Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: information science – Page 272

According to a straightforward interpretation of general relativity, the Big Bang wasn’t the start of ‘everything’.

Taking Einstein’s famous equations at face value and making as few assumptions as possible, a team of researchers has rewound the clock on our Universe to find it wouldn’t lead to a stopping point at all, but would take us through a different kind of beginning into a flipped space.

To understand what all the fuss over the Big Bang is, we need to rewind a bit to understand why physicists think it may not have been the start of everything.

Read more

Companies use different algorithms based on different sets of data. Most of that data comes from people of recent European ancestry.

The problem, obviously, is that a lot of people don’t have grandparents or great-great-great-grandparents from England or Italy or Denmark. Most people on Earth, actually! That means if you’re from, say, Asia or Africa, you might not get as detailed a profile as you’d like.

My mother, who was born in the Philippines, actually got an update from 23andMe with new information about her heritage. Her history didn’t change. But as the company gets more DNA kits from people of Asian descent, the algorithm churns out modified results. Which is great … but that does mean right now, if you’re not white, you might have to wait a bit longer for more accurate results.

Read more

Of course, all the algorithmic rigmarole is also causing real-world problems. Algorithms written by humans — tackling harder and harder problems, but producing code embedded with bugs and biases — are troubling enough. More worrisome, perhaps, are the algorithms that are not written by humans, algorithms written by the machine, as it learns.

Profiles in science.

Donald Knuth, master of algorithms, reflects on 50 years of his opus-in-progress, “The Art of Computer Programming.”

Donald Knuth at his home in Stanford, Calif. He is a notorious perfectionist and has offered to pay a reward to anyone who finds a mistake in any of his books. Credit Credit Brian Flaherty for The New York Times.

Read more

IonQ was founded on a gamble that ‘trapped ion quantum’ computing could outperform the silicon-based quantum computers that Google and others are building. As of right now, it does. IonQ has constructed a quantum computer that can perform calculations on a 79-qubit array, beating the previous king Google’s efforts by 7 qubits.

Their error rates are also the best in the business, with their single-qubit error rate at 99.97% while the nearest competitors are around the 99.5 mark, and a two-qubit error rate of 99.3% when most competitors are beneath 95%. But how does it compare to regular computers?

According to IonQ, in the kinds of workloads that quantum computers are being built for, it’s already overtaking them. The Bernstein-Vazirani Algorithm, a benchmark IonQ is hoping will take off, tests a computer’s ability to determine a single encoded number (called an oracle) when the computer can only ask a single yes/no question.

Read more

This is happening in the city of Tianjin, about an hour’s drive south of Beijing, within a gleaming office building that belongs to iFlytek, one of China’s rapidly rising artificial-intelligence companies. Beyond guarded gates, inside a glitzy showroom, the US president is on a large TV screen heaping praise on the Chinese company. It’s Trump’s voice and face, but the recording is, of course, fake—a cheeky demonstration of the cutting-edge AI technology iFlytek is developing.

Jiang Tao chuckles and leads the way to some other examples of iFlytek’s technology. Throughout the tour, Tao, one of the company’s cofounders, uses another remarkable innovation: a hand-held device that converts his words from Mandarin into English almost instantly. At one point he speaks into the machine, and then grins as it translates: “I find that my device solves the communication problem.”

IFlytek’s translator shows off AI capabilities that rival those found anywhere in the world. But it also highlights a big hole in China’s plan, unveiled in 2017, to be the world leader in AI by 2030. The algorithms inside were developed by iFlytek, but the hardware—the microchips that bring those algorithms to life—was designed and made elsewhere. While China manufactures most of the world’s electronic gadgets, it has failed, time and again, to master the production of these tiny, impossibly intricate silicon structures. Its dependence on foreign integrated circuits could potentially cripple its AI ambitions.

Read more

Investigators from the Neurodegenerative Diseases Research Group at the University of Extremadura are studying signaling mediated by a pathway known as planar cell polarity (PCP), which regulates the coordinated orientation of cells during organogenesis, the process of organ formation in living organisms. This pathway has been highly conserved on the evolutionary scale, and one of its key functions in vertebrates is the regulation of the coordinated positioning of centrioles/ciliary basal cells inside cells.

This signaling pathway was discovered initially in the fruit fly genus Drosophila, although the majority of the pathway components have been retained in humans. It has likewise been observed that certain pathologies such as hydrocephaly, infertility and some kinds of cancers are associated with defective functioning of this signaling.

Under the auspices of the project EPICENTR within the Spanish national research plan, whose objective is to study the planar polarisation of centrioles in epithelial , the UEx researchers have now published the first results of their investigation in the journal Development. These results are related to the polarised positioning mechanism of centrioles in Drosophila and its correlation with actin.

Read more

Facial recognition technology is being tested by businesses and governments for everything from policing to employee timesheets. Even more granular results are on their way, promise the companies behind the technology: Automatic emotion recognition could soon help robots understand humans better, or detect road rage in car drivers.

But experts are warning that the facial-recognition algorithms that attempt to interpret facial expressions could be based on uncertain science. The claims are a part of AI Now Institute’s annual report, a nonprofit that studies the impact of AI on society. The report also includes recommendations for the regulation of AI and greater transparency in the industry.

“The problem is now AI is being applied in a lot of social contexts. Anthropology, psychology, and philosophy are all incredibly relevant, but this is not the training of people who come from a technical [computer science] background.” says Kate Crawford, co-founder of AI Now, distinguished research professor at NYU and principal researcher at Microsoft Research. “Essentially the narrowing of AI has produced a kind of guileless acceptance of particular strands of psychological literature that have been shown to be suspect.”

Read more