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Amazon and Max Planck Society announced the formation of a Science Hub—a collaboration that marks the first Amazon Science Hub to exist outside the United State… See more.

Amazon and Max Planck Society (also known as Max-Planck-Gesellschaft or MPG) today announced the formation of a Science Hub. The collaboration marks the first Amazon Science Hub to exist outside the United States and will focus on advancing artificial intelligence research and development throughout Germany.

The hub’s goal is to advance the frontiers of AI, computer vision, and machine learning research to ensure that research is creating solutions whose benefits are shared broadly across all sectors of society. To achieve that end, the collaboration will include sponsored research; open research; industrial fellowships co-supervised by Max Planck and Amazon; and community events funding to enrich the MPG and Amazon research communities.

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Incredible and somewhat frightening visions of the future will become a reality in the coming decades. According to futurologists, people of the future will gain immortality and will live in the body of a machine. Dr. Ian Pearson predicts that a person will be able to transfer his mind into a computer and one day he will go to a funeral where his previous biological body will be buried. Like anomalien.com on Facebook To stay in touch & get our latest news Cyborgization has some good sides. Let us take into account that we will be able to exchange each of…

Can quantum science supercharge genetics? | Jim Al-Khalili for Big Think.

This interview is an episode from The Well, our new publication about ideas that inspire a life well-lived, created with the John Templeton Foundation.

Continue reading “What if quantum physics could eradicate illness? | Jim Al-Khalili for Big Think” »

For the first time TU Graz’s Institute of Theoretical Computer Science and Intel Labs demonstrated experimentally that a large neural network can process sequences such as sentences while consuming four to sixteen times less energy while running on neuromorphic hardware than non-neuromorphic hardware. The new research based on Intel Labs’ Loihi neuromorphic research chip that draws on insights from neuroscience to create chips that function similar to those in the biological brain.

The research was funded by The Human Brain Project (HBP), one of the largest research projects in the world with more than 500 scientists and engineers across Europe studying the human brain. The results of the research are published in Nature Machine Intelligence (“Memory for AI Applications in Spike-based Neuromorphic Hardware”).

The close-up shows an Intel Nahuku board, each of which contains eight to 32 Intel Loihi neuromorphic research chips. (Image: Tim Herman, Intel Corporation)

Circa 2012

In nature, you’ll find animals that undergo vast transformations, becoming almost unrecognizable in their new forms. Examples like caterpillars becoming butterflies and tadpoles becoming frogs almost look like distinct animals in the different stages of their evolution.

While this might sound amazing, all stages of these animals still belong to the same biological taxonomic rank, Animalia. This means that caterpillars don’t become plants, in their new shapes, they remain animals. That’s not what Mesodinium chamaeleon does. This single-celled organism is a unique mix of animal and plant life.

Continue reading “Mesodinium Chamaeleon Is A Unique Life Form That is Half Plant Half Animal” »

Preparedness For Emerging Diseases & Zoonoses — Dr. Maria Van Kerkhove, Ph.D., Emerging Diseases and Zoonoses Unit Head, World Health Organization, (WHO)

Dr. Maria Van Kerkhove, Ph.D., (https://www.imperial.ac.uk/people/m.vankerkhove) is an infectious disease epidemiologist who serves as the technical lead for the COVID-19 response at the World Health Organization (https://www.who.int/en/), where she develops guidance, training programs, and information products for the continuously evolving state of the pandemic, as well serving as the Emerging Diseases and Zoonoses Unit Head.

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In biological evolution, we know that it’s all about the survival of the fittest: organisms that develop genetic traits that allow them to better adapt to their physical environment are more likely to thrive, and thus pass down their winning genes to their offspring.

From the longer-beaked Galapagos Island finches studied by biologist Charles Darwin that enabled them to more effectively snatch insects, to the ability of some humans over others to digest milk, the process of natural selection results in genetic differences that give some organisms an edge over others.

New research by University of Toronto Mississauga biology assistant professor Alex N. Nguyen Ba adds an important dimension to our understanding of how genes interact in the evolutionary process.

At DeepMind, we’re embarking on one of the greatest adventures in scientific history. Our mission is to solve intelligence, to advance science and benefit humanity.

To make this possible, we bring together scientists, designers, engineers, ethicists, and more, to research and build safe artificial intelligence systems that can help transform society for the better.

Continue reading “Welcome to DeepMind: Embarking on one of the greatest adventures in scientific history” »

Deep learning models have proved to be highly promising tools for analyzing large numbers of images. Over the past decade or so, they have thus been introduced in a variety of settings, including research laboratories.

In the field of biology, deep learning models could potentially facilitate the quantitative analysis of microscopy images, allowing researchers to extract meaningful information from these images and interpret their observations. Training models to do this, however, can be very challenging, as it often requires the extraction of features (i.e., number of cells, area of cells, etc.) from microscopy images and the manual annotation of training data.

Researchers at CERVO Brain Research Center, the Institute for Intelligence and Data, and Université Laval in Canada have recently developed an artificial neural network that could perform in-depth analyses of microscopy images using simpler, image-level annotations. This model, dubbed MICRA-Net (MICRoscopy Analysis neural network), was introduced in a paper published in Nature Machine Intelligence.