing large organizations is culture.
Researchers at the University of Zurich's Brain Research Institute have recently developed a technique to automatically detect neurons of different types in a variety of brain regions at different developmental stages. They presented this deep learning-based tool, called DeNeRD, in a paper published in Nature Scientific Reports. Mapping the structure of the mammalian brain at the cellular level is an important, yet demanding task, which typically involves capturing specific anatomical features and analyzing them. In the past, researchers were able to gather several interesting observations and insights about the mammalian brain's structure using classical histological and stereological techniques. Although these methods have proved to be very useful for studying the anatomy of the brain, carrying out a truly brain-wide analysis typically requires a different approach.
Trees are a low-tech, high-efficiency way to offset much of humankind's negative impact on the climate. What's even better, we have plenty of room for a lot more of them. A new study conducted by researchers at Switzerland's ETH-Zürich, published in Science, details how Earth could support almost an additional billion hectares of trees without the new forests pushing into existing urban or agricultural areas. Once the trees grow to maturity, they could store more than 200 billion metric tons of carbon. Great news indeed, but it still leaves us with some huge unanswered questions.