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Category: information science – Page 236

This AI Generates Photos Using Only Text Captions as a Guide

Researchers at the Allen Institute for Artificial Intelligence (AI2) have created a machine learning algorithm that can produce images using only text captions as its guide. The results are somewhat terrifying… but if you can look past the nightmare fuel, this creation represents an important step forward in the study of AI and imaging.

Unlike some of the genuinely mind-blowing machine learning algorithms we’ve shared in the past—see here, here, and here —this creation is more of a proof-of-concept experiment. The idea was to take a well-established computer vision model that can caption photos based on what it “sees” in the image, and reverse it: producing an AI that can generate images from captions, instead of the other way around.

This is a fascinating area of study and, as MIT Technology Review points out, it shows in real terms how limited these computer vision algorithms really are. While even a small child can do both of these things readily—describe an image in words, or conjure a mental picture of an image based on those words—when the Allen Institute researchers tried to generate a photo from a text caption using a model called LXMERT, it generated nonsense in return.

Data Science to Accelerate Drug Discovery with Artificial Intelligence and Machine Learning, Says Frost & Sullivan

Frost & Sullivan’s recent analysis, Data Science Impacting the Pharmaceutical Industry, finds that data science tools are promising technologies transforming drug discovery costs, speed, and efficiency. When combined with other emerging tech areas, artificial intelligence (AI) technologies move…

Pharmaceutical companies and hospitals are adopting data science rapidly, and its application is going to be established in all branches of healthcare

SANTA CLARA, Calif., Sept. 29, 2020 /PRNewswire/ — Frost & Sullivan’s recent analysis, Data Science Impacting the Pharmaceutical Industry, finds that data science tools are promising technologies transforming drug discovery costs, speed, and efficiency. When combined with other emerging tech areas, artificial intelligence (AI) technologies move to the next phase of advancements. Hence, they are expected to witness adoption by pharma and biotech companies in the next four to five years. Further, with the COVID-19 pandemic, AI and machine learning (ML) can be used for drug research and clinical trials against the coronavirus to screen large databases and perform docking studies to identify existing potential drugs or design new drugs using advanced learning algorithms.

For further information on this analysis, please visit: http://frost.ly/4l2.

“Applying data science tools in healthcare, especially for drug discovery, has a huge potential to systematically change the entire existing practices and methods,” said Aarthi Janakiraman, Technical Insights Research Manager at Frost & Sullivan. “Additionally, pharmaceutical companies and hospitals are adopting this system rapidly, and its application is going to be established in all branches of healthcare.”

Harvard Professor Wants to Slow Down & Reverse Aging: David Sinclair’s Approach For a Longer Life

David Sinclair wants to slow down and ultimately reverse aging. Sinclair sees aging as a disease and he is convinced aging is caused by epigenetic changes, abnormalities that occur when the body’s cells process extra or missing pieces of DNA. This results in the loss of the information that keeps our cells healthy. This information also tells the cells which genes to read. David Sinclair’s book: “Lifespan, why we age and why we don’t have to”, he describes the results of his research, theories and scientific philosophy as well as the potential consequences of the significant progress in genetic technologies.

At present, researchers are only just beginning to understand the biological basis of aging even in relatively simple and short-lived organisms such as yeast. Sinclair however, makes a convincing argument for why the life-extension technologies will eventually offer possibilities of life prolongation using genetic engineering.

He and his team recently developed two artificial intelligence algorithms that predict biological age in mice and when they will die. This will pave the way for similar machine learning models in people.
The loss of epigenetic information is likely the root cause of aging. By analogy, If DNA is the digital information on a compact disc, then aging is due to scratches. What we are searching for, is the polish.

Every time a cell divides, the DNA strands at the ends of your chromosomes replicate in order to copy all the genetic information to each new cell, and this process is not perfect. Over time, however, the ends of your chromosomes can become scrambled.

However, the progress in genetic engineering has proved that these changes can be reversed even at the cellular level, and it is possible to restore the information in our cells, thus improving the functioning of our organs and slowing the aging process.

#Aging #DavidSinclair #Lifespan

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Using deep learning to control the unconsciousness level of patients in an anesthetic state

In recent years, researchers have been developing machine learning algorithms for an increasingly wide range of purposes. This includes algorithms that can be applied in healthcare settings, for instance helping clinicians to diagnose specific diseases or neuropsychiatric disorders or monitor the health of patients over time.

Researchers at Massachusetts Institute of Technology (MIT) and Massachusetts General Hospital have recently carried out a study investigating the possibility of using learning to control the levels of unconsciousness of patients who require anesthesia for a medical procedure. Their paper, set to be published in the proceedings of the 2020 International Conference on Artificial Intelligence in Medicine, was voted the best paper presented at the conference.

“Our lab has made significant progress in understanding how anesthetic medications affect and now has a multidisciplinary team studying how to accurately determine anesthetic doses from neural recordings,” Gabriel Schamberg, one of the researchers who carried out the study, told TechXplore. “In our recent study, we trained a using the cross-entropy method, by repeatedly letting it run on simulated patients and encouraging actions that led to good outcomes.”

