Slashdot Mirror

schwit1 tipped us off to new arrests made with genealogical evidence -- and growing interest in open source genealogy databases. Fast Company reports: In the last week, police have arrested two suspects in unrelated cold cases thanks to data gleaned from open-source ancestry site GEDMatch, reports the New York Times. That's the same open-source ancestry site that was used to track down the alleged Golden State Killer earlier this year. One of the arrests this week was of a 66-year-old nurse who is suspected of killing a 12-year-old girl in 1986. The other arrest is of a 49-year-old DJ who strangled a schoolteacher in 1992. Thanks to data from GEDMatch, Texas law enforcement also thinks that a man who was executed in 1999 for killing a 9-year-old girl was now also behind the murder of a 40-year-old realtor in 1981.
It all reminds me of that scene in "The Circle" where they demo technology that finds "a randomly-selected fugitive from justice -- a proven menace to our global community" -- within 20 minutes.

Last month DNA-based investigations also led to the arrest of the suspected murderer of two vacationers in 1987, and helped identify a suicide cold case from 2001.

Now an Ohio newspaper reports: Emboldened by that breakthrough, a number of private investigators are spearheading a call for amateur genealogists to help solve other cold cases by contributing their own genetic information to the same public database. They say a larger array of genetic information would widen the pool to find criminals who have eluded capture. The idea is to get people to transfer profiles compiled by commercial genealogy sites such as Ancestry.com and 23andMe onto the smaller, public open-source database created in 2010, called GEDmatch. The commercial sites require authorities to obtain search warrants for the information; the public site does not.

But the push is running up against privacy concerns.

jmcbain writes: Machine learning and artificial intelligence skills are in hot demand right now, and it's driving up the already-high salaries in Silicon Valley. "Tech's biggest companies are placing huge bets on artificial intelligence (Warning: may be paywalled; alternative source)," reports the New York Times, and "typical AI specialists, including both Ph.D.s fresh out of school and people with less education and just a few years of experience, can be paid from $300,000 to $500,000 a year or more in salary and company stock." The New York Times notes there are several catalysts for rocketing salaries that all come down to supply and demand. There is competition among the giant companies (e.g. Google, Facebook, and Uber) as well as the automative companies wanting help with self-driving cars. However, the biggest issue is the supply: "Most of all, there is a shortage of talent, and the big companies are trying to land as much of it as they can. Solving tough A.I. problems is not like building the flavor-of-the-month smartphone app. In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research, according to Element AI, an independent lab in Montreal."

In the past, Los Alamos National Laboratory has done some of the United States' most crucial research and development. Lately, the lab has been dealing with accidents and management problems. Reader DougDot directs us to a report from the Santa Fe New Mexican about the questions surrounding LANL's future. Quoting: Federal officials told Congress in December that they will put the LANL contract up for competitive bid for only the second time since the lab opened in 1943. The current LANS contract ends Sept 30, 2017. Identifying what went wrong, and why the lab has proven so difficult to manage, will play an important role for the Department of Energy as it seeks out new managers to run the lab. Investigators say the problems stem from repeated management weaknesses, the kind that were supposed to get fixed when the Department of Energy turned to private industry in 2006 to oversee the lab.

It was the first time the federal government had put the lab’s management up for bid, with the idea that a for-profit model, operating under an incentives-based contract, would fix the problems that haunted the nonprofit University of California, which had run the lab since World War II. ... experts, watchdog groups and former lab employees point to an array of problems, from a clash of cultures between the regimented and profit-driven Bechtel and the languorous, research-oriented university; to incentives that may have induced contractors to put a premium on meeting deadlines despite safety risks; to a mix of shoddy accountability and micromanagement on the part of the federal government.

McGruber writes "Arthur Firstenberg, the Santa Fe, New Mexico man who sued his neighbors, claiming their Wi-Fi made him sick, has lost what might have been his final round in court. According to the Santa Fe New Mexican, state District Judge Sarah Singleton ruled that no scientific study has yet proved that electromagnetic stimulus adversely impacts personal health. While he lost the lawsuit, he did score a victory: the neighbors he sued have moved out of Santa Fe."