AI News, Artificial Intelligence
Young Astronomer Uses Artificial Intelligence To Discover 2 Exoplanets
A team of astronomers led by an undergraduate student in Texas has discovered two planets orbiting stars more than 1,200 light-years from Earth.
Anne Dattilo, a senior at the University of Texas, Austin, found the planets by using an artificial intelligence program to sift through a mountain of data collected by NASA's Kepler space telescope.
Dattilo got involved in the project about a year and a half ago, after astronomer Andrew Vanderburg gave a talk during one of her classes.
Kepler, which launched in 2009, was designed to point at a small patch of sky and measure the light from some 100,000 stars in its field of view.
If there is a planet orbiting one of the stars, the light coming from that star will dim slightly when the planet passes in front of it.
Toward the end of Kepler's life, mechanical failures meant it couldn't measure the light quite as accurately, so the data it collected were harder to interpret.
Once the modified program found stars that appeared to have planets, Dattilo and her colleagues used ground-based telescopes to confirm the findings.
“Each country must lead its own technology journey by implementing artificial intelligence solutions that reach self-awareness and solve development challenges automagically.” USAID is partnering with Alphabet® (the parent company of Google), Apple® (the parent company of the iPhone), and Amazon® (the parent company of everything else), to ensure that humans are no longer needed to provide international assistance.
“We can do half-hour vaccine delivery in Vanuatu, and we can carry objects up to five pounds in Rwanda, which covers 86 percent of the items that USAID delivers.” USAID and its implementing partners will then utilize Google’s unrivaled Cloud Vision visual image recognition system that utilizes machine learning and Neural Architecture Search technology to segment and identify visual artifacts exponentially faster than the human eye.
Evaluation program, led by Chap Pie, will give key stakeholders the power to use Android devices to confirm programmatic impact of USAID’s investments, including: USAID is committed to the day when human assistance is no longer necessary for development, and will be measuring its JSA Initiative by how far every one of its investments moves us closer to that judgement day.
Artificial intelligence can screen job candidates better than human managers
Leaders pride themselves on hiring the best talent, but, like many things, a machine can do better.
And wherever the company used the test as the primary hiring criterion, the company’s workforce reflects the community’s demographics.
The artificial intelligence behind the test proves yet again how time spent screening resumes, checking references and interviewing candidates is mostly wasted.
On HoustonChronicle.com: Bosses need to check their privilege, a sense of impunity can lead to disaster When managers have discretion, they favor people who look like them, act like them and attended similar schools to them.
“When faced with similar applicant pools, managers who exercise more discretion (as measured by their likelihood of overruling job test recommendations) systematically end up with worse hires.”
CEO Jacob Hsu told a session at the South by Southwest Interactive Conference that more than 90 percent of the applicants who score well on the test complete the company’s training course in computer programing and become a productive employee.
“A lady who came in from cleaning hotels and a person who had studied computer science at a university ended up at the same spot in six years in terms of income and job positions,”
Arena tries to prevent hiring managers from making poor or biased decisions, said Myra Norton, president and chief operating officer of Arena.
Can we do a better job of matching people to roles where they are going to be successful and they are going to achieve outcomes that are meaningful to the organization?”
- On 6. maj 2021
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