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Category: robotics/AI – Page 1,773

When A Ghost Seemingly Has Taken Your AI Self-Driving Car

Hey, dude, where’s my car?

That was the question on my mind when I walked out to the parking lot to get into my car and it was not there. Given that Halloween was just a few days away, I naturally suspected that perhaps a ghost had decided to take my car for a spin. Seems like those ghosts don’t get much of a chance to spirit away an everyday car.

I put aside the ghost theory and sought to find something more down-to-earth as an explanation for where my car was.

This particular parking lot was quite expansive and there wasn’t any numbering system associated with the parking spots. Thus, I had to remember where my car was supposed to be as based entirely on my own mental “global positioning” brain ware, and absent of having any tangible and more reliable form of tracing.

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Artificial Intelligence Sheds Light on How the Brain Processes Language

Researchers report the human brain may use next word prediction to drive language processing.

Source: MIT

In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type.

Artificial Intelligence Has Found an Unknown ‘Ghost’ Ancestor in The Human Genome

Only recently, researchers have uncovered evidence she wasn’t alone. In a 2019 study analyzing the complex mess of humanity’s prehistory, scientists used artificial intelligence (AI) to identify an unknown human ancestor species that modern humans encountered – and shared dalliances with – on the long trek out of Africa millennia ago.

“About 80,000 years ago, the so-called Out of Africa occurred, when part of the human population, which already consisted of modern humans, abandoned the African continent and migrated to other continents, giving rise to all the current populations”, explained evolutionary biologist Jaume Bertranpetit from the Universitat Pompeu Fabra in Spain.

As modern humans forged this path into the landmass of Eurasia, they forged some other things too – breeding with ancient and extinct hominids from other species.

Tesla FSD Beta is starting to save lives

Tesla’s Autopilot and Full Self-Driving Beta are, at their core, safety systems. They may be advanced enough to make driving tasks extremely easy and convenient, but ultimately, CEO Elon Musk has been consistent with the idea that Tesla’s advanced driver-assist technologies are being developed to make the world’s roads as safe as possible.

This is something that seems to be happening now among some members of the FSD Beta group, which is currently being expanded even to drivers with a Safety Score of 99. As the company expands its fleet of vehicles that are equipped with FSD beta, some testers have started sharing stories about how the advanced driver-assist system helped them avoid potential accidents on the road.

FSD Beta tester @FrenchieEAP, for example, recently shared a story about a moment when his Model 3 was sitting at a red light with the Full Self-Driving Beta engaged. When the light turned green, the all-electric sedan started moving forward — before braking suddenly. The driver initially thought that the FSD Beta was stopping for no reason, but a second later, the Model 3 owner realized that a cyclist had actually jumped a red light. The FSD Beta just saw the cyclist before he did.

AI-based technology rapidly identifies genetic causes of rare disorders with high accuracy

An artificial intelligence (AI)-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy, according to a report by scientists from University of Utah Health and Fabric Genomics, collaborators on a study led by Rady Children’s Hospital in San Diego. The benchmark finding, published in Genomic Medicine, foreshadows the next phase of medicine, where technology helps clinicians quickly determine the root cause of disease so they can give patients the right treatment sooner.

“This study is an exciting milestone demonstrating how rapid insights from AI-powered decision support technologies have the potential to significantly improve patient care,” says Mark Yandell, Ph.D., co-corresponding author on the paper. Yandell is a professor of human genetics and Edna Benning Presidential Endowed Chair at U of U Health, and a founding scientific advisor to Fabric.

Worldwide, about seven million infants are born with serious genetic disorders each year. For these children, life usually begins in intensive care. A handful of NICUs in the U.S., including at U of U Health, are now searching for genetic causes of disease by reading, or sequencing, the three billion DNA letters that make up the human genome. While it takes hours to sequence the whole genome, it can take days or weeks of computational and manual analysis to diagnose the illness.

Rise of Robot Radiologists

Circa 2019 😀

Because they can process massive amounts of data, computers can perform analytical tasks that are beyond human capability. Google, for instance, is using its computing power to develop AI algorithms that construct two-dimensional CT images of lungs into a three-dimensional lung and look at the entire structure to determine whether cancer is present. Radiologists, in contrast, have to look at these images individually and attempt to reconstruct them in their heads. Another Google algorithm can do something radiologists cannot do at all: determine patients’ risk of cardiovascular disease by looking at a scan of their retinas, picking up on subtle changes related to blood pressure, cholesterol, smoking history and aging. “There’s potential signal there beyond what was known before,” says Google product manager Daniel Tse.

The Black Box Problem

AI programs could end up revealing entirely new links between biological features and patient outcomes. A 2019 paper in JAMA Network Open described a deep-learning algorithm trained on more than 85,000 chest x-rays from people enrolled in two large clinical trials that had tracked them for more than 12 years. The algorithm scored each patient’s risk of dying during this period. The researchers found that 53 percent of the people the AI put into a high-risk category died within 12 years, as opposed to 4 percent in the low-risk category. The algorithm did not have information on who died or on the cause of death. The lead investigator, radiologist Michael Lu of Massachusetts General Hospital, says that the algorithm could be a helpful tool for assessing patient health if combined with a physician’s assessment and other data such as genetics.

“AI 2041” Co-Author Kai-Fu Lee Talks About AI’s Sweeping Future And How He Invests In It

AI is changing the way we live and the global balance of military power. Ex-Pentagon software chief Nicholas Chaillan said this month the U.S. has already lost out to China in military applications. Even 98-year-old Henry Kissinger weighs in on AI as co-author of a new book due next month, “The Age of AI: And Our Human Future.”

Kai-Fu Lee has been sizing up the implications for decades. The former Google executive turned venture capitalist looked at U.S.-China competition in his 2018 book, “AI Superpowers.” His new book, “AI 2041,” co-authored with science fiction writer Chen Qiufan, suggests how AI will bring sweeping changes to daily life in the next 20 years. I talked earlier this month to Lee, who currently oversees $2.7 billion of assets at Beijing-headquartered Sinovation Ventures. Sinovation has backed seven AI start-ups that have become “unicorns” worth more than $1 billion: AInnovation, 4Paradigm, Megvii, Momenta, WeRide, Horizon Robotics and Bitman. We discussed Lee’s new book, the investments he’s made based on his predictions in it, and where the U.S.-China AI rivalry now stands. Excerpts follow.

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