Wednesday March 27, 2019
Home Lead Story AI to help in...

AI to help in search for alien life

As life is currently known only to exist on Earth, the classification uses a "probability of life" metric which is based on the relatively well-understood atmospheric and orbital properties of the five target types

0
//
There are many good uses of AI, but it can be misused too.
AI can now help astronomers find life on other planet. Pixabay
  • AI can now help astronomers too
  • It can help them predict the probability of life on other planets
  • AI is being used in many things nowadays

Artificial Intelligence (AI) could help astronomers predict the probability of life on other planets, according to a new study. Using artificial neural networks (ANNs) researchers from Britain’s Plymouth University classified planets into five types, based on whether they are most like the present-day Earth, the early Earth, Mars, Venus or Saturn’s moon Titan, estimating a probability of life in each case.

All five of these objects are rocky bodies known to have atmospheres and are among the most potentially habitable objects in the Solar System.

Alien
Digital Imaginary Representation of Extraterrestrial beings. Wikimedia commons

“We’re currently interested in these ANNs for prioritising exploration for a hypothetical, intelligent, interstellar spacecraft scanning an exoplanet system at range,” said Christopher Bishop from the varsity.

“We’re also looking at the use of large area, deployable, planar Fresnel antennas to get data back to Earth from an interstellar probe at large distances. This would be needed if the technology is used in robotic spacecraft in the future,” Bishop added.

Also Read: Analysis of Ancient Aliens show on History Channel

ANNs are systems that attempt to replicate the way the human brain learns. Atmospheric observations — known as spectra — of the five Solar System bodies are presented as inputs to the network, which is then asked to classify them in terms of the planetary type. As life is currently known only to exist on Earth, the classification uses a “probability of life” metric which is based on the relatively well-understood atmospheric and orbital properties of the five target types.

Aliens may or may not exist, the question remains. Pixabay

“Given the results so far, this method may prove to be extremely useful for categorising different types of exoplanets using results from ground-based and near-Earth observatories,” said Angelo Cangelosi, the supervisor of the project.

The technique may also be ideally suited to selecting targets for future observations, given the increase in spectral detail expected from upcoming space missions such European Space Agency’s Ariel Space Mission and NASA’s James Webb Space Telescope. The work was presented at the European Week of Astronomy and Space Science (EWASS) in Liverpool. IANS

Next Story

Google Claims Eye Doctors Can Turn More Effective Using AI

Without assistance, general ophthalmologists are significantly less accurate than the algorithm, while retina specialists are not significantly more accurate than the algorithm. 

0
google
The research team at Google AI believes that some of these pitfalls may be avoided if the computer can "explain" its predictions. Pixabay

As Artificial Intelligence (AI) continues to evolve, diagnosing diseases has become faster with greater accuracy. A new study from the Google AI research group shows that physicians and algorithms working together are more effective than either one alone.

In the study, to be published in the journal Ophthalmology, the researchers created a system which not only improved the ophthalmologists’ diagnostic accuracy but also improved the algorithm’s accuracy.

The study expands on previous work from Google AI showing that its algorithm works roughly as well as human experts in screening patients for a common diabetic eye disease called diabetic retinopathy.

eyes
To test this theory, ten ophthalmologists (four general ophthalmologists, one trained outside the US, four retina specialists, and one retina specialist in training) were asked to read images with and without algorithm assistance. Pixabay

“What we found is that AI can do more than simply automate eye screening, it can assist physicians in more accurately diagnosing diabetic retinopathy. AI and physicians working together can be more accurate than either one alone,” said lead researcher Rory Sayres.

Recent advances in AI promise to improve access to diabetic retinopathy screening and to improve its accuracy. But it’s less clear how AI will work in the physician’s office or other clinical settings, the team said.

According to the team, previous attempts to use computer-assisted diagnosis shows that some screeners rely on the machine too much, which leads to repeating the machine’s errors, or under-rely on it and ignore accurate predictions.

The research team at Google AI believes that some of these pitfalls may be avoided if the computer can “explain” its predictions.

web
Recent advances in AI promise to improve access to diabetic retinopathy screening and to improve its accuracy. But it’s less clear how AI will work in the physician’s office or other clinical settings, the team said. Pixabay

To test this theory, ten ophthalmologists (four general ophthalmologists, one trained outside the US, four retina specialists, and one retina specialist in training) were asked to read images with and without algorithm assistance.

Also Read: U.S. Government Human Rights Report Shows ‘Amber’ Warning Light Situation in Hong Kong

Without assistance, general ophthalmologists are significantly less accurate than the algorithm, while retina specialists are not significantly more accurate than the algorithm.

With assistance, general ophthalmologists match but do not exceed the model’s accuracy, while retina specialists start to exceed the model’s performance. (IANS)