Microsoft’s camera-based AI app solves your math problems

Microsoft has made several quirky and useful apps that can help you with daily problems and its new app seeks to help you with math.

Microsoft Math Solver — available on both iOS and Android — can solve various math problems including quadratic equations, calculus, and statistics. The app can also show graphs for the equation to enhance your understanding of the subject.

Big Questions: The Multiverse, Cosmological Neural Networks and “Space Noodles”

Ira Pastor, ideaXme life sciences ambassador and founder of Bioquark interviews Dr Vitaly Vanchurin, PhD, Associate Professor, Theoretical Physics and Cosmology, Swenson College of Science and Engineering, at the University of Minnesota (UMN).

Dr Vanchurin’s big questions and the tools we need to answer them:

“What is the origin of our Universe? What determines our vacuum and the cosmological constant that is responsible for the observed accelerated expansion of space? What determines the onset of structure formation and the birth of galaxies in our Universe? Our innate curiosity about our beginnings has been, since time immemorial, and still is, at the heart of every human being. This age old question of our origin can now be addressed by applying the scientific method”.

Ira Pastor comments:

Today, we have a really exciting thought leader joining us on ideaXme who spends his time thinking about really BIG questions – Questions like: what is the origin of our Universe? What’s behind the cosmological constant (in Albert Einstein’s field equations of general relativity) that is responsible accelerated expansion of space? What determines the onset of structure formation and the birth of galaxies in our Universe? And many other fascinating topics.

Dr. Vitaly Vanchurin, is an Associate Professor, Theoretical Physics and Cosmology, Swenson College of Science and Engineering, at the University of Minnesota (UMN).

Continue reading “Big Questions: The Multiverse, Cosmological Neural Networks and “Space Noodles”” | >

Ventilator-Associated Pneumonia: Diagnosis, Treatment, and Prevention

While critically ill patients experience a life-threatening illness, they commonly contract ventilator-associated pneumonia. This nosocomial infection increases morbidity and likely mortality as well as the cost of health care. This article reviews the literature with regard to diagnosis, treatment, and prevention. It provides conclusions that can be implemented in practice as well as an algorithm for the bedside clinician and also focuses on the controversies with regard to diagnostic tools and approaches, treatment plans, and prevention strategies.

Patients in the intensive care unit (ICU) are at risk for dying not only from their critical illness but also from secondary processes such as nosocomial infection. Pneumonia is the second most common nosocomial infection in critically ill patients, affecting 27% of all critically ill patients (170). Eighty-six percent of nosocomial pneumonias are associated with mechanical ventilation and are termed ventilator-associated pneumonia (VAP). Between 250,000 and 300,000 cases per year occur in the United States alone, which is an incidence rate of 5 to 10 cases per 1,000 hospital admissions (134, 170). The mortality attributable to VAP has been reported to range between 0 and 50% (10, 41, 43, 96, 161).

Neuroscience study finds ‘hidden’ thoughts in visual part of brain

How much control do you have over your thoughts? What if you were specifically told not to think of something—like a pink elephant?

A recent study led by UNSW psychologists has mapped what happens in the brain when a person tries to suppress a . The neuroscientists managed to ‘decode’ the complex brain activity using functional brain imaging (called fMRI) and an imaging algorithm.

The findings suggest that even when a person succeeds in ignoring a thought, like the pink elephant, it can still exist in another part of the brain—without them being aware of it.

NASA to test precision automated landing system designed for the moon and Mars on upcoming Blue Origin mission

NASA is going to be testing a new precision landing system designed for use on the tough terrain of the moon and Mars for the first time during an upcoming mission of Blue Origin’s New Shepard reusable suborbital rocket. The “Safe and Precise Landing – Integrated Capabilities Evolution” (SPLICE) system is made up of a number of lasers, an optical camera and a computer to take all the data collected by the sensors and process it using advanced algorithms, and it works by spotting potential hazards, and adjusting landing parameters on the fly to ensure a safe touchdown.

SPLICE will get a real-world test of three of its four primary subsystems during a New Shepard mission to be flown relatively soon. The Jeff Bezos –founded company typically returns its first-stage booster to Earth after making its trip to the very edge of space, but on this test of SPLICE, NASA’s automated landing technology will be operating on board the vehicle the same way they would when approaching the surface of the moon or Mars. The elements tested will include “terrain relative navigation,” Doppler radar and SPLICE’s descent and landing computer, while a fourth major system — lidar-based hazard detection — will be tested on future planned flights.

Currently, NASA already uses automated landing for its robotic exploration craft on the surface of other planets, including the Perseverance rover headed to Mars. But a lot of work goes into selecting a landing zone with a large area of unobstructed ground that’s free of any potential hazards in order to ensure a safe touchdown. Existing systems can make some adjustments, but they’re relatively limited in that regard.