Lifeboat Foundation

The Facebook research builds upon steady progress in tweaking deep learning algorithms to make them more efficient and effective. Self-supervised learning previously has been used to translate text from one language to another, but it has been more difficult to apply to images than words. LeCun says the research team developed a new way for algorithms to learn to recognize images even when one part of the image has been altered.

Most image recognition algorithms require lots of labeled pictures. This new approach eliminates the need for most of the labeling.

Dr. John Torday, Ph.D. is an Investigator at The Lundquist Institute of Biomedical Innovation, a Professor of Pediatrics and Obstetrics/Gynecology, and Faculty, Evolutionary Medicine, at the David Geffen School of Medicine at UCLA, and Director of the Perinatal Research Training Program, the Guenther Laboratory for Cell-Molecular Biology, and Faculty in the Division of Neonatology, at Harbor-UCLA Medical Center.

Dr. Torday studies the cellular-molecular development of the lung and other visceral organs, and using the well-established principles of cell-cell communication as the basis for determining the patterns of physiologic development, his laboratory was the first to determine the complete repertoire of lung alveolar morphogenesis. This highly regulated structure offered the opportunity to trace the evolution of the lung from its unicellular origins forward, developmentally and phylogenetically. The lung is an algorithm for understanding the evolution of other physiologic properties, such as in the kidney, skin, liver, gut, and central nervous system. Such basic knowledge of the how and why of physiologic evolution is useful in the effective diagnosis and treatment of disease.

Continue reading “Dr. John S Torday — Lundquist Institute / UCLA — Aging And Disease As A Process Of Reverse Evolution” »

A new mathematical algorithm examines data from EEG and brain implants to learn each epilepsy patient’s unique brain pattern signatures. The system can predict the onset of a seizure within an hour, allowing the patient to take necessary interventions.

A team of researchers at Uber AI Labs in San Francisco has developed a set of learning algorithms that proved to be better at playing classic video games than human players or other AI systems. In their paper published in the journal Nature, the researchers explain how their algorithms differ from others and why they believe they have applications in robotics, language processing and even designing new drugs.

😃

The Nobel-winning author talks about scaring Harold Pinter, life after death – and his new novel about an ‘artificial friend’

Continue reading “Kazuo Ishiguro: ‘AI, gene-editing, big data … I worry we are not in control of these things any more’” »

10 November 2020

Qudit is a multi-level computational unit alternative to the conventional 2-level qubit. Compared to qubit, qudit provides a larger state space to store and process information, and thus can provide reduction of the circuit complexity, simplification of the experimental setup and enhancement of the algorithm efficiency. This review provides an overview of qudit-based quantum computing covering a variety of topics ranging from circuit building, algorithm design, to experimental methods. We first discuss the qudit gate universality and a variety of qudit gates including the pi/8 gate, the SWAP gate, and the multi-level controlled-gate. We then present the qudit version of several representative quantum algorithms including the Deutsch-Jozsa algorithm, the quantum Fourier transform, and the phase estimation algorithm.

This art installation enhances plant growth while taking pesticides out of the equation through ultraviolet light. The GROW project shines vertical lights across 215000 square feet of farmland creating a luminous dreamscape that highlights the beauty of agriculture, and displays nature as the ultimate work of art it is!

📹 @roosegaarde via IG.

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.

The algorithm isn’t perfect, but it vastly outperforms past attempts.