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Robohub Podcast #245: High-Performance Autonomous Vehicles, with Chris Gerdes

Robohub

The idea is to make vehicles safer, as Gerdes says, he wants to "develop vehicles that could avoid any accident that can be avoided within the laws of physics." In this interview, Gerdes discusses developing a model for high-performance control of a vehicle; their autonomous race car, an Audi TTS named'Shelley,' and how its autonomous performance compares to ameteur and professional race car drivers; and an autonomous, drifting Delorean named'MARTY.' Chris Gerdes is a Professor of Mechanical Engineering at Stanford University, Director of the Center for Automotive Research at Stanford (CARS) and Director of the Revs Program at Stanford. His laboratory studies how cars move, how humans drive cars and how to design future cars that work cooperatively with the driver or drive themselves. When not teaching on campus, he can often be found at the racetrack with students, instrumenting historic race cars or trying out their latest prototypes for the future.


What CMU's Snake Robot Team Learned While Searching for Mexican Earthquake Survivors

IEEE Spectrum Robotics

A few days after a 7.1-magnitude earthquake struck Mexico City last month, Carnegie Mellon University roboticists were contacted to see if their snake robots could help with search-and-rescue efforts. Mexican rescuers were still trying find people in the rubble of collapsed buildings, and even though several days had passed, they thought it'd be worth trying to bring in the snakebots. Within 24 hours, a team of CMU roboticists had packed their gear and headed out to the disaster site. We spoke with Matt Travers, who was on the ground in Mexico City operating the robots, along with Howie Choset, who heads CMU's Biorobotics Lab where the snake robots are developed, about their experience with using robots in a real disaster and how, although no survivors were found during the rescue missions they assisted with, they learned an enormous amount being on-site. IEEE Spectrum: Were you and your robots ready for a real disaster? Howie Choset: Since the beginning of my adventure into snake robots, I've been interested in search and rescue.


Chapter 1 : Supervised Learning and Naive Bayes Classification -- Part 1 (Theory)

@machinelearnbot

Well if you guessed it to be Alice you are correct. Perhaps your reasoning would be the content has words love, great and wonderful that are used by Alice. Now let's add a combination and probability in the data we have.Suppose Alice and Bob uses following words with probabilities as show below. Now, can you guess who is the sender for the content: "Wonderful Love." Now what do you think?


Where are all the women in economics?

BBC News

We hear a lot about the under-representation of women in so-called STEM fields - science, technology, engineering and maths. But the proportion of women in economics is by some measures smaller. In the US, only about 13% of women hold permanent academic positions in economics; and in the UK the proportion is only slightly better at 15.5%. Only one woman has ever won the Nobel Prize in economics - American Elinor Ostrom in 2009. And there wasn't even a single woman on some of the lists floating about guessing who this year's prize winner would be - it went to the behavioural economist Richard Thaler.


How Artificial Intelligence is used to find cancer cures

#artificialintelligence

Four out of 10--that's how many Americans the National Cancer Institute estimates will be diagnosed with cancer at some point. While 33 percent of those patients won't live longer than five years, giving them precious little time to find effective treatments, it takes over a decade to bring new cancer drugs to market. The process involves animal testing, human trials and regulatory review--a gantlet through which less than 7 percent of experimental medicines successfully pass. Is it any wonder, then, that there are less than 2,000 Food and Drug Administration-approved pharmaceuticals on the market? Insilico Medicine, a Baltimore-based biotech research company, hopes to revolutionize drug development by slashing the time necessary for research with the help of artificial intelligence (AI). In a study published in the medical journal Oncotarget, a team led by Insilico Medicine details their approach.


News at a glance

Science

In science news around the world, a deadly plague epidemic spreads through Madagascar, Japan's economy ministry announces a successful first test of seafloor mining for metallic ore deposits near hydrothermal vents, the World Health Organization releases a new strategy for fighting cholera, and the U.S. Environmental Protection Agency moves to roll back limits on greenhouse gas emissions from power plants. Also, economist Richard Thaler of the University of Chicago in Illinois wins the Nobel economics prize for his study of irrational human economic behavior, scientists discover evidence of rice domestication in South America, and a Carnegie Mellon University roboticist describes how his robotic snakes combed through rubble of the 19 September earthquake in Mexico.


Who Is Sally Jones? ISIS Member 'White Widow' Allegedly Killed In Syria

International Business Times

Sally Jones, a former punk rocker from Kent, United Kingdom, who gained notoriety as "Mrs Terror" after joining the Islamic State group (also called ISIS), was reportedly killed in a United States drone strike along with her 12-year old son Jojo in Syria as she tried to escape Raqqa, the Sun reported. Though Whitehall sources confirmed reports that Jones was killed, according to the Guardian, the Pentagon was unable to confirm the news. Maj Adrian Rankine-Galloway, a Pentagon spokesman, told the Guardian, "I do not have any information that would substantiate that report but that could change and we are looking into this." Rukmini Callimachi, a correspondent for the New York Times, also said two senior U.S. officials denied that Jones was dead. Fifty-years-old Jones was born in Greenwich, southeast London, and later moved to Kent.


mit-computer-scientist-regina-barzilay-wins-macarthur-genius-grant-1011

MIT News

Regina Barzilay, a professor in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) who does research in natural language processing and machine learning, is a recipient of a 2017 MacArthur Fellowship, sometimes referred to as a "genius grant." The Delta Electronics Professor of Electrical Engineering and Computer Science, Barzilay does research in natural language processing (NLP) and machine learning. She is the recipient of the National Science Foundation Career Award, the Microsoft Faculty Fellowship, and multiple "best paper" awards in her field. For her contributions to teaching machine learning and natural language processing, she was awarded the Jamieson Award for Excellence in teaching.


10 ways this year's MacArthur Fellows find their 'genius'

PBS NewsHour

Njideka Akunyili Crosby, a 2017 MacArthur Fellow, photographed in her studio in Los Angeles, CA on Wednesday September 13th, 2017.Photo courtesy of the MacArthur Foundation. The MacArthur Foundation announced today it has selected 24 individuals -- from photographers and historians, to computer scientists and psychologists -- for its annual "genius grant," given to those who have "extraordinary originality and dedication to their creative pursuits." How does someone become a so-called "genius"? We reached out to a few of them to ask about their "secret sauce." What are the quirks and habits that fuel their creativity and enhance their work?


Q&A: Douglas Hofstadter on why AI is far from intelligent

#artificialintelligence

The field of artificial intelligence may finally be coming back around to Douglas Hofstadter. Since winning a Pulitzer Prize in nonfiction for his 1979 book Gödel, Escher, Bach: an Eternal Golden Braid, Hofstadter, 72, has been quietly thinking about thinking, and how we might get computers to do it. In the early days of AI research in 1950s and 60s, the goal was to create computers that think and learn the way humans do, by remodeling our ability to intuitively understand the world around us. But thinking turned out to be more complicated than something that could fit in a 1950s computer program. What did eventually yield results, though, was giving up on thinking altogether, focusing computers instead on highly specific tasks and giving them vast amounts of relevant data--resulting in the AI boom we see today. A computer can beat a human at chess not by searching for the satisfaction of making an elegant move, but sifting through millions of previously played games to see which move is more likely to lead to victory.